最新刊期
卷 20 ， 期 5 ， 2016
- 摘要：For sustainable development, China must deal with a lot of significant major issues, such as resource shortage, environmental deterioration, ocean exploitation, climate change, and so on. As the acceleration of global economic integration process, we have to study and resolve these resource and environment problems with global view. Remote sensing is the unique and basic global observation technology to support the sustainable development, due to its advantages of synoptic view and dynamic monitoring capability for the earth system science,environmental science, resource science and global change study. After a short review of the remote sensing development history, the major international earth observation programs for human sustainable development and global change are summarized and the Chinese remote sensing technology and application status is analyzed accordingly. The most important five remote sensing frontier and challenge directions are presented as the Global Earth Observation System of Systems（GEOSS）, high performance remote sensing modeling and inversion,quantitative remote sensing product validation theory and platform, earth system model and remote sensing data assimilation, and remote sensing big data science. Finally, we point out that the remote sensing application service model should be innovated for much better services on sustainable development, global strategy and economic development. The high-resolution remote sensing satellite commercialization, Unmanned Aerial Vehicle（UAV） remote sensing development, and the remote sensing application marketization should be encouraged.关键词：remote sensing;global changes;data assimilation;big data;high resolution;GEOSS;sustainable development
- 556
- |
- 2817
- |
- 29
发布时间：2021-06-10 - 摘要：Hyperspectral Remote Sensing（HRS）, also known as hyperspectral imaging, has been considered one of the greatest breakthroughs in the remote sensing science and technology, attributed to its unique advantages in very high spectral resolutions as well as allowing for the synchronous acquisition of both images and spectra of objects. China, as one of the pioneers in HRS technology development, has made great achievements in both hypersepctral image processing and subsequent applications to real world problems under the supports of national and ministerial and provincial-level governments. These advances have bridged the gap between the most advanced theoretical contributions and their actual use in a number of applications including agriculture, mineral and energy resource exploration, environment, preservation of cultural relics, producing really rare and invaluable societal and economical impacts. This paper reviews current progresses in HRS in China, presenting main innovative achievements.关键词：hyperspectral remote sensing;imaging spectroscopy;remote sensing technology;sensor;information extraction;remote sensing applications
- 1035
- |
- 6458
- |
- 164
发布时间：2021-06-10 - 摘要："Internet Plus" represents a new form of society that provides vast platforms of reform, innovation, and development. With the gradually deepening integration of the Internet and traditional industries, the "Internet Plus" has prompted profound transformation and has generated obvious influence on many traditional industries, such as manufacturing, agriculture, finance, education, and logistics. In the big data era, the instrumental acquisition of geo-information expands from professional air-space-ground sensors, such as satellites, airplanes,and UAVs, to billions of non-dedicated sensors connected to the Internet of things. Ubiquitous geospatial data sensors with communication,navigation, positioning, photo/video imaging, and broadband data transmission functions are in development. Furthermore, millions of video cameras in cities can continuously provide images with PB and EB data size. These ubiquitous sensors can greatly enhance the data acquisition ability of geomatics. The application of geomatics is becoming increasingly pervasive, expanding from expert users to global public users. However, given the volume, velocity, variety, and veracity of data, effectively extracting useful information from big data is difficult,thus resulting in situations of "massive data, missing information, and unavailable knowledge".The ultimate goal of geo-spatial information services is to deliver the right data, information, or knowledge to the right person in the right place at the right time. To provide global all-time, all-weather services to everyone, we should overcome the defects of existing geospatial information service systems, such as limitations of coverage area, slow response, and weaknesses of systematic interoperability.Therefore, we propose an "Internet Plus" space-based information service coupled with ground networks. In line with the principles of "one satellite with multiple functions, multi-satellite networking, and multiple network cooperation", a proposal for an integrated space-based information service system is presented. This space-based network with remote sensing, navigation, and communication functions can be seamlessly integrated with existing ground Internet and mobile networks. With the support of spatial-temporal big data, cloud computing,and intelligent terminals for space-based information services, all sectors of the national economy, industries, and the vast majority of public users will be provided with rapid, accurate, and intelligent positioning, navigation, timing, remote sensing, and communication services in real time. Considering the development condition of aerospace and information technologies, we describe a trilogy of an "Internet Plus"space-based information service system construction: web GIS in the primary stage, sensor web GIS in the intermediate stage, and smart sensor web GIS in the advanced stage. The key characteristics of the three stages are emphasized. Finally, the development prospects of the"Internet Plus" space-based information service system and its key technologies are discussed.关键词：Internet Plus;space-based information service;space information network;earth observation brain
- 199
- |
- 1063
- |
- 20
发布时间：2021-06-10 - 摘要：In the past 50 years, global Earth observation has formed strong technological abilities and comprehensive systems, and played a significant role in different fields. With in-depth research on land, atmosphere and oceans, a new strategic demand for Earth Observation from space is coming forth from Earth system science and global change research. In this paper, we have proposed a new series of satellites-scientific satellites for global change research, which includes the following six satellites: atmospheric carbon satellite, aerosol satellite,night-light satellite, forest biomass satellite, glacier satellite and ocean salinity satellite; and we have presented our new suggestion entitled of "Establishing a Moon-based Earth observation system", which focuses on the observation of large scale geoscientific phenomena for its several unique advantages. Meanwhile, we have introduced our idea of a "Earth observation for the three poles environment comparison research", which approaches to study global change with new Earth observation techniques including Moon-based platform and scientific satellites.关键词：earth system science;global change;scientific satellite;Moon-based Earth observation;three poles comparison
- 222
- |
- 715
- |
- 11
发布时间：2021-06-10 - 摘要：The constantly developing laser/spectrum technology has promoted the development of atmospheric stereoscopic monitoring technology. With optical detection and spectral data analysis at the core, various high-resolution optical monitoring technologies with ultraviolet-visible light-infrared "full spectra" as detection bands, the real-time monitoring of meteorological elements and atmospheric trace constituents from near-surface to 100 km, and the experimental simulations of atmospheric multi-factors from near-surface to 50 km have gradually developed in China. With its numerous advantages, such as high sensitivity, high resolution, high selectivity, multiple component, and provision of real-time data, optical technology plays an increasingly important role in the field of atmospheric environment in China. It provides data support for the research into basic scientific issues, such as the interaction between the evolution of atmospheric pollution and meteorological processes, the formation mechanism of atmospheric fine particle pollution and photochemical smog, and the interaction between atmospheric aerosol and cloud microphysical processes. Optical technology also offers technical support to reveal the formation mechanisms of combined atmospheric pollution and to quantize their environmental influence at urban and regional scales in China.关键词：environmental optics;atmospheric environment;stereoscopic monitoring;laser spectroscopy;remote sensing technology
- 246
- |
- 659
- |
- 4
发布时间：2021-06-10 - 摘要：With the development of earth observation techniques, a large number of high-resolution remote sensing images can now be acquired by using different types of sensors. Handling these "big" remote sensing data with diverse characteristics is difficult when traditional remote sensing techniques are used. New challenges, such as high-dimensional datasets（high spatial and hyperspectral features）, complex structures（nonlinear and overlapped distribution）, and optimization problems（high computational complexity）, have also emerged. To address these problems, evolutionary computing-based techniques based on biological systems have been widely used for remote sensing image processing. Such techniques possess the following advantages:（1） powerful global optimization capability, acquiring the optimal or nearly optimal solution of objective functions;（2） self-organizing and self-learning capability, learning from original remote sensing data autonomously; and（3） capability of handling multi-objective problem, optimizing the multiple objective function simultaneously because of its population-based characteristics. Evolutionary computing has achieved preliminary success in the field of remote sensing data processing.In this paper, the applications of evolutionary computing to the fields of remote sensing image processing are reviewed, along with feature representation and feature selection, classification and clustering, and sub-pixel-level processing techniques, such as endmember extraction,hyperspectral unmixing, and sub-pixel mapping. Compared with the traditional methods of remote sensing image processing, these new methods are thought to be intelligent and accurate because of their powerful global optimization. For example, their constraints on the characteristics of objective functions, such as their derivatives, are few. They can also generate few assumptions about remote sensing data because of their self-organizing and self-learning capabilities. They can consider a large number of objective functions because of their capability of handling multi-objective problems. In summary, these new methods exhibit intelligent characteristics and high accuracy in remote sensing image processing. Finally, several crucial issues and research directions in the use of evolutionary computing are highlighted:（1）multi-objective optimization for regularization-based ill-posed problems in remote sensing processing, such as hyperspectral unmixing;（2）the discussion on the efficiency of evolutionary computing-based remote sensing processing methods, such as the memetic algorithm, which is a hybrid of evolutionary computing and machine learning, and the speeding up techniques of evolutionary computing-based remote sensing processing methods.关键词：evolutionary algorithm;multi-objective optimization;remote sensing image classification;endmember extraction;sub-pixel mapping
- 310
- |
- 1531
- |
- 24
发布时间：2021-06-10 - 摘要：This paper represents a literature review on the progress in the field of research and applications of agricultural remote sensing in the past 20 years in China. In remote sensing information retrieval, the space–ground–network integrated technical system has emerged because of the rapid development of Earth observation satellites, the booming of unmanned aerial vehicles, as well as the extensive and intensive application of wireless sensor networks and the Internet of Things in China. In quantitative remote sensing, various agricultural parameters, including LAI, soil moisture, and crop nutrients have been inverted from remote sensing data via statistical and/or mechanical models. In crop acreage estimation and crop mapping by remote sensing, considerable progress in algorithms and operational system development has been made in the past 20 years in China. In crop growth monitoring and yield estimation/prediction, quantitative remote sensing data products as well as various remote sensing indexes have been used with in-situ data. Various empirical models have also been investigated.Remote sensing data assimilation with crop growth models is a prevailing issue in this research field. For agricultural disaster monitoring and assessment with remote sensing, drought, flood, pests, plant disease, and so on have been studied with different types of remote sensing data and quantitative data products with various models. Some of these research outcomes and systems have been operational. In remote sensing for agricultural land resources, the research foci is shifting from land resources quantity research to spatial patterns and their dynamics, as well as to specific elements of agricultural lands, e.g., facility agriculture land and plastic-mulching cropland. The classification methods are more diverse, and novel methods, including object-oriented methods, machine learning methods, knowledge-based algorithms, and so on, are investigated. In the past 20 years, significant progress has been made in the research and application of agricultural remote sensing in China. In the future, an increasing number of Earth observation satellites will be in orbit with the application of the China High Resolution Earth Observation System and National Spatial Infrastructure. Sensor technology, Internet plus, big data, and artificial intelligence,among other technologies, are expected to develop rapidly. In this new era, the agriculture development pattern will change with the upgrade of the national economy and social development in China. Many new demands and opportunities will occur in agricultural remote sensing research and application. First, the space–ground–network integrated technical system for agricultural information retrieval will be applied more extensively to meet diverse demands in various agricultural sectors. Second, new techniques, including artificial intelligence,big data, and so on, will play important roles in solving critical problems in agricultural remote sensing research and applications. Third, remote sensing is expected to be applied more extensively in new sub-disciplines of agronomy, which will not only improve agricultural research but also enrich the theory and techniques in remote sensing.
- 754
- |
- 6999
- |
- 126
发布时间：2021-06-10 - 摘要：Satellite-borne remote sensing is a type of information technology that retrieves the physical characteristics of the environment/targets via scattering and radiative transfer by electromagnetic waves. A series of novel information trends for fine quantitative retrievals have emerged with the advancements of high-resolution remote sensing technology with multi-mission, multi-frequency, multi-polarization, multi-source, and multi-mode characteristics. This paper presents a general profile of the research progress during recent decades.It includes a discussion of vector radiative transfer theory of natural media and satellite-borne microwave remote sensing CAL/VAL, electromagnetic scattering theory and fully polarimetric multi-mode SAR imagery, high-resolution monitoring and ATR technology, and extraplanetary remote sensing（e.g., Moon and Mars）.关键词：scattering and radiative transfer;microwave remote sensing;SAR imagery;target recognition;information train of remote sensing
- 214
- |
- 372
- |
- 1
发布时间：2021-06-10 - 摘要：China High-resolution Earth Observation System（referred to short as CHEOS） was carried out at the end of "11th Five-Year Plan" of China, and has been comprehensive constructing independent and advanced earth observation system with the abilities of high spatial resolution, high temporal resolution, high spectral resolution and high precision, while strengthening and improving relevant infrastructure construction and forming stable operation system. CHEOS is actively meeting strategic demands for resources, environment, agriculture, disaster prevention and reduction, and so on of China, and focusing on strengthening application abilities of administrations and provinces of China, while promoting CHEOS data widely used and China’s space information industry rapid developing. CHEOS will also support China to develop into space power country from space big country at present, and promote information consumption to expand domestic demands to effectively adapt to the new normal of China’s economic.关键词：high resolution;earth observation system;remote sensing application;space information industry;big data;information consumption
- 298
- |
- 1364
- |
- 30
发布时间：2021-06-10 - 摘要：In the 1970 s and 1980 s as the new period of reform and opening up approached, the Teng Chong aerial remote sensing experiment, the Tianjin-Bohai Bay environmental remote sensing experiment, and the Ertan hydropower exploitation remote sensing experiment were performed to improve the remote sensing technology cognition of China. These remote sensing experiments were the products of an unprecedented, well-organized technological cooperation among several research bodies. Through these experiments, multidisciplinary in-tegration was implemented and a large number of high-quality professional and technical experts were cultivated. China also achieved many scientific and technological achievements as well as remarkable economic and social benefits. Using remote sensing technology, we improved our capability of recognizing our natural environment, and remote sensing integrated application was successfully introduced into China. Therefore, these experiments were collectively called the "three campaigns" of remote sensing in China. After rapidly developing and accumulating over the last 40 years, spaceborne remote sensing application has entered several important stages and is increasingly becoming a strategic emerging industry oriented through continuous accumulation, bold innovation, and rapid collection. To satisfy the demands of China’s current science, technology, economy, society, and globalization development strategies, the high-resolution Earth observation system, the national civil space infrastructure and long-term development plan, and the global earth observation system（2030） were implemented in China to help the country shift from pursuing foreign advanced technologies to pursuing research and development independently. By paving the way for space remote sensing applications to enter the stages of industrialization and commercialization, these three projects can be collectively called the new "three campaigns" of remote sensing in China. Combined with the Belt and the Road, the implementation of these "three campaigns" will enhance the "going out" strategy, expand the global service ability, and enhance the international competitiveness of China to a new level.关键词：remote sensing "three campaigns";systematic innovation;industrialization promotion;international cooperation
- 296
- |
- 844
- |
- 6
发布时间：2021-06-10 - 摘要：The Journal of Remote Sensing, which printed its first issue in 1997, publishes research on remote sensing, with a focus on the real-world effects of scientific innovations. To investigate the development of the Journal of Remote Sensing and remote sensing science in China over the last 20 years, we analyzed the status and trends of 1,804 papers published in the Journal of Remote Sensing from 1997 to2015. Based on bibliometrics, statistical investigation items are presented in this paper, including the total number of citations per year, average number of citations per paper, ranking among the top institutes and universities in terms of the annual number of published papers, annual number of papers supported by the National Natural Science Foundation of China, and so on. We also separately analyzed the quantity of publications and their citations related to standing issues and special ones. By comparing the co-occurrence relation of keywords during four periods, we conclude that with the increasing number of satellites launched successfully, quantitative retrieval models tend to become highly complex, and satellite observation technologies change from single-sensor satellite remote sensing to multi-sensor satellite remote sensing.In addition, a large number of remote sensing studies focus on multi-disciplinary crossing research, including disaster response, global change, air pollution, and food security. In this context, establishing national remote sensing application systems is imperative. Such systems will improve the state’s capacity for macro-control of the environment and resources, and they can provide a scientific basis and decision support for resource management, environmental protection, disaster reduction, and macro-control.关键词：Journal of Remote Sensing;remote sensing;statistical analysis of papers
- 263
- |
- 1360
- |
- 4
发布时间：2021-06-10 - 摘要：In order to adapt to model change of the china civil spaceborne remote sensing from scientific experiments to the business service and promote the harmonious and sustainable and development of the space remote sensing, the center for national spaceborne demonstration was timely established in 2004, to explore, understand and solve the technical problems in the application requirements and space remote sensing system docking. For more than ten years, the demonstration center took the space remote sensing system as the research object,and systematically carried out the application-oriented space remote sensing scientific demonstration concepts, theory methods, technology engineering and application research. This paper is a systemic summary of the Demonstration Center team in space remote sensing scientific demonstration research and practice for a long time, which mainly introduces the content of four aspects, i.e. the preliminary cognition of scientific demonstration, the issue concerned to remote sensing demonstration, the theoretical system and model method set of remote sensing demonstration, and remote sensing demonstration practice of the application-oriented space remote sensing system. In this paper,a scientific demonstration definition of application-oriented space remote sensing is givenfor the first time and the range and content of demonstration is also detailed analyzed, and a 3D spatial structure of remote sensing demonstration scope composed of knowledge dimension, process dimension and logic dimension is proposed synchronously. As the social development has increasingly accelerated and the informatization level has increasingly enhanced, the whole space remote sensing data information chain is driven to develop towards larger-scale data stream, shorter response time cycle, more comprehensive data integration and higher data quality, so that the space remote sensing system will step in a development phase of new "intelligent remote sensing". Owe to the rapid development of our civil space in the past ten years,we have the opportunity to participate in the FY-3 satellite flying evaluation, multi-angle polarization multispectral remote sensing sensor demonstration, and HJ satellite applicationengineering demonstration, and have made the breakthrough invarioustheory methods. These research result have been applied to several demonstrations, such asthe2030 civil space development planning, the high resolution earth observation system, the national natural disaster spatial information infrastructure, the medium and long-term development of national civil space infrastructure, the China earth observation system planning（2030） and so on. Meanwhile, the theory system of remote sensingdemonstration has been established, which includes the information flow model, information feature model, information application model, information quantity analysis model, data engineering modelsystem structure model, system state magic model, system quality model, dynamic model of system development and system model of system capability. The theoretical system for remote sensing demonstration and corresponding model method set gradually formed through practice will comprehensively reflect the structure, state and development state of the space remote sensing system, and will be used for conducting investigation, analysis, evaluation, forecast, and carrying out practical exploration on the space remote sensing system.关键词：space remote sensing system;remote sensing demonstration;information flow;intelligence remote sensing
- 239
- |
- 727
- |
- 5
发布时间：2021-06-10 - 摘要：Earth, as a single complex system, is changing; these changes affect every aspect of life on the planet and include profound implications on society. Studying the Earth system is essential to understanding the causes and consequences of climate change and other environmental concerns. Space-based observation systems explore interactions among the atmosphere, oceans, land surface interior, ice sheets,biology, and life itself under global coverage and a daily timescale. The present development trend of Earth system study focuses on the important circulation processes（such as energy cycle, water cycle, and biochemical cycle） that drive the Earth system. The water cycle is the most active cycling process and is thus the core foundation of scientific issues in the Earth system. To improve Earth system science and global change research, accurate observations of various spatial-temporal processes and key parameters of the global water cycle should be derived. Moreover, significantly improving the accuracy and synchronization of key water cycle parameter measurements necessitate the development of innovative theory and techniques for observation and retrieval.关键词：the Earth system;energy and water cycle;biochemical cycle;remote sensing observations;water cycle observation mission
- 173
- |
- 833
- |
- 4
发布时间：2021-06-10 - 摘要：In 1960, the first meteorological satellite was launched into space, demonstrating the feasibility of observing global weather systems with space technology. Today, the capabilities of meteorological satellites and remote sensing instruments have developed enormously,to the point where geostationary meteorological satellites can complete local observations every minute and polar orbiting meteorological satellites can observe the Earth’s atmosphere not only in the ultraviolet, visible, infrared, but also in microwave spectra. With the development of space technology in the past half century, meteorologists have experienced the increasing demands for the sophisticated use of meteorological satellite data. With the framework of World Meteorological Organization, the meteorological satellite constellation operated by many countries and government agencies plays an essential role in weather forecast, climate analysis, environment and disaster monitoring,etc. This paper first provides an overview of the history of meteorological satellites, with a focus on American, European, and Chinese polarorbiting and geostationary meteorological satellites, including the NOAA, GOSE, METOP, Meteosat, Fengyun, etc. This overview illustrate show meteorological satellite observation has developed from photographic to digital, from optical to microwave, and from imaging to sounding. The second part of this paper reviews the progress of satellite data applications by introducing image interpretation, quantitative data analysis, and data assimilation, as well as the scientists who made significant contributions to the methodology of data application, including Roger B. Weldon, Vernon F. Dvorak, and James Purdom. It explain show the application of satellite data has reached its maturity along with the development of space technology and how it has been integrated fully into many areas of atmospheric sciences, especially in weather forecasting. With regard to the importance of calibration for the usefulness of satellite data, the national calibration programs launched by America, France, and China are also presented. The future holds great challenges in the development of a global atmospheric observation system. Considering that some studies have published satellite development plans, we conclude the paper by highlighting geostationary microwave observation, atmospheric dynamic observation, and radiometric calibration reference satellite techniques that are currently not listed in the plans approved by meteorological satellite operators. The geostationary microwave sounder can provide high-frequency thermal structure information of ever-moving cloud systems, which is crucial to now casting. Atmosphere dynamic observation can solve the middle-scale forecast problem caused by the lack of an atmospheric wind profile, and radiometric calibration satellites are designed to establish a space-based radiometric reference for the calibration of all remote sensing satellites. These three components could become milestones in the development of meteorological satellites in the future.关键词：meteorological satellites;data application;the polar orbit meteorological satellite;geostationary orbit
- 272
- |
- 1209
- |
- 21
发布时间：2021-06-10 - 摘要：Over the past 20 years, the Chinese Fengyun meteorological satellite has progressed from the experimental phase to the operational phase, from the first generation to the second generation, from providing single observation to providing comprehensive observations,and from qualitative application to quantitative application. The Fengyun meteorological satellite has also realized the objects of operation,serialization, and quantification. Great progress has been made in data preprocessing, product generation, and data application. In the field of geolocation, the development and continuous optimization of independent geolocation algorithms have improved the geolocation accuracy of operational satellite data from 2—3 pixels to 1 pixel. In the field of radiometric calibration, the inner blackbody calibration algorithm corrected by lunar emission, the deep convective cloud calibration algorithm, the lunar calibration algorithm, and the cross calibration algorithm have been developed. On the basis of such algorithms, a comprehensive calibration system has been established to improve the calibration accuracy of solar reflective bands to 5% and thermal infrared bands to 0.5K. In the field of product generation, the Fengyun Product Generation System（PGS）and its corresponding quality control system have been established. The PGS system can output dozens of quantitative products of the atmosphere, land, ocean, and space weather. The quality of several products reaches or approaches those at the international level. Fengyun satellite data have been widely used in weather monitoring, climate analysis, ecology and environmental surveys, etc. After strict quality control and evaluation, Fengyun satellite data have been operationally assimilated into ECMWF’s operational NWP model,thus indicating that the application of Fengyun satellites has reached a new level. The meteorological satellite observation system established in China shows continuous improvement in terms of observation accuracy and service capability. However, the system cannot fully satisfy the requirements of different applications. In the future, the following aspects should be considered for the development of Fengyun satellites. First, a reasonable observation system should be established. Second, data and product quality should be improved. Third, sounding ability should be strengthened. Forth, future meteorological satellites should enhance emergency response capability. Fifth, the continuity and stability of observation should be enhanced to satisfy the requirements of climate change research. Finally, the comprehensive application capability should be enhanced to make meteorological satellites more useful.关键词：remote sensing;meteorological satellite;Fengyun satellite;radiometric calibration;payload
- 223
- |
- 1186
- |
- 11
发布时间：2021-06-10 - 摘要：Since the invention of the hyperspectral imager AVIRIS（Airborne Visible and Infrared imaging spectometer） in the United States in the 1980 s, hyperspectral imaging technology has seen rapid development for nearly 40 years. At present, hyperspectral imaging data are widely used in geology, marine science, agriculture, forestry, hydrology, urban studies, environmental science, and military fields; this wide use has played a catalytic role in sustainable economic development. The most typical representatives of hyperspectral imaging systems are the Tacsat-3 satellite ATERMIS, the Terra satellite, and the Aqua satellite MODIS. According to different imaging methods, hyperspectral imaging systems can be divided into three categories, namely, opto-mechanical scanning, push broom-type scanning, and staring. The hyper-spectral imager for opto-mechanical scanning features a large field of view and real-time calibration. The hyperspectral imager for push broom-type scanning exhibits a relatively high sensitivity; hence, a majority of spaceborne hyperspectral imagers are of this type. The hyperspectral imager for staring can obtain extremely high sensitivity and spectral resolution. Hyperspectral imaging systems can also be divided into prismatic spectrograph, grating spectrograph, and optical filter spectrograph depending on the difference obtained with the beam-split method. In recent years, hyperspectral imaging technology has seen rapid development in China. Representative instruments include the following: the successful development of an airborne OMIS system in 2000, the moderate resolution imaging spectrograph of Shen Zhou 3 in2003, and the infrared imaging spectrograph of Chang’E-3, which landed on the moon in 2013. The Fourier interference hyperspectral imager of environmental satellite 1 is China’s first interference hyperspectral imager, which launched into orbit in 2008. The Tian Gong 1 hyperspectral imager is China’s first high-resolution hyperspectral imager, which launched into space in 2011. Considering the depth of research and expansion of its application, hyperspectral imaging technology has undergone diversified development. Thus, we need to adopt new technologies to meet different application needs. This paper introduces essential technologies of the hyperspectral imaging system and their applications, including the following:（1） motion compensation spaceborne hyperspectral imaging technology of Tian Gong 1 based on prism spectrograph,（2） splitting technology in low temperature of compact thermal infrared hyperspectral imager,（3） integration of airborne ultraviolet/visible light/short-wave infrared/ thermal infrared hyperspectral imaging technology,（4） splitting technology of a step integrated filter, and（5） staring hyperspectral imaging technology based on AOTF. Given the traction of major national mission requirements,China’s aerospace hyperspectral imaging technology has achieved important progress. The breakthrough of key technologies guarantees the enhancement of the ability to obtain spectral information. The technologies identified in this paper are representative breakthroughs in the hyperspectral imaging domain. The improvement of the core component parts will result in a high spectral resolution, high spatial resolution,and great scope of the hyperspectral imaging system.关键词：hyperspectral imaging;beam-split method;spectrograph;image motion compensation;joint technology of field of view
- 287
- |
- 1294
- |
- 10
发布时间：2021-06-10 - 摘要：The Global Navigation Satellite Systems（GNSSs）, including the United States Global Positioning System（GPS）, Russian GLONASS, the European Union’s Galileo, and China’s Bei Dou, provide L-band microwave signals with high temporal resolution. These systemshave extended the applications of the GNSS from positioning/navigation to remote sensing. Since the 1990 s, the versatile refracted GNSS signals have been successfully demonstrated to sound the ionosphere and troposphere. In the pasttwo decades, reflected signals,which involve making measurements of the reflections from the Earth, have shown theircapacity for earth observations over wateror land.On the basis of such background, GNSS remote sensing, as a hybrid of GNSS and remote sensing, has been developed over the years. The concepts of GNSS remote sensing can be summarized into two categories: GNSS refractometryand GNSS reflectometry（GNSS-R）. The applications of GNSS remote sensing involves atmospheric water vapor, seismo-ionospheric disturbances, oceans, lands, hydrology, and the cryosphere. To further promote the applications of the GNSS remote sensing technology in atmospheric, seismic, and water cycle studies,this review systematically introduces the international and domestic forefront of GNSS remote sensing technology and its applications, with a focus on GNSS/meteorology, GNSS ionospheric seismology, GNSS radio occultation, ocean observations, land applications, cryosphere applications,and missions of GNSS-R. We also discuss and provide an overview of the bottlenecks related to the further development of each branch of GNSS remote sensing. The next generations of GNSS systems, especially GPS III and Bei Dou II, are expected to show improved performance and offer excellentcapabilities to users around the globe. This study can provide references for the future development of GNSS remote sensing technologiesand otherrelated subjects.关键词：GNSS remote sensing;Beidou;GPS;GNSS-R
- 654
- |
- 2298
- |
- 17
发布时间：2021-06-10 - 摘要：With the availability of the increased amount of remotely sensed data, quantitative remote sensing is in a period of rapid development. This paper reviews the recent development of the quantitative remote sensing of land surface from the two main aspects: inversion methodology and generation of the remote sensing data products. Because the number of environment variables in the atmosphere and land surface system is much larger than that of remote sensing observations, the nature of remote sensing inversion is an ill posed inversion problem. After reviewing the machine learning methods（e.g. artificial neural network, support vector regression, multivariate adaptive regression splines） and their applications, we mainly focus on seven regularization methods for overcoming the ill posed inversion problem: using multi-source data, a prior knowledge, constrained optimization, spatial and temporal constraints, integration of multiple inversion algorithms,data assimilation, and scaling. Another significant feature of the quantitative remote sensing development is satellite observations are transformed into different geophysical and geochemical parameters, namely remote sensing high-level products, for the user community by the data providers（e.g., data acenters）. This paper mainly introduces the latest development of the Global LAnd Surface Satellite（GLASS）products produced by Beijing Normal University, and the research and the development of the Climate Data Record for climate studies.关键词：quantitative remote sensing;inversion;regularization;machine learning methods;GLASS products;climate data records
- 394
- |
- 2328
- |
- 30
发布时间：2021-06-10 - 摘要：Land Surface Temperature（LST） is a key parameter in the physical processes of surface energy and water balance at local and global scales. Knowledge of LST provides information on the temporal and spatial variations of the surface equilibrium state and is of fundamental importance in many applications. This paper systematically surveys the methods for LST derived from thermal infrared remotely sensed data. These methods include single-channel, multi-channel, multi-angle, multi-temporal, and hyperspectral retrieval methods. To provide potential LST users with reliable information regarding the quality of the LST product and to provide feedback to the developers of LST retrieval algorithms for future improvement, assessing the accuracy of the retrieved LST is necessary. We review the methods used to validate LST derived from thermal infrared remotely sensed data, including temperature-based, radiance-based, and inter-comparison methods. The advantages and disadvantages of these methods are discussed. Furthermore, we review the temporal and angular normalization methods of satellite-derived LST. Finally, we present suggestions for future research to improve the accuracy of satellite-derived LST.关键词：land surface temperature;thermal infrared data;Retrieval;validation
- 837
- |
- 3895
- |
- 67
发布时间：2021-06-10 - 摘要：The scale issue in quantitative remote sensing is a significant challenge that comprises three major problems that need to be addressed:（1） the forward modeling of remote sensing signals for heterogeneous land surfaces,（2） the parameter inversion for heterogeneous land surfaces, and（3） the upscaling of in situ observation for the validation of remote sensing products. This study focuses on the third problem by reviewing the progress of upscaling research in the Heihe Watershed Allied Telemetry Experimental Research（Hi WATER）. First,we define several basic concepts associated with scaling on the basis of the probability space and data assimilation theory. These concepts include spatial average, spatial upscaling, footprint scale, pixel scale, point scale, representativeness error, observation truth, and validation threshold. Second, we introduce the multiscale observation platform of Hi WATER and multiscale observation data, which covers the scales from point to pixels, sub-basins, and the whole river basin. Third, we describe several new developments in the sampling design based on geostatistics and temporal stability analysis. Specifically, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of eco-hydrological wireless sensor network nodes, a universal co Kriging model is proposed to optimize multivariate sampling design, and a stratified block kriging is used to optimize the sampling locations in a spatial heterogeneous area. The temporal stability analysis is improved for the selection of the representative sampling points of the albedo and leaf area index. The stratified temporal stability analysis is proposed to identify the representative sampling points for monitoring long-term soil moisture at the pixel scale in high-intensity irrigated agricultural landscapes. Fourth, the representativeness of the in situ observation of solar radiation, carbon flux, soil moisture, and land surface temperature is evaluated. Results showed that the uncertainty of the validation for remote sensing products in heterogeneous areas mainly comes from the spatial and temporal representativeness of in situ measurements. Fifth, several upscaling methods are developed. The Kriging method is extended to block regression Kriging, area-to-area regression Kriging, spatiotemporal regression block Kriging, and unequal accuracy block Kriging for upscaling the in situ observation from the point-scale or footprint-scale to the pixel scale. Additionally, several case studies show that the Bayesian maximum entropy, a nonlinear method, is capable of providing a generalized theory framework to fuse general knowledge（such as that obtained from a model） and specific knowledge（such as that obtained from direct and indirect observations）. The usefulness of high-resolution remote sensing data as auxiliary information in improving the accuracy of upscaling is verified in this work. Overall, the multi-scale observation data collected in Hi WATER are helpful in improving our understanding of remote sensing scale problems.关键词：pixel-scale;representativeness error;true value;sampling design;validation;Heihe river basin
- 220
- |
- 938
- |
- 15
发布时间：2021-06-10 - 摘要：Radiative transfer models establish the quantitative relationship between remote sensing signals and physical parameters, including the object properties, the object structures and the observation geometries, on the understanding of the interactions of the electromagnetic wave and the objects. They serve as the theoretical basis for the interpretation of the remote sensing signals and the retrieval of surface parameters. Recently spatial heterogeneity has drawn widespread attention in the field of quantitative remote sensing. The increasing high resolution imagery and Li DAR data provide a strong support for the consideration of heterogeneity. For the radiative transfer modeling process over heterogeneous vegetation scenarios, the component area ratio, the 3D structure and the distribution pattern within the pixel, and the shadowing and scattering effects near the boundary, are important factors that should be considered. The recent progresses on the VIS/NIR BRDF and the TIR directional emission modeling over heterogeneous land surfaces are introduced, respectively. The key scientific issues and future development directions of heterogeneous vegetation canopy modeling are proposed at last.关键词：spatial heterogeneity;radiative transfer modeling;mixed pixel;3D structure
- 327
- |
- 852
- |
- 15
发布时间：2021-06-10 - 摘要：Satellite observations of the terrestrial biosphere cover a period of time sufficiently extended to allow the calculation of a reliable climatology. The latter is particularly relevant for studies of vegetation response to climate variability. Observations from space of the land surface are hampered by clouds at shorter wavelength and affected by water in the atmosphere in the microwave range. Both polar orbiting and geostationary satellites have a revisit frequency high enough to allow for some redundancy relative to the processes being observed, so that time series where a fraction of observations are removed and the resulting gaps filled are still very useful to monitor land surface processes. We applied the Harmonic ANalysis of Time Series（HANTS） to identify and remove anomalous observations（outliers） and to fill theresulting gaps. The HANTS algorithm has been widely used to reconstruct time series of Normalized Difference Vegetation Index（NDVI）,Leaf Area Index（LAI）, Land Surface Temperature（LST） as well as the Polarization Difference Brightness Temperature（PDBT） during the past 30 years to remove random noise or eliminate cloud/snow contamination. Several studies in North and Southern Africa, South America,Europe, China and India captured the response of the land surface to climate forcing, modulated by water availability across a range of temporal scales from hourly to decennial. These studies are reviewed to illustrate how the analysis of time series of different land surface properties reveal processes and interactions.关键词：Fourier series;phenology;Vegetation Mapping;flood monitoring;interannual variability
- 194
- |
- 652
- |
- 3
发布时间：2021-06-10 - 摘要：Leaf Area Index（LAI） is a key parameter for terrestrial remote sensing. Indirect methods are fast and efficient, and they arewidely used in ground measurement and the remote sensing validation of the LAI. These methods servea large number of industries and fields, as theircitation count is far greater than theirliterature count. This paper comprehensively reviews the development and current status of indirect LAI measurement with regard to theories, algorithms, instruments, and influence factors. The latest progress and future prospects are summarized and discussed onthe basis off our challenges, including clumping/scale effect, leaf angle distribution, woody component, and slope effect. First, the basic concepts and theoretical background are summarized to provide an overview of indirect LAI measurement. The basic concepts include LAI definition, gap probability, leaf angle distribution, leaf projection function, clumping index, needle-to-shoot area ratio, and woody-to-total area ratio. Theoretical derivations begin with the introduction of Beer’s law on indirect LAI measurement, followed by three essential adaptations concerning leaf angle distribution, clumping effect, and woody component. Second, representative methods for quantifying the clumping effect are reviewed, with the clumping effect beingthe most important factor. These methods consist of the finite-length averaging method, the gap-size distribution method, the combination of finite-length averaging and gap-size distribution method, and the path length distribution method. Third, representative instruments for indirect measurement are reviewed. These instruments include LAI-2000, TRAC, line quantum sensors（Accu PAR, Sun Scan, and LAInet）, DEMON,imaging instruments（Hemi View, MVI,and MCI）, and Li DAR. Airborne and spaceborne Li DAR are also reviewed because they also use Beer’s law as the indirect LAI measurement. Finally, four key factors that limit indirect LAI measurement accuracy are discussed. These factors are the clumping/scale effect, leaf angle distribution, woody component, and slope effect. The mixed effects of these factors are also explained.The clumping effect has attracted the most attention in the community, with several related methods having beendeveloped and being widely used in field measurement.The non-randomness inside canopies and the scale effect of measurement is also worth studying further. The theory of leaf angle distribution is well-developed, whereas the spherical distribution assumption（G≡0.5） is often used because of the inconvenience of measurement.The spherical distribution assumption should be used with caution because it is only valid near a zenith angle of 57.3°. The efforts to develop fast and automatic methods for measuring leaf angle distribution show greatpromise. The importance of woody components is widely recognized,but they are always ignored in measurement because commercial instruments are incapable of distinguishing woody components.Near-infrared technology and instruments should be applied to ground measurement to distinguish the LAI from the plant area index. The slope effect has attracted more attention than before. Research shows that it canbe ignored when the slope is less than 30°; otherwise, it could be a moderate source of error. Generally, making a break through in theories is difficult, although the main constraints have been identified and much progress hasbeen made. With a focuson these aspects, developing new instruments and calculation and validation methods, further exploring existing data, and finally improving the accuracy and stability of indirect LAI measurement are endeavors worth pursuing.关键词：leaf area index;indirect measurement;clumping effect;scale effect;leaf angle distribution;woody components;slope effect
- 284
- |
- 1359
- |
- 23
发布时间：2021-06-10 - 摘要：Earth Observation data sharing plays fundamental role for earth science research, which is an important part in the EO data lifecycle. Affected by the changing of data sharing ecosystem with resource provider/consumer/processor relationship, the sharing mechanism is presenting itself in sequential phases of rear-sharing, project-sharing, department-sharing and public-sharing. Information technologies have always driving the changing of scientific agenda of data sharing, which now can be understood as data open, data sharing and data link.Open of data means the condition of accessible via network, sharing of data means authorized method to reuse data, and link of data means scientific cross-understanding and cooperation of different data resources. Comparing with the evolution history of data sharing policy in USA, China needs to improve its sharing mechanism to be multi-win and sustainable by a dynamic adjusted data sharing socio-ecosystem.The present technical framework of earth observation data sharing is built up with implementation components of data open, data sharing,data publication and data citation, and so on. Under the revolution on cultural, political, technical and application factors for earth observation data sharing, the Next Generation EO Data Infrastructure based on deeply and widely sharing is becoming a reality. The new technical trends of earth observation data sharing as Globalization, cross-disciplinary, standardization, facility-oriented, big-data and public-engagement, will heavily change the related scientific activities in near future.关键词：earth observation;data sharing;sharing mechnism;social ecosystem;data infrastructure
- 223
- |
- 662
- |
- 4
发布时间：2021-06-10 - 摘要：In the past years, the land cover community has strived to develop and supply more datasets at different spatial scales（e.g., regional, national, or global） with increasing spatial-temporal resolutions and improved classification accuracy. Although these data products have been widely applied in climate change studies, environmental monitoring, sustainable development, and many other societal benefit areas, the user communities constantly propose new demands, such as additional land cover classes, up-to-date time series, and consistency among different datasets. Therefore, the continuous updating and content refinement of land cover data products have become key objectives of the land cover community. The updating and refinement of land cover data products differ from their original creation. Change detection with remotely sensed imagery is a major approach for updating a large area land cover, and the rapidly increasing crowdsourcing information provides another valuable resource. However, as a technical challenge is that no existing change detection algorithm can be applied to all kinds of imageries and geographic regions because of the extremely complex spectral heterogeneity of land cover classes. Therefore, an efficient change detection approach with the consideration of the existing land cover datasets needs to be developed. One cuttingedge issue is to integrate the imagery-based change intensity measurement with prior knowledge represented by existing land cover datasets.Change detection for time series imagery is moving from the comparison of two neighboring points to global trend analysis. The coupling of SAR and infrared images with multispectral images needs to be explored from several aspects, such as relative radiometric correction, spectral matching, and temporal-spatial data fusion. Another key challenge comes from the rational utilization of crowdsourcing information for updating and refining land cover. Crowdsourcing information may differ in terms of data contents, position accuracy, spatial-temporal resolution, and uncertainty, and hence, previous studies have aimed to develop appropriate methods and techniques for evaluating volunteered data quality, discovering useful information from deep web, extracting incremental changes, and integrating multi-source datasets. The increasing amount of freely accessible remote sensing data has increased the data intensiveness of the generating future land cover data products. Specific tools and systems must be designed and developed to support the updating and refining of large area land cover. One of these tools is an online land cover updating system that allows users to execute web-based land cover change detection and processing in an open web environment. The key issues in using this tool include domain-knowledge-based change detection service modeling and dynamic service composition. Data Cube is another system that has a flexible classification concept, but this tool is still under investigation. Nevertheless, this tool is expected to facilitate the on-demand extraction of land cover classes with deep learning and other data mining algorithms.关键词：land cover;remote sensed data product;updating;change detection;crowdsourcing
- 268
- |
- 792
- |
- 10
发布时间：2021-06-10 - 摘要：Important progress has been achieved in global land cover mapping in the past decade. For example, spatial resolution has increased from 300 m to 30 m. The level of classification detail has also improved from a plane level to a two-layered hierarchical classification scheme with 29 classes. However, major challenges emerge in mapping at a fine spatial scale with primarily optical data. This paper introduces the major challenges in mapping croplands, human settlements, water, and wetlands. The challenges in the use of multi-temporal and multi-sensor data, which may be useful in the future applications of remotely sensed data, are also discussed. Some of the on-going efforts to improve the quality of global land cover maps are then summarized. We argue that although harmonizing and integrating various global land cover products may be worthwhile for land cover data developed in the past, existing technologies provide sufficient data for improved map making if extra efforts are exerted. Developing and selecting effective algorithms, as well as several input variables（new types of data or features） for classification, and utilizing representative training samples are among the effective conventional measures for improving mapping accuracies at local scales. Data are more important than algorithms with regard to improving mapping accuracies. Finally, a new paradigm for global land cover mapping is proposed. This new paradigm includes a view of vegetation classes based on their types and form, canopy cover, and height. The appropriate determination of a vegetation class requires complementary information on canopy cover and height that cannot be extracted with classification algorithms. The new paradigm also suggests that a universally applicable training sample set is effective in improving land cover classification at the continental scale of Africa. To ensure an easy transition from traditional land cover mapping to the new paradigm of global land cover mapping, we recommend the creation of an all-in-one data management and analysis system. This system can be used as a foundation for a global land cover mapping portal that links freely accessible cyberspace resources and bridges data users and producers, specialists, and laymen toward a gradually evolving online global land cover mapping system.关键词：remote sensing;image classification;class definition;universal sampling;all-in-one system;on-line mapping
- 303
- |
- 1048
- |
- 19
发布时间：2021-06-10 - 摘要：Geographical Conditions Monitoring（GCM） is a novel and important aspect in the development of geoinformation science in the age of big data. Its development needs top-level design, new technology, and the establishment of a more flexible, efficient, and low cost service mode. This paper first explains the sources and characteristics of Geographical Condition and Big Data（GCBD）, which mainly comprises eight types of data, namely, Earth observation data, basic geographic information data, geographical condition census data, geographical condition monitoring change data, ground observation data, survey and investigation data, statistics data, and public source geospatial data. GCBD involves five Vs, namely, volume, variety, velocity, veracity, and value, and exhibits the characteristics of regionality, objectivity, and dynamicity. A research framework of GCBD in the cloud computing environment is then presented. A deep transformation of "geographical data, geographical information, and geographical conditions" must be achieved through the establishment of a"space–aviation–ground" integrated monitoring network, a big data warehouse and cloud computing center, and a big data service environment to provide active, intelligent, integrated, and specialized service for the public, enterprises, and governments. Finally, building a cloud platform of GCBD is discussed from the perspectives of data storage, processing, mining, and application service. The cloud platform can fulfill the requirements of GCM in rapid data processing, data mining, intelligent service, and public application. The establishment of the GCBD framework can significantly change the service mode of GCM and promote its wide application and industrialized development.关键词：geographical conditions monitoring;big data;geographical conditions and big data;cloud computing
- 168
- |
- 1076
- |
- 8
发布时间：2021-06-10 - 摘要：Agricultural information is essential for the World Food Organization, governments, food traders, and management of farms. By providing a powerful new solution, the Big Data era transforms agricultural monitoring and early warning from being model-driven to datadriven. Along with their rapid growth, Big Data and cloud computing technologies provide an innovative means for agricultural monitoring and early warning. Since 2013, Crop Watch, a remote-sensing-based global agricultural monitoring system, has gradually introduced various techniques that deal with Big Data, such as cluster analysis, time series analysis, correlation analysis, and spatial and temporal abnormal pattern analysis, into the operational system. Big Data technologies have successfully enhanced the data mining capability of Crop Watch and expanded the spatial and temporal coverage of agricultural monitoring and early warning. Big Data has also had a catalytic role in promoting the service-oriented agricultural information cloud service. Big Data has also become an important driving force in upgrading the principles of the Crop Watch agricultural monitoring and early warning system. In the future, with the help of Big Data, agricultural monitoring and early warning systems are expected to move toward fully automated monitoring, real-time management, and precise agriculture information service direction. Volunteered geographic information in the Big Data era provides an efficient technique for acquiring Big Data for agricultural monitoring and early warning. Based on the capacity of cross-cutting data mining technology, the diversification of crop-border information services will become the mainstream direction of agricultural information services in the Big Data era. With the use of Big Data technologies, Crop Watch will transform into a Big-Data-driven agricultural monitoring and early warning system.关键词：big data;agriculture monitoring and early warning;data mining;cloud service;volunteered geographic information
- 329
- |
- 2136
- |
- 20
发布时间：2021-06-10 - 摘要：Remote sensing images can provide important and abundant information about the Earth at a global or local scale. Thus, many applications often require remote sensing data with high acquisition frequency and high spatial resolution. However, meeting this requirement is a considerable challenge given satellite limitations. The spatiotemporal fusion method provides a feasible way to solve these "spatialtemporal" contradictions.In the last 10 years, spatiotemporal fusion has elicited wide interest in various applications because it integrates the superiority of multisource satellite data in fine spatial resolution or frequent temporal coverage and it can generate fused images with high spatial and temporal resolution. In this study, we reviewed the advantages and limitations of three types of method for spatiotemporal fusion, namely, transformation-based, reconstruction-based, and learning-based methods. First, the transformation-based method consistently filters and processes transformed data and then accesses high-spatiotemporal resolution data via inverse transform. It mainly focuses on the spatial and spectral information of multi-source satellite image enhancement or fusion. The spatial resolution of the results obtained with this method remains low, and the accuracy is relatively poor because the temporal change information is not used in this method. Second, the reconstruction-based method has elicited much attention since the proposal of a semi-physical fusion model and STARFM. This method integrates the information of temporal change, spatial change, and spectral change among multi-source satellite images acquired in different times and generates high-spatiotemporal resolution data by calculating the weight of different changes. This method provides an excellent fusion approach for spatiotemporal fusion because the results show high accuracy.However, the results would be poor when the type of land cover changes or the cover area is heterogeneous. Third, the learning-based method is based on the development of compressed sensing and sparse representation technology. This method represents a recent developmentthat relies on learning the relationship and difference of multi-source satellite images by training samples and constructing an image dictionary. Although the learning-based method could obtain good results, the processing efficiency is lower than that of other methods, and it requires the training of sample selection. Recently, the result of spatiotemporal fusion has been used in various applications, especially in the reconstruction-based method. This method is mainly used in time series data analysis as well as in retrieval and regional data set generation. For time series data analysis and retrieval, many researchers have used the results in developing the missing images of time series, detecting phenology, inversing urban environment parameters, estimating gross primary production, evaluating biomass, calculating land surface temperature, and so on. Given that the covered area of a low spatial resolution is large and the spectrum continuity of spatiotemporal fusion results is high, these results could be applied to the generation of regional data sets. Although the spatiotemporal fusion method has seen considerable development, certain problems remain. The uncertainties are attributed to the complexity of land cover change, the errors of sensor calibration, and the data pretreatment process. The five potential aspects of the spatiotemporal fusion method that require further study are the consistency of data from different sensors, introduction of nonlinear mixed models, addition of prior knowledge, introduction of deep learning theory, and expansion into other satellites.关键词：multi-source data;remote sensing;spatial-temporal contradictions;high spatiotemporal fusion;Model
- 412
- |
- 1752
- |
- 18
发布时间：2021-06-10 - 摘要：Data fusion is an important means of improving the applicability of remote sensing images, and has long been a hot research topic in the remote sensing field. This paper reviews the progress and future of remote sensing data fusion. First, the hierarchy and category of data fusion are summarized, and remote sensing data fusion methods are classified into four categories, namely, homogeneous data fusion,heterogeneous data fusion, fusion for remote sensing observation and station data, and fusion for remote sensing observation and non-observed data. Second, this paper discusses spatio-temporal-spectral fusion of optical remote sensing data, including multi-view spatial fusion,multi-scale fusion, spatio-spectral fusion, spatio-temporal fusion, and integrated spatio-temporal-spectral fusion. Third, this paper discusses the prospective direction of remote sensing data fusion literature, including the extension of integrated spatio-temporal-spectral fusion,across-scale fusion from aerospace to ground observations, online fusion in sensor web environment, and application-oriented fusion.关键词：remote sensing image;data fusion;spatio-temporal-spectral integration;multi source;sensor
- 777
- |
- 3446
- |
- 49
发布时间：2021-06-10 - 摘要：Hyperspectral remote sensing is an important technique in Earth observation. Hyperspectral image processing and information extraction is one of the key issues in hyperspectral remote sensing. This paper introduces the major characteristics of hyperspectral remote sensing. It also summarizes and reviews the development history and current advancements of hyperspectral image processing and information extraction, which mainly comprises four aspects: data dimensionality reduction, pixel unmixing, image classification, and target and anomaly detection. Moreover, the high-performance computing technique in hyperspectral image processing and information extraction is summarized and analyzed. In the future, the technical developments of intelligent information analysis and high-performance processing based on hardware indicate that the hyperspectral remote sensing satellite system will enter an intelligent era. Therefore, the present studyindicates three aspects that should be considered in hyperspectral image processing and information extraction. First, a multidisciplinary connection should be emphasized, and new achievements in the fields of machine learning and artificial intelligence should be fully adopted.Second, close attention should be given to the integration of software and hardware to develop a high-performance technique for processing hyperspectral images in real time. Finally, the advantages and characteristics of hyperspectral remote sensing should be extensively explored,and the development of new theories and new methods should integrate the requirements of various applications.关键词：hyperspectral remote sensing;data dimensionality reduction;Pixel Unmixing;image classification;target detection;high performance computing
- 631
- |
- 4399
- |
- 83
发布时间：2021-06-10 - 摘要：Hyperspectral images, which span the visible to infrared spectrum with hundreds of contiguous and narrow spectral bands, are advantageous because of their subtle discriminative spectral characteristics. Owing to the fine spectral differences between various materials of interest, hyperspectral images support improved interpretation capabilities, and they perform important functions in various fields, such as the military, precision agriculture, and mineralogy. The sparsity of signals is a powerful and promising statistical signal modeling tool for hyperspectral image processing and analysis because signals can be compactly represented by only a few coefficients that carry the most important information in a certain basis or dictionary.A full diagram of Sparse Representation（SR） consists of sparse coding（regression） and dictionary learning. A brief review about this basic theory from the perspective of hyperspectral remote sensing is presented in the second section. With various forms of complex degradation and the demand for resolution enhancement considered, basic theories as well as recent studies in the area of hyperspectral image processing, including denoising, unmixing, super-resolution, and spectral-spatial image fusion in an SR manner, are presented in the third section. Dimensional reduction, classification, target detection, and anomaly detection, which are aimed at mining subtle diagnostic information on hyperspectral images in an SR manner, are also reviewed in the hyperspectral image analysis section. This review is followed by some suggestions and remarks on SR-based hyperspectral image processing and analysis. Processing literature considers denoising as the most fundamental task, single image super-resolution as problematic, and hyperspectral unmixing and spectral-spatial fusion as necessary subjects. In the hyperspectral analysis area, classification and detection are the most important tasks, and feature extraction/dimensional reduction works as a meaningful pre-processing step. The research on SR-based hyperspectral processing and analysis has recently attained some achievements. However, the obstacles mentioned in this paper still require further study. This review also presents several important remarks and outlines the future directions in this field. First, despite the increasing research on hyperspectral signal recovery and reconstruction, single image super-resolution and multi-resolution image fusion remain a problem area,mainly because of the limited availability of prior information within the remote sensing data and because of unstable sparse inverse optimization. Thus, the method for qualified over-completed dictionary design for specific hyperspectral image processing and delicate inverse optimization is an important study area. Second, the most important issue for hyperspectral image information extraction comes in the form of a discriminative dictionary. Most research ideas on hyperspectral target detection involve multiple sparse representation classification-based model simplification, whereas the anomaly detection method relies on the quality of the local ambient dictionary. Thus, the detection area should be studied further. In addition, reasonable approximated sparse coding combined with specific dictionary learning and some unique characteristics of hyperspectral images, such as manifold structure, multi-modality, and low rank property, should be regarded as useful tools for future research.
- 300
- |
- 1586
- |
- 31
发布时间：2021-06-10 - 摘要：Spectral Mixture Analysis（SMA） is one of the main topics in quantitative remote sensing research. It is able to provide land cover information at sub-pixel levels for practical applications. With the emergence of improved algorithms, SMA has made significant progress in many aspects, including spectral mixture models, endmember determination, endmember fraction inversion, and accuracy assessment. This study focused on these four key components in SMA and reviewed the available models and algorithms developed in last two decades. Moreover, the deficiencies of existing studies were analyzed. These deficiencies include the absences of widely accepted model selection criteria for linear and nonlinear spectral mixture analysis models and the unstable inversion of existing spectral mixture analysis caused by the high spectral correlation between endmembers. Finally, the study summarized the directions for future research, which include quantitatively evaluating the amplitude and spectral shape of multiple scattering among endmembers, identifying the factors that contribute to the nonlinear component in mixture observed signals by using radiative transfer models and laboratory measurement experiments,improving the robustness of linear spectral mixture analysis models, and suppressing high sensitivity to noise error signals resulting from collinearity with some insights from available statistical regression models for collinearity issues.
- 286
- |
- 1396
- |
- 25
发布时间：2021-06-10 - 摘要：As a result of the increasingly convenient access to high temporal resolution data, and even video remote sensing data, a large amount of historical data have accumulated in recent years. Accordingly, change detection technology using remote sensing time series data has achieved rapid development and has become a hot research field in remote sensing, especially after the successful launch of "GF-4","Jilin No.1", and Skysat satellites. Thus, change detection research with time series remote sensing data has entered a brand new stage. This review systematically summarizes the research progress and application of Remote Sensing Series Data Change Detection（RSSDCD）. Considering the significance and advantage of applying time series analysis in change detection, we start this work by identifying the time series change detection methods in other fields. Then, according to the requirements of RSSDCD, we divide the methods into two categories: methods for anomaly detection for emergencies and methods for the detection of gradual and constant changes in land use/cover types. This review presents the latest progress and methods for these two types of purposes and presents discussions about their advantages and disadvantages. The remote sensing time series data exhibit the following characteristics: seasonality, instability, locality, multi-scale,time-space autocorrelation, multi-dimension, and huge quantity. This review introduces an anomaly detection method based on empirical mode decomposition and a land use/cover gradual change detection method based on hidden a Markov model. Instances for both approaches are offered as references for related research and application. A conclusion about the latest trends and existing issues in this field is drawn after tracking recent research on RSSDCD. Future works are also discussed.关键词：time series;change detection;anomaly detection;land use/cover;empirical mode decomposition;hidden Markov model
- 508
- |
- 2805
- |
- 21
发布时间：2021-06-10 - 摘要：Global change research consistently requires the combined use of cross-sensor images with similar spectral wavelengths. To meet the temporal resolution and coverage requirements of remote sensing applications, new requirements are proposed for remote sensing image processing technology. Such technology requirements are related to how to obtain geometric consistency between cross-sensor/multi temporal data, how to obtain radiometric normalization, and how to obtain land cover class labels that are consistent between cross-sensor/multi temporal data. They are also related to highly automated processing. For the above requirements, we propose a framework for the automatic processing of remote sensing images with "an invariant feature point set"（IFPs） as the control data set. Specifically, we combine the spatial and temporal alignment in geometry space, radiation space, and land cover class space into a unified framework and thereby provide an indirect means to achieve fast processing. The key technologies for building IFPs are also reviewed.关键词：remote sensing image processing;invariant feature point set;control point set;image controt point;Pseudo-In variant features;active learning;deep learning
- 187
- |
- 469
- |
- 20
发布时间：2021-06-10 - 摘要：LiDAR can be used to obtain forest spatial structure and terrain under canopy with high precision by transmitting laser energy and receiving returned signals. Full waveform LiDAR is able to record whole energy of returned signal and characterize vegetation vertical profile with sub-meter. Discrete return LiDAR records single or multiple echoes from stratified canopies. Spaceborne LiDAR usually configures laser profiling system with full waveform or photo counting technique to acquire single or multiple beams data under satellite orbit for vertical structure or change observation of forest at regional or global scale. Airborne LiDAR often use laser scanning system with discrete return or full waveform technique to obtain scan data within special FOV under flight trajectory for structure measurements of forest at stand or regional scale. Terrestrial LiDAR mainly carry laser scanning system with discrete return technique to get scan data within spherical space centered at observing station for detecting vertical structure of individual trees or forest stand. Inversion methods of individual tree parameters may be group into three category including CHM-based, NPC-based and voxel-based methods. CHM-based methods recognize tree tops by local maximum algorithm, and detects crown edges or crown main direction by region growth or image segmentation. NPC-based methods distinguish individual trees by spatial clustering or morphology algorithm. Voxel-based methods identify tree crown by region growth or spatial clustering algorithm in 3D voxel space. Forest stand parameters can be estimated using individual tree based or canopy height distribution based method. The features of canopy height distribution may be extracted from point cloud or full waveform. Multiple temporal LiDAR can be used to monitor forest growth, biomass change, structure changes caused by deforestation or disaster. It will be widely used in the field of operating organization or scientific research such as forest inventory, ecosystem modelling, etc. as the development of LiDAR technique.关键词：lidar;forest;individual tree;forest stand
- 491
- |
- 1992
- |
- 2
发布时间：2021-06-10 - 摘要：Atmospheric delay effect is unavoidable and sometimes serious when using spaceborne repeat-pass synthetic aperture radar interferometry（InSAR） to generate Digital Elevation Models（DEMs）. InSAR atmospheric correction methods come in various types. However,they are rarely used in InSAR DEM generation. The method based on atmospheric numerical models offersunique advantages.It can estimate atmospheric water vapor field at the SAR data acquisition time, and it is not affected by clouds. Therefore, this work studies the atmospheric correction strategy and method during the process of InSAR DEM generation based on the atmospheric numerical model called the Weather Research and Forecasting（WFR） model to improve the accuracy of the generated InSAR DEM.First, atmospheric correction strategies are discussed. These strategies include the proper settings of WRF Preprocessing System（WPS）to make the temporal and spatial scales of WRF results match those of SAR data, as well as the selection of a proper atmospheric correction timing to improve the accuracy of InSAR DEMs. One of the key issues of InSAR is phase unwrapping, and atmospheric correction removes the residual atmospheric phase from the interferometric phase of SAR data. Thus, there are two possible atmospheric correction timings: before phase unwrapping and after phase unwrapping. Atmospheric correction before phase unwrapping is theoretically helpful for phase unwrapping because the contribution of the atmosphere is removed. Atmospheric correction after phase unwrapping is commonly used in the field of Differential InSAR（D-InSAR）, and its efficiency has been validated. The topographic phase in the process of D-InSAR is removed before phase unwrapping, which makes phase unwrapping easier than that in the process of InSAR DEM generation. A method of atmospheric correction based on WRF results is then introduced. The direct output results of WRF are not atmospheric water vapor field, which is needed to calculate the residual atmospheric phase. Thus, a method for transforming the direct output results of WRF to integrated water vapor（IWV） andthen transforming the IWV to the residual atmospheric phase is introduced. The original coordinates of the WRF results are transformed to the coordinates of SAR data. A workflow of atmospheric correction during the process of InSAR DEM generation is proposed. Experiments are carried outwith Terra SAR-X data to validate the efficiency of the proposed methods. The accuracies of the generated InSAR DEMs with residual atmospheric phase corrected at each possible timing are compared. The compared qualitative and quantitative results prove that the atmospheric corrections work at both timings and that the atmospheric correction before phase unwrapping performs well. However, the atmospheric correction before phase unwrapping may not always work or may worsen the accuracy of the DEM resultin regions where interferometric qualities are poor. The proposed methods are then applied to the fusion of multi-baseline and multi-frequency InSAR results, with the experimental resultsalso proving the efficiency of the methods and the good performance of atmospheric correctionin regions of good interferometric quality.关键词：atmospheric correction;DEM;WRF;InSAR;multi-baseline multi-frequency
- 233
- |
- 495
- |
- 2
发布时间：2021-06-10 - 摘要：With the construction and development of the national space infrastructure, many breakthroughs have been made in the research and construction of remote sensing monitoring systems in China. The national capability for environmental remote sensing monitoring has been developed independently. The operation of production and service for the main environmental remote sensing monitoring elements is achieved; such operation has provided strong support for national environmental management in the new period. Firstly, on the basis of the analysis of the domestic and international development of environmental remote sensing and the application demands of environmental remote sensing monitoring in China, this paper elaborates on the necessity and urgency of developing environmental remote sensing monitoring systems in the country. At present, the demand of environmental remote sensing applications continues to increase. Application demands for remote sensing of atmospheric environment include the atmospheric particulates near surface and haze monitoring, the distribution of burning point and ecological impact of straw burning monitoring, dust, polluted gases and greenhouse gases monitoring. Application demands for remote sensing of water environment include bloom, water quality, flooding monitoring, risk sources of source of drinking water monitoring, water ecology, human activities of river shore monitoring, and ecological condition of the catchment area monitoring. Application demands for remote sensing of ecological environment include investigation and assessment of national ecological environment,human activity monitoring in natural protection area, habitat monitoring in biodiversity priority area, destruction of the ecological resources monitoring in the development zone, and the ecological monitoring in the ecological protection red line area, urban and rural areas, ecological function region, cross-border area. Secondly, the establishment and operation of the national environmental remote sensing monitoring system are investigated, which is composed of satellite system, technique system and operation system. An environmental special satellite monitoring system which is composed of HJ-1, GF-5 and atmospheric environmental monitoring satellites etc., a suit of water, atmospheric,ecological environmental remote sensing technology which are proposed by Satellite Environment Center Ministry of Environmental Protection, and the environmental remote sensing operation system composed of atmospheric monitoring, water monitoring, ecological monitoring and environment supervision are introduced in turn. The long time practice has proved that the setup and operation of the national environmental remote sensing monitoring system has providing the key support and efficient service for China’s environmental protection work. Finally, the development of China’s environmental remote sensing monitoring system and focus on the next step are proposed.关键词：environmental remote sensing;monitoring system;research and operational application
- 221
- |
- 1291
- |
- 21
发布时间：2021-06-10 - 摘要：The research and application of disaster remote sensing in China has achieved fruitful results given the deepening disaster system theory and the rapid development of remote sensing technology. On the basis of disaster system theory, this study comprehensively summarizes the research progress of disaster remote sensing theory from the aspects of the three-dimensional "space-air-ground" disaster monitoring system, disaster element classification system, disaster remote sensing service system, and standard and specification construction. The methods for the remote sensing monitoring and assessment of disasters are also analyzed. The significant issues in application research and existing problems are discussed. The three stages of the development of China’s disaster remote sensing system are then introduced. The system architecture of the operational system of disaster remote sensing is proposed on the basis of application needs. The business application mode is described according to the disaster remote sensing monitoring of daily business, emergency monitoring business, and major natural disaster damage assessment. Moreover, the business application development level is evaluated in terms of timeliness, evaluation accuracy,and business process. Finally, opportunities and challenges faced by the current disaster remote sensing research and applications are analyzed. Some suggestions, such as strengthening the research on disaster remote sensing mechanism, accelerating the space infrastructure construction for disaster prevention, strengthening the research on disaster monitoring and assessment methods, enhancing the comprehensive service capability using disaster spatial information, and strengthening soft environment construction, are suggested for future development.关键词：natural disaster;remote sensing;disaster monitoring;disaster assessment;research progress
- 497
- |
- 2380
- |
- 35
发布时间：2021-06-10 - 摘要：China attaches great importance to the development of marine remote sensing and monitoring technology. The ocean remote sensing systems with complementary vantages offer significant economic and social benefits. HY-1A/B data have been widely used in seasurface temperature forecasting, sea ice operational monitoring in winter, red tide and green tide monitoring in summer, dynamic monitoring of coastal zones, coastal water quality monitoring, and fishery remote sensing. The HY-2A satellite fills the gaps of ocean dynamic environment satellite remote sensing and is the world’s only in-orbit comprehensive ocean dynamic environment satellite that carries active and passive microwave remote sensors. HY-2A can simultaneously obtain data on sea-surface wind field, significant wave height, sea surface height, and sea surface temperature. The effectiveness of ocean environment monitoring and catastrophic sea condition forecasting has been improved with the use of satellite data. Ocean satellites provide reliable remote sensing data to the national economy and defense construction, marine scientific research, and global change research. They also play an important role in the international Earth observation system and are highly recognized by domestic and foreign users.HY-1 and HY-2 series satellites lay a solid foundation for the establishment of a sound ocean environment stereo monitoring system in China. With national development and the implementation of "the Belt and Road" strategy in China, the construction of maritime power, the safeguarding of marine rights and interests, and the development of marine economy demand high requirements and emphasize the urgent need for ocean remote sensing. Therefore, the "Long-term Development Plan of Civil Space Infrastructure（2015—2025）" is focused on the national maritime power strategy and establishes the plan for the ocean satellite series. This development plan is aimed at supporting the areas of marine resource survey, environment protection, disaster prevention and reduction, rights and interests safeguarding, management of sea areas, island and coastal zone investigation, and the polar ocean expedition of China. Moreover, the requirements of land and atmosphere observations are taken into account. On the basis of the development experience and application achievement of HY-1A/B, HY-2A, GF-3, and CFOSAT, multiple optical and microwave remote sensing techniques are developed, a new generation of ocean color and ocean dynamic environment satellites is built for marine networking observation, and ocean monitoring satellites are improved to construct an integrated marine satellite monitoring system. Ocean remote sensing satellites will inevitably play an import role in the process of building maritime power through the construction of space infrastructure.关键词：ocean remote sensing;sea color satellite;ocean dynamic environment satellite;ocean monitoring satellite;observation system
- 424
- |
- 2381
- |
- 24
发布时间：2021-06-10 - 摘要：Global mountainous areas account for about 24 percent of the total global terrestrial area. The mountain area in China makes up approximately 65 percent of the national land area. Thus, China can be described as a mountainous country. Mountains are an important resource foundation and are a vital ecological defense for the existence and development of human beings. However, because of the special energy gradients, mountainous regions are centralized areas for the development of natural hazards. Besides, mountainous areas also serve as a sensitive indicator for global change studies because of their vertical environment gradient. Mountainous areas has become a hotspot and area of focus for many earth system studies. Remote sensing is one of the most important and effective tools for mountain studies. It can provide continuous spatio-temporal land cover, feature status, and historical change information. However, given the dramatically different geometric characteristics of mountainous surface and the various special ecosystem structures and functions, remote sensing applications in mountainous areas still face many challenges and difficulties, including serious geometric and radiometric distortion problems, more complex energy balance process, and more prominent ill-condition retrieving problem for ecosystem parameters than that of the plain area.Mountain remote sensing, which mainly focuses on the basic theories, methodologies, and integrated applications of remote sensing in mountainous environments, is a research branch of the remote sensing science. Although the word "mountain remote sensing" firstly began to be used in the middle 1980 s, the research on remote sensing in mountainous areas can be tracked back to nearly 100 years ago because topographic mapping began early in the photogrammetry remote sensing field. In recent decades, issues regarding the basic theories and integrative applications of mountain remote sensing have attracted worldwide attention. Mountain remote sensing has become one of the most popular research areas in remote sensing sciences. We summarized the scientific significance and several frontier issues in mountain remote sensing studies. Currently, the main contents of mountain remote sensing research should include but not be limited to the following aspects:（1） the interaction mechanism and modeling theory between electromagnetic signatures and mountain land surfaces;（2）spatial–temporal–spectral normalization methodologies for mountainous remote sensing data;（3） remote sensing modeling, retrieving, and assimilation methodologies for land surface information in mountainous areas;（4） scaling effects and the validation of remote sensing products in mountainous areas; and（5） the integrated applications of remote sensing information in mountain studies. Currently, mountain remote sensing faces unprecedented developing opportunities because of the following reasons:（1） emerging novel remote sensing observation technologies,（2） in-depth development of basic theories and methodologies of mountain remote sensing,（3） driving forces from earth science big data studies, and（4） great application demands of mountain remote sensing. In this work, we reviewed the research progresses of basic theories and applications of mountain remote sensing in recent years, and analyzed the opportunities, challenges, and future prospects of mountain remote sensing in the modern era.关键词：mountain remote sensing;Model;scale conversion;ill-conditioned inversion;data assimilation;topographic effect
- 376
- |
- 1129
- |
- 12
发布时间：2021-06-10 - 摘要：A coastal zone is a special geographical zone that connects marine and terrestrial systems. Itis closely related to human existence and development. However, its natural and ecological environments are extraordinarily vulnerable and sensitive. Climate changes and human activities have large impacts on coastal zones, including the deterioration of the ecological environment. With technical advancement,remote sensing has become an important method in the geo-environmental monitoring of coastal zones, as well as in the planning, management, and protection of coastal zones. This paper reviews the main data sources, methods, and limitations of the applications of remote sensing techniques（i.e., land use/cover, soil quality, vegetation, coastal line, water color, water depth, underwater topography, and disaster） in the geo-environmental monitoring of coastal zones. The prospects for future development are also discussed.Moderate or low resolution（e.g., MODIS, Landsat TM/ETM+, and SPOT）, hyperspectral resolution（e.g., ground-based ASD reflectance, Hyperion, Hymap, and CASI）, and high resolution（e.g., Quickbird, World View, and Pleiades） remote sensing data have been widely used in the monitoring of land use/cover, soil quality, vegetation, coastal line, and water color in coastal zones. Airborne laser radar, microwave, and synthetic aperture radar（e.g., ALOS PALSAR and In SAR） data are mainly used in the monitoring of water depth, underwater topography, and disasters in coastal zones. Multi-source data fusion（e.g.,Li DAR-hyperspectral and high-resolution hyperspectral） provides a new method for improving monitoring accuracy. The classification and extraction or quantitative retrieval of land use/cover, soil quality, vegetation, coastal line, water color, water depth, underwater topography, and disasters are the main processes in the geo-environmental monitoring of coastal zones. The main methods for classification and extraction are maximum likelihood, vegetation index, support vector, artificial neural network, object-oriented, decision tree, and random forest. The main methods for retrieval are statistical regression, physical modeling, and semi-empirical modeling. The cloudy and rainy environment in coastal zones is the biggest limitation in high-quality optical imagery and the continuous monitoring of land use/cover, soil quality, vegetation, coastal line, and water color. The retrieval of coastal soil quality with airborne and satellitebased hyperspectral images and the retrieval of the biochemical parameters of coastal vegetation have received minimal attention. The universality of water color models is mainly affected by atmospheric correction and study area. The retrieval accuracy of water depth is not guaranteed owing to the indirect measurement of water depth. Acquiring remote sensing data at random times and sites in the presence of sudden and catastrophic incidents in coastal zones remains difficult. Finally, this study proposes the following research prospects to further develop and improve the geo-environmental monitoring of coastal zones with remote sensing techniques: strengthening the multidiscipline collaboration on research methodologies; developing multiple sensors and monitoring platforms for monitoring measures; focusing on multi-source data fusion and assimilation in data processing;emphasizing data mining, intelligence, and physical models in information extraction; and paying attention to the integrated management and sustainable development of coastal lines in information application.关键词：land use/cover;soil quality;vegetation;coastal line;watercolor;water depth;disaster
- 434
- |
- 2306
- |
- 26
发布时间：2021-06-10 - 摘要：This paper presents a review of lunar exploration missions and techniques, as well as the products of lunar mapping using remote sensing data. Since 1958, 126 lunar exploration missions have been carried out, and 70 of these missions were successful. Lunar exploration missions can be broadly classified into unmanned and manned missions, with unmanned probes mainly using an orbiter, a lander, and arover. Lunar surface mapping using remote sensing data is one of the fundamental tasks in these missions and is critical to support other science or engineering tasks. Lunar mapping is more challenging and difficult compared with Earth mapping because orbit and attitude determination is of relatively low accuracy, a global navigation satellite system is lacking, obtaining ground truth for geometric and radiometric calibration is difficult, and the lunar surface is a desolated environment with poor image texture. A vast amount of remote sensing data have been acquired from successful missions. The two primary data sources for lunar mapping are orbital optical images and laser altimeter data. Among the optical images, the Chang’E-2 stereo images cover the entire moon surface with 7m resolution, and the narrow-angle images of the lunar reconnaissance orbiter camera offer the highest spatial resolution of up to 0.5 m but with limited coverage. Among the laser altimeter data, the lunar orbiter laser altimeter data of the lunar reconnaissance orbiter show the highest precision and density. Orbital remote sensing data provide facilitate global and regional mapping with medium and high resolutions,where slander and rover images offer the highest resolution（up to millimeter level） for the detailed mapping of the landing site and traversing area. Photogrammetric techniques, including geometric sensor modeling, image block adjustment, stereo image matching, space intersection for 3D position computation, and DEM and orthophoto generation, have been developed by the planetary mapping community for lunar mapping from orbiter, lander, and rover images. The rigorous sensor models of orbital images are usually established by collinearity equations with interior and exterior orientation parameters. Bundle adjustment is a rigorous block adjustment method that simultaneously solves exterior orientation parameters and 3D ground points with high accuracy and consistency. A generic geometric model, with a rational function model as the representative, has been investigated and used in lunar mapping. Unlike rigorous sensor models, rational function models are simple and independent of sensors. It is particularly advantageous for integrated mapping using multiple images from the same orbiter or different orbiters. Global image mosaics and global DEM have been produced by mission teams with resolutions ranging from tens to hundreds of meters.Sub-meter to meter resolution regional maps have been produced for scientific investigation orthe selection of landing sites. Centimeter resolution maps have been generated from lander or rover images to support in-situ investigations and rover traverse planning at landing sites. Some future research directions of lunar mapping using remote sensing data are discussed at the end of the paper, along with the construction of a new-generation lunar global control network using the newly acquired multi-mission data, fine-resolution lunar mapping using multi-mission multi-coverage images, automated processing of huge amount of data, lunar mapping standards, data sharing, and international cooperation.关键词：lunar exploration;lunar mapping;remote sensing data;photogrammetric technique
- 241
- |
- 688
- |
- 11
发布时间：2021-06-10 - 摘要：Remote sensing applied to land resource research has received increasing interest because of the excellent agreement of the temporal and spatial characteristics of remote sensing data and land resources. In the past decades, the development of remote sensing technology has greatly enriched the method and content of geography research. As one of most important directions of geography research, the research on land resources and the environment is carried out using remote sensing techniques. Remote sensing provides voluminous amounts of information and improves the depth of land resource research. With the support of the periodic acquisition of information via remote sensing, data information in land resource research is subjected to dynamic monitoring and updating. Extensive dynamic land resource information, such as quantity, distribution, composition, and type conversion, can be extracted from remote sensing data. Modern process analysis and change prediction for land resources have gradually become research hotpots because of the results of the monitoring of land resource changes. The research directions in relation to the remote sensing of land resources should focus on the following vectors in the future. First,research methods should be innovated to match the application requirements in China. Many research studies in China still focus on tracking,citing, consummating, and verifying the content and method of foreign models. Models suitable for the Chinese environment should be developed in the future. Second, remote sensing applications should be combined effectively with traditional disciplines. Maintaining consistency with traditional research in terms of concepts and connotations, clarifying the relationship of remote sensing parameters and their geoscience implications, and realizing the organic combination of land resource information and remote sensing parameters can improve the applicability and interpretability of research results. Third, the development of remote sensing applications for land resources should meet the requirements of global change research and consider large spatial regions, long time processes, and multiple observation angles. Given the different geographical elements of different regions, the consistency of temporal and spatial cognition should be emphasized against the background of global change research. Finally, applications should promote comprehensive analysis and evaluation to embody the relationship between human beings and land resources. The influence of this relationship on the sustainability and quality of the development process should also be studied.关键词：Land resources;land use;land cover;remote sensing;application research
- 355
- |
- 2757
- |
- 27
发布时间：2021-06-10 -
- 摘要：Worldwide land use change and urban spatial expansion have replaced the vegetation-dominated natural landscape with various impervious surfaces. This replacement has brought about significant negative impacts on the global ecological environment and has raised public awareness of the emergence of this key ecological environment indicator. Impervious surfaces have become an important consideration in many environmental-or socioeconomic-related studies. Quickly gathering information regarding the magnitude, location, geometry,and spatial pattern of impervious surfaces and accurately quantifying the dynamic information on impervious surfaces have become urgent issues to be addressed. Today’s remote sensing technology can provide a promising solution to this problem owing to its rapid, repetitive,synoptic, and multi-scale Earth observation. The remote sensing of impervious surfaces has made considerable progress after its development in 2000, and various innovative techniques for the retrieval of impervious surface information have been proposed in the last decade.Therefore, we examined these innovative approaches and focused on their advantages and disadvantages through a literature review. Chinese research and achievements regarding the remote sensing of impervious surfaces were also summarized. The current remote sensing of impervious surfaces has made great progress, and many of the techniques for the information extraction and classification of impervious surfaces achieve an accuracy of over 85%. Nevertheless, the mapping of impervious surfaces remains a challenge. The main problem is the confusion between impervious surface information and bare soil/shadow information, which affects the accurate retrieval of impervious surface information. Most impervious surface materials are made of or directly from rock, sand, or clayish soil. Thus, impervious surfaces exhibit similar spectral characteristics. Existing multispectral remote sensors lack sufficient spectral resolution to distinguish impervious surface materials from bare soil. Thus, using the techniques on the basis of spectral characteristics alone hampers the improvement of the accuracy of impervious surface inversion. Other secondary data, such as Li DAR data, are expected to help solve this bottleneck in future research on the remote sensing-based retrieval of impervious surfaces.关键词：impervious surface;remote sensing;information retrieval;image processing;ecological environment
- 294
- |
- 2773
- |
- 65
发布时间：2021-06-10 - 摘要：Geographic knowledge, which is the higher level of geographic information, is acquired on the basis of geographic background,process, and results. The expression and sharing of geographic knowledge is important in many applications for urban and environmental planning and for any application in territorial intelligence. Expressing and sharing geographic knowledge is a significant issue in current geographic research. This paper is based on the evolution of geographic language from maps to geographic information system（GIS） and virtual geographic environments（VGEs）. It aims to review the capability of VGEs to support geographic knowledge expression and sharing. To investigate the characteristics of different geographic languages and thusexpress and share geographic knowledge, we divided geographic knowledge into three levels: factual knowledge, rules and control knowledge, and decision-oriented knowledge. The evolution of geographic languages and their capability to support geographic knowledge expression and sharing were reviewed by discussing the relationship between geographic world, geographic language, and geographic knowledge. VGEs have more power to support geographic knowledge expression and sharing compared with maps and GIS. The outstanding features of such new generation of geographic language were reviewed considering their contributions to geographic knowledge expression and sharing. The features include interactive visualization, multi-channel perception, virtual reality technology, model base and model management, and spatially distributed collaboration. 1. Interactive visualization, multi-channel perception, and virtual reality technology enhance the expression of geographic world and geographic knowledge. The distance between geographic knowledge "writer" and "reader" is shortened. Thus, reaching a consensus on the expression and understanding of geographic knowledge becomes easy. Users in this virtual environment, which is the counterpart of the geographic world, can easily share geographic knowledge, unlike in traditional maps or dimension-reduced GIS. 2. Two cores of VGEs, data base and model base, are helpful in expressing and reusing geographic knowledge. Model base, which includes statistical models and dynamic geographic models, is the output from geographic facts and rules. Such geographic knowledge can be accumulated and reused by different users through an integrated model base. Users can analyze and simulate geographic phenomenon and process and acquire a high level of geographic knowledge to manage the geographic world. 3. Geo-spatial collaboration is developed in VGEs to support experts from multiple, spatially distributed disciplines and allow these experts to collaborate in conducting geographic simulation and analysis. In this way, they can share knowledge and obtain scientific cognition of the geographic world. Air quality problem is a crucial issue for the government of Hong Kong and the Pearl River Delta region. Thus, a VGE platform is developed for users from multiple disciplines to conduct air quality simulation and visual analysis by coupling meteorological and air quality models. In multiple perspectives, this case study analyzed the capability of VGEs in expressing and sharing geographic knowledge, with VGEs including virtual reality technology, geographic model base and management system, dynamic visualization, and geo-spatial collaboration technology. VGEs are under development and face key challenging issues. This paper is concluded with a discussion on future research concerning geographic knowledge creation, management, and application.关键词：geographic knowledge;geographic language;virtual geographic environments;knowledge sharing
- 142
- |
- 763
- |
- 7
发布时间：2021-06-10 - 摘要：Short-term heavy rainfalls have become the norm as the climate changes. However, previous city drainage design is often unable to cope with this rainfall pattern. Thus, the damage caused by urban flood disasters is high, especially because of relatively high population densities. Several sudden rains in Taiwan have caused flooding in the cities in recent years. Taichung’s Shalu area experienced flooding because of the heavy rains brought by typhoons Sura, Tam Mei, and Su Li from 2012 to 2014. The Taichung City Government has made flood remediation investments and has built wireless sensing devices to convey real-time flooding information. However, a considerable amount of resources are required to establish a complete monitoring network, and such requirement is unachievable in practice. Therefore, how to use innovative tools to enhance cities’ flood adaptability has become an important issue. As a result of the popularity of smart phones, an increasing number of people publish personal information on popular Internet communities, such as Facebook, Flickr, Twitter, and Plurk.Using their smart devices, people can take pictures and post information to share with community members. The shared information is tagged with coordinate points. Information from a large group of people can thus be screened and integrated for use as valuable flood information.This study investigates the online descriptions of direct experiences during flooding events to obtain the spatial information of floods through semantic retrieval and filtering analysis and thereby identify flood patterns. Sensed disaster data, credible information extracted from Internet communities, and the use of such information as city flooding information can effectively support the assumptions and limitations of physical sensing mathematical models, particularly in terms of the degree of effective operation and adequate maintenance of urban drainage systems and grid mode homogenization. This study, which on urban flooding events in history, extracts real-time flood-related information from online communities, such as Facebook, and compares the actual values of the flood for spatial analysis. Moreover, this study filters VGI on the basis of semantic meaning and obtains 49 "rain"-related descriptions. The descriptions are matched to the flood spatial information reconstructed with FLO-2D simulation, with the result indicating that the distribution correlation is significant. The method of converting human-sensed non-structured information from Internet communities into usable spatial information, extracting usable information available in online communities, converting this information into disaster prevention information, and using physical-sensing FLO-2D simulation to reconstruct flood spatial information for a correlation analysis is unique and innovative. Results show that a non-task-based,non-specific community can compensate for the insufficiency of detective equipment and further provides flood information. Rainfall situations in other areas can be detected with this method and be framed using Facebook’s community check-in information to detect possible flooding ranges. Using flood information from online communities to provide initial flood information and to govern cities with broad areas is a feasible method.关键词：flood;semantic mining;social flooded measurement;volunteers space information
- 233
- |
- 266
- |
- 1
发布时间：2021-06-10 - 摘要：Economic and social development planning, urban planning, and land use planning are statutory plans in China. However, China faces a "three planning separation" problem because these plans have different planning principles, technical standards, and approaches,thereby resulting in conflicts. To eliminate such conflicts, the "three-plan integration" program was introduced in China in 2013. Many cities, such as Guangzhou, Shanghai, and Xiamen, have attempted to achieve such integration. As a basic technology for solving problems related to "three planning separation," the geographic information system has been very helpful in the quantitative analyses of spatial information. Apart from traditional spatial analysis, combining GIS with the location-allocation model, cellular automata（CA）, or multi-agent model provides an innovative alternative in the quantitative analysis of the decisions made in urban planning. The geographical simulation andoptimization applications not only simulate and optimize the land use systems in complex environments but also provide sufficient information for preparing planning scenarios. However, because of the lack of theoretical and practical support, these applications remain in the primary stage. Therefore, advanced GIS analytic models must be developed to devise effective methodologies for integrating the three aforementioned plans. In this paper, we summarized the geographical simulation and optimization applications from the perspective of geographic information science from national and international studies. The Geographical Simulation and Optimization System（GeoSOS） comprises three components, namely, CA, Multi-Agent Systems（MAS）, and swarm intelligence. This system compensates for the weakness of the general GIS software, which cannot perform advanced spatial analyses, and satisfies the demands of complex simulation and optimization. We reviewed several geographical simulation and optimization methods, including CA, MAS, ant colony optimization, and Particle Swarm Optimization（PSO）. We also summarized the GeoSOS applications related to planning ecological control, urban growth boundary, and permanent basic farmland protection. GeoSOS technologies have been proven to be capable of solving the problems encountered in these applications. The framework associated with geographical simulation and optimization has been used as the theoretical and methodological support of the "three-plan integration." This framework aims to provide various techniques, such as the Pareto strategy, Pareto simulated annealing,non-dominated sorting genetic algorithm, multi-objective PSO, and multi-objective immune system algorithm, for solving the multi-objective optimization problem in "three-plan integration." High-resolution land use imageries have been increasingly used for solving planning problems. A very large data volume must be used when various sources of spatial data are used in implementing large-scale simulation. However, previous studies have utilized high-performance computation techniques for geographical simulation and optimization, for establishing eco-designated line of control, and for generating predictions and early warnings of illegal development.关键词：three-plan integration;cellular automata;multi-agents;Geographical Simulation and Optimization System（GeoSOS）
- 155
- |
- 1031
- |
- 3
发布时间：2021-06-10
- Postal code：100190
- Tel：010-58887052 Email：nrsb@aircas.ac.cn
- Technical support is provided by Beijing Founder electronics co., LTD 京ICP备20021838号-9
京公网安备11010802024621 - It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
- Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.
0