最新刊期
卷 28 ， 期 6 ， 2024
- “在地球观测领域，专家建立了地球观测知识枢纽EOKH体系，探索了知识共享与复用技术，为提升地球观测系统效能提供解决方案。”
摘要：Intelligently sharing and reusing the knowledge developed by application practices are the keys to break through technical barriers and fully activate and release the effectiveness of Earth Observations (EO). The Earth Observation Knowledge Hub (EOKH), which is used to couple decentralized knowledge bases organically, is a research frontier for the governance and intelligent service of global EO applications. In the design of Group on Earth Observations (GEO), the GEO Knowledge Hub (GKH) is intended to provide authoritative, validated, and reproducible content for evidence-based reporting on policy commitments and decision-making. Thus, the GKH offers a platform for users to discover, learn about, and employ methods, analytical tools, and applications; it also provides opportunities for the GEO community to collaborate and provide mutual assistance related to GKH contents. However, important lessons, such as the sensitive issue of intellectual ethics and how to profit GKH from the recent technological advances in information technologies, have been learned during the implementations. In response to the problems and insights encountered by GEO in developing GKH, we systematically analyzed the connotation and characteristics of EOKH and sorted out the fundamental needs and challenges for the development of EOKH in China.First, we systematically analyzed the connotation and characteristics of EOKH. The study argues that EOKH is the intersection node of high-throughput trusted EO knowledge in knowledge-sharing networks. It has three typical features, i.e., connectivity, high throughput, and lightweight computing. Its core mission is to identify and transfer valuable research in a timely manner and to promote high throughput of application packages. Second, we sorted out the fundamental needs and challenges for the development of EOKH in China. Considering the latest progress in the study of EO ontology, we also analyzed the possible key technical problems and gave strategies to cope with them. On this basis, the system architecture prototype of EOKH, which is drawn on the system design concept of representational state transfer, is proposed, and an ontology model of conceptual EO knowledge and a formalization model of process-oriented EO knowledge are established.The study argues that EOKH should be in an open collaborative environment where humans are in the loop. The key technologies are system metrics, knowledge transfer, knowledge reuse, and knowledge exploration and visualization. The transfer and reuse of knowledge packages can greatly enhance the ease of development and reuse of EO application practices. Ontology modeling helps formalize the intrinsic connection between the human-cyber-physical systems of EO application and enhances the interpretability of higher-order complex problems.EOKH transforms knowledge sharing from point to point at the element level to group collaborative at the system level, which not only reduces the cost of cross-industry and socially integrated EO applications but also avoids repetitive research inputs, helps break through technical barriers and cognitive obstacles, and releases the effectiveness of satellite digital economy services comprehensively. The study argues that connecting EO knowledge in the human–cyber–physical systems and exploring high-throughput knowledge coproduction and transfer technology in a “humans-in-the-loop” environment are necessary to enhance the interpretability of tacit EO knowledge and promote the competitiveness and activeness of EOKH.关键词：remote sensing;Knowledge hub;Earth observations;ontologies;knowledge packages;knowledge recusing;cyber-physical-social systems;humans in the loop- 920
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发布时间：2024-07-19 - “在植被干旱遥感监测领域，专家综述了当前研究现状，并展望了未来发展方向。研究表明，监测方法的发展趋势是精细化、综合化和智能化。未来研究方向包括机理模型和学习模型耦合的反演技术，基于两阶段梯形模式的温度异常探测方法，以及植被干旱响应规律指导的深度学习监测模型。”
摘要：Drought has been a serious threat to Chinese food and ecological security. Satellite remote sensing has unique technical advantages in vegetation drought monitoring and early warning, and it is an important means to further improve the defense ability of drought disaster in most countries including China. Based on the perspective of drought disaster system, this paper firstly divided the remote sensing monitoring methods of vegetation drought into three categories: drought-causing factor monitoring method, vegetation condition monitoring method, and comprehensive monitoring method. For the first category, the degree of drought was expressed mainly by measuring the degree of abnormality of the drought-causing factor, which usually utilizes a long time series of drought-causing factor data (i.e., rainfall, soil moisture, air temperature, evapotranspiration, etc.), and calculates the degree of deviation from normal for the evaluation period by taking the average state of the same period of many years as the normal state. For the second category, the degree of drought was mainly measured by the anomaly degree of vegetation condition under drought stress, where the vegetation condition includes vegetation greenness indexes, vegetation moisture indexes, vegetation fluorescence indexes, and vegetation temperature indexes. The comprehensive monitoring method mainly measures the degree of vegetation drought by integrating drought-causing factors, vegetation conditions, and environmental parameters (e.g., land cover type, agriculture irrigation, ecoregion, soil hydraulic parameters, etc.). After reviewing the current research status, we found that: (1) the overall development trend in the remote sensing of vegetation drought is ‘refinement’, ‘integration’, and ‘intelligence’, which means that the future remote sensing monitoring methods should be more faster, more sensitive, higher resolution, more comprehensive, smarter and so on; (2) The main challenges are: the remote sensing spatial resolution of vegetation drought background and characteristic parameters is still coarse, and the time series is still short and delayed. The existing vegetation drought remote sensing comprehensive monitoring models do not yet effectively integrate water, fluorescence, and temperature anomaly indicators. The response of vegetation canopy temperature, greenness, water, and fluorescence anomalies to drought stress has not been fully understood, and the establishment of existing drought remote sensing comprehensive monitoring models lacks the constraints or guidance of vegetation response laws to drought stress. (3) Future research directions include: Inversion and quality improvement of vegetation drought parameters with couple of mechanism model and learning model, vegetation canopy temperature anomaly detection technology based on two-stage trapezoidal model, and comprehensive monitoring model based on vegetation drought response law guiding deep learning algorithm. This study is helpful to break through the key technical bottleneck of drought remote sensing monitoring and accurately serve the needs of national disaster prevention and mitigation and ecological civilization construction.关键词：remote sensing;Vegetation drought;soil moisture;canopy temperature;fluorescence anomaly;comprehensive monitoring;deep learning- 1041
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发布时间：2024-07-10 - “在遥感地学分析领域，专家提出了基于等级斑块建模的循环迭代式分析框架，为地学知识引导下的遥感大数据智能解译提供新思路。”
摘要：In the past two decades, Geographical Object-Based Image Analysis (GEOBIA) has been widely studied and applied; however, it still does not meet the expectation for big remote sensing image analysis in geographical cognition activities in terms of accuracy and intelligence. We think that the major problem is the lack of geographical thoughts to lead the research and development (R&D) of GEOBIA key techniques, especially when introducing the techniques of computer vision, which does not regard comprehending the earth’s surface as the objective.On this basis, we review the concepts of GEOBIA from a geographical perspective, specifically the principles of region, scale, and pattern and function. From the region principle, we regard the image segmentation in GEOBIA grouping the spatial neighbor pixels sharing similar spectral and textures as the representation of a fine-scale geographical zoning in remote sensing image spaces. From the scale principle, we regard the multiscale of segmentation as the representation model quantifying the relationship of geographical zones among different scales. From the pattern and function principle, we regard the multiscale segmentation as an ideal hierarchical patch model representing the earth surface structure, i.e., the landscape, and could quantify the pattern (e.g., orientation, shape, arrangement, distance, etc.) for the function recognition. In other words, we think that the target of GEOBIA is to recover the hierarchical multiscale structure of the earth’s surface from the remote sensing images so that we can quantify the structure and then recognize and comprehend its function.On the basis of these reviews, we propose an iterative GEOBIA framework where the core is constructing a hierarchical patch model of the earth’s surface. The framework starts with fusing the big geographical data, including remote sensing images, existing geographical thematic maps, and other helpful knowledge, to construct an initial hierarchical patch model of the earth’s surface. Then, object features are extracted from the hierarchical patch model, and the function of these objects is recognized; the features include the internal features extracted from the object itself (e.g., shape and spectrum) and the external features extracted from its relationship with other objects (e.g., its neighbor objects, parent objects, and children objects). Finally, the recognized results are used to update the hierarchical patch model for the next recognition cycles. With the iteration of the remote sensing image analysis, the accuracy of geographical object recognition can be improved because we also have a more accurate hierarchical patch model describing the earth’s surface due to the updating process, which could provide an accurate calculation of the object’s features.To achieve the above proposed framework, we also propose a few suggestions for further R&D, such as constructing different hierarchical patch models for different geographical elements, fusing multiresolution images by using the hierarchical patch model instead of pixels, and choosing the suitable interpretation models instead of one model for different big geographical patches.We hope the above insights could provide an instructive idea of how to embed geographical knowledge into intelligent interpretation models to extract new knowledge from big remote sensing images with improved accuracy.关键词：Geographic Information Science (GIS);remote sensing geoscience analysis;object-based classification;remote sensing intelligent interpretation;Geographic Object-Based Image Analysis (GEOBIA);Geo-knowledge graphs;earth observation;pattern;scale;region;hierarchy;patch;remote sensing big data- 306
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发布时间：2024-07-19
Reviews
- “最新研究揭示了黄海、渤海和东海浮游植物粒径等级的时空变化规律，为海洋生态环境监测提供了重要数据支持。”
摘要：Phytoplankton are indispensable part of the marine ecological environment, and their size class PSC (Phytoplankton Size Class) is a key parameter to describe the vital role of phytoplankton in different geobiochemical cycles. The Yellow Sea, the Bohai Sea and the East China Sea are located in the eastern part of China as a whole, shown as semi-closed characteristics. The PSC field measurement is mainly dependent on the in situ cruise observation experiments carried out in recent years. The sampling points are sparse and uneven in space and time. Therefore, it is necessary to use high Remote sensing inversion technology with a wide range of frequency and coverage to fill the insufficiency of field measured data.Based on the sea surface remote sensing reflectance products of MODIS/Aqua sensors from 2002-08 to 2022-05, this paper applies the PSC remote sensing inversion model constructed by Sun et al. (2019) to produce PSC long-term data set. The data set is stored in the standard format of Matlab and contains 238 files in total, which are easy to read by each software (DOI: 10.17632/mjg5s9p4wp.3). The product accuracy verification results show that the satellite inversion and the field measurement results are relatively consistent (the average absolute percentage error is 22.9%, 11.4%, and 35.0% for micro, nano, and picophytoplankton, respectively). At the same time, the comparison of spatial distribution in different sea areas shows that the PSC inversion after reconstructing the chlorophyll a concentration is closer to the field measured value.The statistical results of the long-term distribution of PSCs based on this dataset show that the coastal waters are mainly enriched by microphytoplankton, while the offshore waters are primarily dominated by nanophytoplankton. Judging from the multi-year monthly averaged PSCs in five specific areas, taking microphytoplankton as an example, there are “double peaks” in spring (May) and summer (July) in the center of the Bohai Sea and the mouth of the Yangtze River, while the North Yellow Sea area presents a spring (April), autumn (October) peak feature. Meanwhile, the spring peaks in the offshore waters of the South Yellow Sea and the East China Sea are more significant in April and March, respectively.This dataset is helpful for fine-grained analysis and understanding of the temporal and spatial variation of phytoplankton in the Yellow Sea, the Bohai Sea, and the East China Sea. It can also be used as a routine project for water environment monitoring and is worthy of popularization.关键词：Remote sensing dataset;phytoplankton size class;Bohai Sea;Yellow Sea and East China Sea- 576
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发布时间：2024-07-19
Data Article
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Remote sensing of surface meltwater routing in the Denmark Basin of the Northern Greenland Ice Sheet AI导读
“格陵兰冰盖北部融水研究取得新进展，揭示冰面—冰前融水汇流过程对冰面消融强度的响应，为全球气候变化研究提供重要参考。”
摘要：Mass loss from the Greenland Ice Sheet (GrIS) has accelerated in recent decades, with profound effects on global sea-level rise. During each summer, the meltwater forms supraglacial rivers and then is transported to the proglacial zone, eventually flowing into the ocean and forming a continuous supraglacial-proglacial river system. This continuous supraglacial-proglacial drainage system directly results in the mass loss of the GrIS and has an important impact on the changes in the marine environment. Satellite images can directly observe the temporal and spatial distribution of supraglacial and proglacial rivers and have been widely used in the study of the GrIS. The satellite-derived observation can provide key information, such as the location, morphology, and dynamic changes of rivers. It has become an important way to analyze meltwater routing. In this study, 361 scenes of Sentinel-2 and Landsat 8 satellite images are used to extract the supraglacial and proglacial rivers in the Denmark supraglacial-proglacial basin of the northeastern GrIS during the melt seasons (from July to August) and monitor their spatial distribution and dynamic changes. Furthermore, satellite-derived observation and meltwater runoff simulated by regional climate models (MARv3.12 and RACMO2.3p2) are compared and analyzed, and then the lag time of the supraglacial-proglacial drainage system is estimated. The main contents and conclusions of this study include the following three aspects: (1) The proglacial river width is in the range of 100—2000 m and experiences a seasonal trend. The ice surface meltwater shows similar variation characteristics, advancing to the high-altitude areas of the ice surface (up to ~1400 m) at the initial stage of ablation, and then gradually receding to the edge of the ice sheet (up to ~500 m). (2) A significant positive correlation is found between satellite-derived proglacial river width and meltwater on the ice surface (R=0.87, P<0.01), forming a continuous supraglacial-proglacial drainage system that can effectively transport the meltwater each summer. (3) MARv3.12 and RACMO2.3p2 models can accurately simulate the meltwater runoff in the supraglacial-proglacial drainage system on a large area and long-term scale, and the simulated meltwater runoff and satellite-derived ice surface meltwater (MAR: R=0.87; RACMO: R=0.84, P<0.01) and proglacial river width (MAR: R=0.89; RACMO:R=0.88, P<0.01) have strong correlations. (4) The r between the simulated lagged meltwater runoff and satellite-derived proglacial river width (MAR: R=0.93; RACMO: R=0.92, P<0.01) increased, which is significantly higher than that of the instantaneous meltwater runoff. The optimal lag time of the supraglacial-proglacial drainage system in the Denmark Basin is approximately 2 days. This lag time quantitatively represents the efficiency of meltwater routing in the supraglacial-proglacial drainage system.关键词：ice melting;supraglacial river;proglacial river;river remote sensing;polar remote sensing;Greenland ice sheet- 45
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发布时间：2024-07-10 - “在格陵兰冰盖流速监测领域，研究人员提出了一种基于Sentinel-1 SAR影像的数据处理流程，有效提高了流速时序的时空分辨率和数据覆盖率。”
摘要：Monitoring the Greenland glacier flow velocity is essential for the quantitative estimation of ice sheet material loss, the assessment of the impact of global climate change on ice sheet dynamics, and the evaluation of Greenland’s contribution to current sea-level rises. The offset-tracking technique is the main method for deriving glacier velocity by using the intensity information of SAR or optical images. Intensity offset tracking is less sensitive to decorrelation than the InSAR method and can be applied to images with long temporal intervals. However, glacier avalanche, ice avalanche, snowfall, and melting–freezing cycles on glaciers still cause changes in the scattering characteristics of the surface, resulting in changes of the SAR image intensity, leading to a loss of correlation in matching between images, especially in summer. To provide more accurate glacier flow velocity field, this research proposes a novel data processing strategy of processing Sentinel-1 SAR data and takes the famous Petermann outlet glacier in Greenland as an example to extract its glacier velocity based on image tracking. Noise and errors in tracking images formed by single pairs of Sentinel-1 images are removed through morphological opening operation, connectivity analysis, adaptive median filtering, etc. Meanwhile, annual and monthly Greenland ice flow velocity products are employed to select datum by taking its low-speed area as reference. We also introduce flow direction of the annual or seasonal glacier flow to filter out wrong matchings. Similar to the small-baseline analysis of the InSAR technique, redundant observation of tracking pairs with 6-, 12-, and 18-day intervals are then applied to the Singular Value Decomposition (SVD) method to solve the time series of glacier velocity and to avoid the possible rank deficit. SVD is iteratively performed to remove the observed coarse error that could not be eliminated in the previous processing by checking residuals of the observation after each iteration. We obtain the time-series glacier velocity for the Petermann Glacier from the year 2018 to 2020 with a temporal resolution of 6 days. Compared with the published glacier velocity products, our derived results are less noisy, more continuous, smoother, and cover more area than the CPOM product, which employs the same data source. Compared with the PROMICE product produced from multitrack SAR, data show that we share similar accuracy and effective data coverage, but the results of this research have higher resolution and are less noisy, especially in summer. We conclude that the proposed algorithm can effectively eliminate the anomalous matching of single offset-tracking pair for forming high spatial and temporal resolution glacier flow velocity time series with redundant matching pairs by using an iterative SVD method, which is essential for monitoring glacier flow velocity for the Greenland Ice Sheet with satellite SAR images.关键词：remote sensing;Greenland ice sheet;glacier velocity;SAR;Sentinel-1;Offset-Tracking;singular value decomposition- 790
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发布时间：2024-07-10 - “最新研究揭示了高亚洲冰川消融季反照率与年际物质平衡的显著正相关性，为理解冰川物质平衡变化提供了新视角。”
摘要：Albedo is an important parameter that controls the absorption of solar radiation by the glacier surface and affects the rate of glacier ablation. Previous studies have found a significant correlation between the minimum or average albedo during the ablation season and annual mass balance in several High Mountain Asia glaciers. Due to the diverse types and complex change mechanisms of High Mountain Asia glaciers, the ability of ablation season albedo to characterize the annual mass balance in different types of glaciers and their regional characteristics needs to be further understood. Using the MODIS ice/snow albedo data and in-situ annual mass balance time series from the years 2000 to 2019, this study analyzed the interannual variation characteristics of four ablation season albedo parameters for 23 glaciers in High Mountain Asia and evaluated the correlation between different ablation season albedo parameters and annual mass balance. We also discussed the impact of albedo change on the annual mass balance in different glacial subregions and glacier types (maritime, sub-continental, and extreme continental). In the past 20 years, the albedo of studied glaciers in High Mountain Asia has shown a decreasing trend, except for those in the western Himalayas and the Qilian Mountains. The fluctuation of the minimum albedo during the ablation season is more drastic than that of the average albedo; their values are concentrated in the ranges of 0.1—0.4 and 0.3—0.6, respectively. We found that the interannual variation and the long-term trend of ablation season albedo are consistent within the same glacial subregions. Among the four ablation season albedo parameters, the average albedo derived from the eight-day composite albedo data shows the strongest correlation with annual mass balance. 13 glaciers exhibited a significant linear positive correlation (P<0.05); the highest coefficient of determination is 0.98 for the Gurenhekou glacier, and the lowest is 0.28 for Urumqi glacier No.1. Moreover, the linear correlation between ablation season albedo and annual mass balance shows no obvious regional differences and is not limited by glacier type. There are still 7 glaciers whose albedo did not show a significant correlation with the annual mass balance, mainly due to factors such as glacier size, the number of in-situ annual mass balance measurements, and the quality of albedo estimation. Our study demonstrates that the average albedo outperforms the minimum albedo in reflecting changes in annual mass balance. Since the minimum albedo represents a single time-phase value, indicating the peak absorption of solar radiation, it is susceptible to the influence of perturbing factors such as cloud cover and sudden snowfall. However, the average albedo, which integrates solar radiation absorption over the entire ablation season, better mitigates the influence of the aforementioned perturbing factors and exhibits a stronger correlation with annual mass balance. This study serves as a valuable reference for enhancing our understanding of the impact of ice and snow albedo on glacier mass balance in High Mountain Asia.关键词：remote sensing;glacier albedo;glacier mass balance;MODIS ice/snow albedo;High Mountain Asian- 661
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发布时间：2024-07-19
Remote Sensing of Cryosphere
- “城市地表温度遥感研究取得新进展，从二维方向温度到三维表面温度，为精细城市热环境评估提供新视角。”
摘要：Urban land surface temperature is an important indicator of the energy budget of urban underlying surface and local climate change. Remote sensing is an important tool to obtain urban land surface temperature at a large spatial scale. Remarkable urban three-dimensional structure and complex urban surface materials substantially influence the directional variation in upwelling thermal radiance. Thermal infrared remote sensing typically provides an average temperature (i.e., directional temperature) of all component surfaces in a sensor’s field of view at a specific viewing direction. The directional temperature varies with the sensor’s observation angle and differs from the true distribution of urban surface temperature. The term “complete surface temperature” was proposed to represent the characteristics of urban surface temperature to characterize the energy exchange between the urban underlying surface and the atmosphere. Currently, “complete surface temperature” has only made a breakthrough in describing the average state of urban surface temperature, but it still cannot reflect the high-resolution spatiotemporal characteristics of urban surface temperature and cannot meet the needs of fine-scale assessments of urban thermal environment.In this review, we summarize the development of urban surface remote sensing temperature from “directional temperature” (2-dimensional) to “complete surface temperature” (2.5-dimensional) and then to “3-dimensional surface temperature” (3-dimensional) and the current progress in using remote sensing directional observations to obtain urban surface temperature in different dimensions. We also clarify the differences and interrelationships of different dimensions. The application of remotely sensed urban surface temperature in different dimensions is also elaborated. On the basis of the existing problems, the future development trend of remotely sensed urban surface temperature is determined as follows: (1) definition of three-dimensional urban surface temperature for different application purposes, (2) stereoscopic observation for the reconstruction of three-dimensional urban surface temperature, and (3) coupling of three-dimensional surface temperature products and urban climate models.关键词：urban remote sensing;land surface temperature;directional temperature;complete surface temperature;three-dimensional surface temperature- 965
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发布时间：2024-07-19 - “最新研究揭示新疆城市化进程：21世纪以来，新疆城市化发展整体向西南扩张，南疆地区发展迅速，城市化演化经历缓慢、波动、加速三个阶段，城镇地区发展均衡，乡村地区差异化发展。”
摘要：Given that Xinjiang Uygur Autonomous Region is a strategic barrier and an important platform of opening up to the western region, assessing its urbanization is critical to promote the national reform strategy and the Belt and Road Initiative. Compared with traditional method, nighttime light (NTL) remote sensing has been proved to be able to monitor human activity intensity and regional comprehensive development level in a more objective, flexible spatial scale and wider coverage. NTL remote sensing data has been able to analyze the urbanization evolution process and the level of social and economic development, but it is still necessary to expand and enrich the breadth and depth of research, especially to explore its spatial pattern and long-term evolution process, so as to more comprehensively understand the urbanization process and social development balance in Xinjiang.This paper comprehensively analyzes and discusses the evolution process of NTL in Xinjiang since the 21st century from three dimensions: time change trend, spatial distribution pattern and social development equilibrium, using NTL remote sensing data of long time series from 2000 to 2020, time series decomposition, spatial standard deviation ellipse and Night Light Development Index (NLDI).(1) From 2000 to 2020, the total amount of NTL in all regions of Xinjiang Uygur Autonomous Region increased to varying degrees. In terms of spatial pattern, urbanization in northern and eastern Xinjiang developed steadily, while rapid development in southern Xinjiang. The planning and construction of transportation lines is one of the important driving forces for the spatial expansion of urbanization in Xinjiang. (2) In the past 20 years, the total amount of NTL in Xinjiang has increased by 5.30 times, and the growth trend is accelerating. The NTL intensity in rural areas of Xinjiang increased by 7.60 times, which was larger than that in urban areas (4.10 times). The process of urbanization in Xinjiang can be divided into three stages: slow development (before 2007), volatile growth (from 2008 to 2014), and rapid development (after 2015). Policy support and the transformation of industrial and agricultural development make Xinjiang’s urbanization transition from the slow development period to the volatile growth period. The growth rate of the volatile growth period is nearly three times that of the slow development period, but at the same time, it is also disturbed by various extreme events. (3) From 2000 to 2019, the NLDI in most areas of Xinjiang decreased, the distribution of population and infrastructure construction in the whole region and most cities in Xinjiang became more reasonable, and the social development showed a trend of balanced development. However, compared with urban areas, the balance in rural areas of Xinjiang is weaker. This is due to the low starting point of urbanization development in rural areas of Xinjiang, which is still in the stage of rapid development, and urbanization is undergoing a process of “from point to surface”, so the current social development balance in rural areas shows a trend of decline. In general, the urbanization process of Xinjiang has been developing rapidly and evenly since the 21st century.关键词：nighttime light remote sensing;urbanization evolution;time series decomposition;Night Light Development Index;Xinjiang Uygur Autonomous Region- 1486
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发布时间：2024-07-19
City and Land
- “在定量遥感领域，研究者扩展RAPID模型，通过纹理矩阵精细模拟地表反射光谱，显著提升图像模拟精度，为深度学习提供高质量样本。”
摘要：Three-dimensional (3D) Radiative Transfer (RT) simulation is an important method to use in studying the mechanism of quantitative remote sensing and improving inversion accuracy. Computer graphics combined with laser scanning data or photogrammetry images can help produce realistic centimeter-level vegetation scenes, including leaves, branches, trunks, and ground polygons. Current 3D RT models can utilize these kinds of reconstructed scenes to simulate decimeter-level spaceborne or airborne remote sensing images. However, sparse forest areas still exhibit some deviations between the simulated and actual images. Such deviation is somehow due to the reconstruction error of the 3D structure of the trees or understorey, while the limitation of the average component spectrum of soil background plays another role, which hardly reflects the random heterogeneity of surface reflectance.To solve the second problem, this study extends the 3D radiosity applicable to porous individual objects for directional reflectance over complex vegetated scenes (RAPID) model, adding two weight-coefficient texture matrices based on the end-member spectra of bare soil and dense vegetation, realizing the finer simulation of surface reflection spectrum. A multispectral or hyperspectral image or at least an RGB image containing the background texture information should be given as input. First, the Normalized Difference Vegetation Index (NDVI) can be used to extract the pixel spectra of bare soil (NDVI:~0.2) and dense vegetation (~maximum NDVI). Second, the two weight coefficients for each background pixel are fitted. Last, RAPID simulates the reflectance image using the texture matrices filled with the weight coefficients. By using real images from the Tianfeng Mountain of Yunnan Province and Dayekou of Gansu Province, the improvement of image quality by considering heterogeneity on image simulation has been evaluated. The Tianfeng Mountain scene represents a sparse Yunnan pine (Pinus yunnanensi) forest with heterogeneous background (bare soil, shrub, grass, or dead wood) in the stand, with a hyperspectral image used as input. The Dayekou scene shows the Qinghai spruce (Picea carassifolia) forest segmented by a large grass patch, with a Quickbird image used as input.Results show the following: (1) the two weight coefficients can be solved directly from real images when the end member of bare soil and dense vegetation are chosen properly. (2) If two heterogeneous weight coefficients are assigned to each surface pixel, high coincidence exists between the synthetic spectrum and the spectral curve of the real image (R2 is better than 0.98, RMSE=0.016). (3) The simulated image qualities are remarkably improved in the Tianfeng Mountain and Dayekou scenes (R2 increased by 0.096 and 0.041, respectively, and RMSE decreased by 0.015 and 0.01, respectively). (4) Near infrared (NIR) band images can also be predicted from three-band RGB images. When only RGB images are used as input, a similar texture is reproduced, but a certain deviation exists in the NIR reflectance values (0.006—0.027).The method proposed in this study can simulate more precise submeter high resolution satellite images, which can provide high-quality samples for deep learning and improved training data for quantitative inversion.关键词：remote sensing;surface texture;high resolution satellite image;3D radiative transfer;image simulation;end-member spectrum;training sample- 58
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发布时间：2024-07-19 -
Multisensor remote sensing registration method and system based on dense feature of orientated phase AI导读
“在遥感影像配准领域，研究者提出了一种基于结构相似性的快速精确配准方法，通过构建方向相位稠密特征DFOP，有效提升了匹配正确率。”
摘要：To solve the problem of registration difficulty caused by considerable geometric distortion and gray differences between multisensor remote sensing images, this study proposes a fast and accurate registration method based on structural similarity between images. In this method, the phase congruency model with illumination and contrast invariances is introduced to construct robust structural feature descriptors of images. First, the intensity and orientation of phase congruency are used to build a pixel-wise three-dimensional structural feature representation named Dense Feature of Orientated Phase (DFOP), which can effectively resist the grayscale difference between multisensor images by capturing geometric structures of images. Next, the DFOP feature descriptor is transformed into the frequency domain, and the single-step DFT approach is used to achieve fast matching with subpixel accuracy by employing a template matching scheme. In addition, a fast and robust automatic multisensor remote sensing image registration system is developed on the basis of the proposed DFOP. Finally, the proposed method and registration system is validated using multiple pairs of multisensor remote sensing images (including optical, LIDAR, and SAR) covering different scenes. Results show that the proposed DFOP achieves higher correct matching rate, and the developed registration system outperforms the registration module of ENVI and ERDAS in registration accuracy. Our system is available at https://github.com/yeyuanxin110/Remote-Sensing-Image-Registration-system.git关键词：multi-sensor remote sensing images;image registration;phase congruency;dense feature of orientated phase;images registration system- 755
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发布时间：2024-07-10 - “高分七号卫星（GF-7）实现全球1∶1万比例尺立体测图精度，通过激光高程点提升立体影像高程精度，为全球地理信息资源建设提供重要支撑。”
摘要：The GF-7 satellite is the world’s first Earth observation satellite synchronously equipped with an optical stereo camera and an operational laser altimeter, which can simultaneously obtain submeter resolution dual linear-array stereo images and sparse ground Laser Altimetry Points (LAPs). LAPs can be used for improving the elevation accuracy of stereo images to ensure that the GF-7 satellite can be applied to the global 1:10,000-scale stereo mapping. On the basis of the error propagation principle of the working processes of satellite cameras and laser altimeter, the basic principles of improving the elevation accuracy of stereo images by utilizing LAPs was first analyzed in this study. Then, an integrated processing method of GF-7 satellite stereo images and LAPs, including the construction of precise measurement method of LAPs on stereo images and the combined block adjustment model of LAPs and stereo images, was designed. Finally, the elevation accuracy of the stereo images was effectively improved. A total of 70 stereo images and 463 LAPs of the GF-7 satellite in the northern region of Hebei Province, China, were selected to conduct integrated processing experiments. Results show that the vertical Root Mean Square Error (RMSE) of stereo images in the flat, hilly, mountainous, high-mountainous, and entire regions was reduced from the original 3.0, 4.68, 2.86, 2.48, and 3.19 m to 0.35, 0.66, 0.74, 0.91, and 0.68 m, respectively, and the horizontal RMSE of stereo images was 4.99, 3.52, 4.42, 5.99, and 4.82 m, respectively. These results reveal that the horizontal and vertical accuracy of the GF-7 stereo images satisfied the accuracy requirements of China's 1∶10,000-scale mapping. At present, the integrated processing software system of GF-7 satellite stereo images and LAPs constructed by the method described in this study has achieved business application, which is vital for the future construction of global 1∶10000-scale geographical information resources.关键词：remote sensing;GF-7 satellite;stereo images;Laser altimetry point;Integrated processing;1∶10000-scale mapping- 1153
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发布时间：2024-07-10 - “在遥感图像超分辨率重建领域，专家提出了一种基于自注意力的超时相遥感图像超分辨率重建模型，充分利用超时相数据的时空信息，显著提升了重建效果，为该领域研究提供了新方向。”
摘要：Video satellite hypertemporal data have the characteristics of high temporal resolution, while the single-frame super-resolution reconstruction algorithm can only use the information of the image frame itself, and the reconstruction effect is limited. Therefore, how to utilize fully and effectively the rich spatiotemporal information in hypertemporal data in the super-resolution reconstruction of video satellite images is an issue of interest.Aiming at the characteristics of hypertemporal data, this study proposes a self-attention-based super-resolution reconstruction model of hypertemporal remote sensing images. The model can mine high-frequency information from low-resolution images through an end-to-end network. High-resolution images are recovered from multiple frames of low-resolution images. First, the hypertemporal sequence frames are divided into multiple time groups according to the frame rate, and the spatial and temporal information under different time groups are extracted by using the characteristics of 3D convolution to model space and time simultaneously. It pays attention to the calculation range and completes high dynamic mapping, extracts rich spatial detail information while realizing hypertemporal sequence frame modeling, and finally fuses the features of multiple time groups and completes the reconstruction through subpixel convolution to improve the resolution. The advantage of the proposed algorithm is that the multitime group feature fusion method can extract the spatiotemporal information of sequence frames in multiple time dimensions and fully mine the rich spatiotemporal-related information in the hypertemporal data; the improved self-attention block can be used without registration. It can complete the modeling of sequence frames and improve the extraction ability of detailed spatial information.Experiments on the GF-4 dataset show that the subjective visual effect and objective evaluation index of the algorithm are better than those of the comparison algorithm. When the GF-4 dataset is reconstructed twice, the PSNR value is improved by more than 2.49 dB compared with the bicubic interpolation algorithm, and it still has a strong reconstruction performance when the reconstruction is four times, which is a huge improvement compared with the bicubic interpolation algorithm. Experimental results show that the method has good super-resolution reconstruction effect, which is beneficial to the application of hypertemporal data in various fields.The self-attention-based super-resolution model of hypertemporal remote sensing images proposed in this study fully extracts the spatiotemporal information in hypertemporal data by dividing multiple time groups and calculating the attention features in each time group. The combination of multitemporal group feature fusion and self-attention enables the modeling of overphase sequence frames while ensuring the ability to extract detailed information. Comparative experiments on the GF-4 dataset show that the algorithm in this study is superior to the compared algorithm in terms of objective evaluation indicators and subjective visual effects, verifying the effectiveness and advancement of the algorithm in super-resolution reconstruction of hypertemporal data and the algorithm’s improved reconstruction performance. However, the proposed algorithm must be optimized in terms of calculation time. In a follow-up research, the algorithm structure will be optimized (e.g., changing the residual structure of the network) to reduce the calculation time while ensuring accuracy.关键词：remote sensing;hyper-temporal data;super-resolution reconstruction;deep learning;fusion feature of multiple time groups;wide self-attention;GF-4- 783
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发布时间：2024-07-10 - “在遥感领域，研究人员提出了一种新的对称网络结构，通过特征空间变换，有效提高了光学影像和SAR影像变化检测的精度与效率。”
摘要：Compared with homogeneous image change detection (homo-CD), Change Detection (CD) of optical images and SAR images offers the advantage of utilizing complementary information from different types of data. This advantage has made it a research hotspot in the field of remote sensing image processing and holds promise for emergency disaster monitoring. However, the differences in imaging mechanisms between optical and SAR images prevent direct comparison of bitemporal images for CD. Existing methods for optical image and SAR image CD still face certain challenges. Methods aiming to unify the feature space of optical and SAR images often suffer from issues, such as low mapping precision and efficiency. In this study, we propose a Symmetric Change Detection Network (SCDN) that addresses the difference in imaging features between optical and SAR images by mapping them to a common feature space for comparison. The SCDN is initialized and optimized using similarity measurement, and it subsequently maps the optical and SAR images to a similar feature space for change information extraction.The proposed method consists of several steps. First, the similarity between multiple sets of features generated by the symmetrical network is measured, and the weights corresponding to the most similar features are used to initialize the network. This initialization guides the network to map optical and SAR image features. Subsequently, the SCDN maps the optical images and SAR images into the same feature space using similarity optimal learning, enabling direct comparison. Finally, change types are determined by clustering the multitemporal change vectors.To validate the proposed method, we conduct experiments using three sets of images, namely, Google Earth, Landsat-8, and Sentinel-1 images. Comparative analysis with five state-of-the-art methods reveals that the proposed method achieves an increase of at least 4.02% in the kappa coefficient while reducing the running time by at least 30.79%.In this study, we introduce SCDN, a CD method for optical and SAR images. Experimental results demonstrate its effectiveness in achieving relatively high precision and efficiency compared with existing methods.关键词：remote sensing;optical image;SAR image;change detection;symmetric network;feature extraction;spatial mapping;similarity measure;change type- 141
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发布时间：2024-07-19 - “在遥感领域，一项新研究提出了一种快速重建三维场景的方法，利用全局式仿射模型，显著提升了重建速度、精度和完整性。”
摘要：Three-dimensional (3D) scene reconstruction based on multiview satellite remote sensing images is a challenging task in the field of remote sensing. Most of the existing methods either have to perform bundle adjustment repeatedly or must calculate several parameters in the rational polynomial camera model, resulting in a relatively long reconstruction time. To solve the abovementioned problems, this study considers that the local small-sized patches in large-sized satellites could be approximately modeled by the affine imaging model and proposes a fast 3D reconstruction method of satellite images based on global affine model estimation.First, the input multiview satellite images are cropped into a set of small-sized patches with overlapping regions. For each pair of patches that have a sufficient number of point correspondences from two views, the corresponding 3D affine point cloud is calculated. Second, on the basis of the obtained local point clouds, a global affine camera motion estimation algorithm is presented for calculating the affine motion matrices of the cameras corresponding to all the patches in a unified coordinate system. Finally, the obtained affine camera motion matrices and a few ground control points are utilized to recover the Euclidean scene structure.3D reconstruction is conducted for the same group of remote sensing images and all remote sensing images to verify the effectiveness of the method. The proposed solution is compared with three state-of-the-art methods (i.e., COLMAP, S2P, and JHUAPL). Experimental results on two public datasets (i.e., MVS3DM and DFC2019) show that the proposed method outperforms the three comparison algorithms in most cases with respect to speed, accuracy, and completeness. To verify further the reconstruction accuracy of the method, this study selects 15 complex scene areas from two public datasets, including complex scenes with built-up areas, shadow areas, and complex object areas. For 15 complex scenarios, the proposed method outperforms the three methods with respect to accuracy and completeness in most cases.This study proposes a fast reconstruction method of satellite images based on the global affine model estimation algorithm. The method assumes that the local image tile in large-scale satellite remote sensing images conforms to the affine imaging model and introduces a global affine motion matrix estimation algorithm based on local point clouds. Consequently, the proposed solution can calculate the global affine motion matrix of each local image tile through only one bundle adjustment, considerably reducing the reconstruction running time. Experimental results show that the proposed method can quickly solve the global affine matrix corresponding to each image tile and realize fast 3D reconstruction of remote sensing images.关键词：3D reconstruction;satellite images;affine imaging model;Euclidean structure update;global affine matrix- 890
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发布时间：2024-07-19 - “最新研究利用HY-2卫星数据，提出主被动微波遥感联合观测热带气旋海面高风速和海面气压的方法。通过校正雷达高度计观测中的降雨影响，结合气压差与风速差的比例关系，计算中心气压。该方法在高风速和海面气压观测方面表现优异，为热带气旋监测提供了新的解决方案。”
摘要：Tropical cyclones are accompanied by different degrees of rainfall, which attenuates the remote sensing parameters obtained by the active microwave remote sensor to varying degrees, resulting in the underestimate of wind speed, and the wind speed above 30 m/s cannot be observed effectively.Based on the comprehensive consideration of the sensitivity of HY-2 satellite radar altimeter and calibration microwave radiometer to wind speed observation, this paper proposes a new method for the joint observation of tropical cyclone wind speed and sea level pressure based on HY-2 satellite active and passive microwave remote sensor, that is, the influence of rainfall on radar altimeter observation during typhoon is compensated by using the brightness temperature of calibration radiometer T18 channel, to improve the observation ability of high wind speed; Based on the effective observation of typhoon high wind speed and the relationship between typhoon central pressure difference and wind speed difference, an inversion method of sea surface pressure is proposed.The method can realize high-precision observation of wind speed above 50 m/s. The absolute error between the method and SFMR airborne observation data is within 2 m/s, and the RMSE is 1.0 m/s. The absolute errors of the proposed sea level pressure observation method compared with SFMR airborne observation data and CMA, JTWC and NHC are all within 10 hPa, and RMSE is 4.6 hPa, which proves the reliability of the method. At the same time, the method in this paper also has the ability to observe the sea level pressure under the condition of medium and low wind speed.Based on HY-2 satellite data, a method for active and passive microwave remote sensing to jointly observe tropical cyclone sea surface wind speed and pressure is presented. This method is suitable for satellite radar altimeter and correction microwave radiometer data, which can make up for the shortage of active microwave remote sensing payload observation ability under the condition of tropical cyclone rainfall, and has the ability to simultaneously obtain the information of tropical cyclone wind speed and sea level pressure. The deficiency lies in that, due to the time and space limitations of HY-2 satellite observation data in the study, there are few comparison data that meet the requirements of verification. Subsequently, HY-2 satellite observation data for a longer period of time and global tropical cyclone data will be accumulated for more comprehensive data analysis and evaluation. In terms of data evaluation, it is proposed to apply the method in this paper to the Jason series of satellite observation to obtain the satellite observation data of tropical cyclone in a long time series, and realize more observation of typhoon or hurricane wind speed, so as to give more objective statistical analysis results. At the same time, it can also further test the applicability of the method in this paper on similar satellites. In terms of sea level pressure observation, the method in this paper is proposed to be further improved and evaluated with NDBC buoy data in order to realize sea level pressure observation under non-cyclone conditions and expand radar altimeter.关键词：remote sensing;HY-2 satellite;tropical cyclone;wind speed;sea level pressure;inversion method- 40
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发布时间：2024-07-10 - “在遥感目标检测领域，专家提出了一种基于稠密连接递归特征金字塔的算法，通过改进特征融合模式、加入多感受野机制、引入稠密连接结构，实现了对遥感目标的高精度检测。”
摘要：In recent years, the multiscale utilization of input sample features has gradually become a research hotspot in the field of target detection. However, remote sensing target detection suffers from some problems, such as small target size, easy confusion with similar objects, and extensive background interference. Therefore, a remote sensing target detection algorithm based on dense connection recursive feature pyramids is proposed. First, the feature fusion mode is improved to use the features of remote sensing images fully. The traditional feature fusion method is only pixel-by-pixel addition, which is simple and rough to calculate and cannot effectively screen features. Therefore, canonical correlation analysis is used to replace the simple pixel-by-pixel additive fusion mode to enhance the effectiveness of feature fusion. Moreover, this method does not add any new parameters. Second, the multireceptive field (MRF) mechanism was added to enhance the feature extraction of small-scale targets, and the features of different receptive fields were extracted and fused by dilated convolution of different sizes to enhance network perception. Given the increase in receptive field types, the richness of features that can be extracted is greatly enhanced, which is conducive to the improved transmission of effective information. In addition, our proposed MRF module is a multibranch convolution module, which is intended to mimic the human visual receptive field mechanism. Then, the feature recurrence form is improved to solve the generalization problem of a multiscale remote sensing target, and the dense connection structure is introduced to enhance the feature fusion density. A dense connection improves network performance because the feature level increases, and the feature richness is enhanced accordingly. Compared with the original recursive feature pyramid, the utilization of the backbone network is remarkably improved. The backbone network and the feature information of high and low layers are fully utilized. Finally,Based on our proposed methods above, this study changes the way of feature recursion and designs a dense connection structure of the recursive feature pyramid. That is, it adds dense connections between multiscale features and each layer of the backbone network to improve the efficiency of feature extraction and utilization. In summary, the network design in this study includes a top-down fusion subnetwork, bottom-up path enhancement subnetwork, and feature recursive fusion subnetwork. Experimental results show that the average accuracy of the proposed pyramid model can be improved by 9.9% on the general dataset MS-COCO2017. On the remote sensing dataset NWPU VHR, the average accuracy of the proposed algorithm can be improved by 1.1%. On the remote sensing dataset DIOR, the average accuracy of the proposed algorithm can be increased by 2.2%, which is higher than other feature pyramid models and detection algorithms. On the large-scale remote sensing dataset DOTA, the average accuracy of the proposed algorithm can be increased by 1.8%. Experimental results show that the proposed method can outperform other feature pyramid models and detection algorithms. It achieves not only high precision detection of remote sensing targets but also has good performance on the benchmark dataset COCO. Therefore, the proposed method is advanced.关键词：remote sensing image;object detection;feature pyramid network;feature recursive;densely connected- 104
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发布时间：2024-07-10 - “在矿区形变监测领域，研究人员引入坐标—时间函数CT，构建了CT-PIM模型，显著提升了形变预测精度，为矿区安全和生态保护提供参考。”
摘要：Long-term monitoring and the subsequential prediction of deformation for salt mining areas is essential to the safety prevention and environmental protection of mining areas. The combination of the interferometric synthetic aperture radar (InSAR) technique with the Probability Integral Method (PIM) has proven to be powerful in predicting the deformation of mining areas. However, single multitemporal InSAR (MT-InSAR) is limited because it can only obtain the deformation sequences during SAR acquisition dates, and the subsequent future displacement beyond the span of the SAR observations cannot be acquired. In addition, traditional mathematical empirical models are mostly used in the time-series modeling of mining areas, ignoring the underground mining mechanisms, which seriously affect the accuracy of the observations. Inaccurate InSAR deformation monitoring results transmit errors to forward predicted subsidence, which may induce considerable errors.In this study, the Coordinate-Time (CT) function is introduced into time-series InSAR deformation modeling, and a CT function prediction model (CT-PIM), which can well describe the dynamic evolution disciplines of the underground mining subsidence in InSAR deformation modeling, is constructed to replace the traditional mathematical empirical models. The unknown CT-PIM parameters can be estimated directly via InSAR time-series phase observations, and the constructed CT-PIM is directly used in the deformation prediction of the mining area, which can avoid the error propagation from the InSAR-generated deformations and improve deformation prediction accuracy.The new approach is tested by simulation and real data experiments. The simulation results show that the root mean square error between the time-series deformation prediction of the model and the simulated true value is estimated to be ±4.6 mm, which implies that the proposed method is of promising accuracy. The real experiment was conducted using a total of 35 Sentinel-1A SAR images covering the salt mining area in Huaian City, and the deformation prediction results of the study area from March 30, 2019 to July 28, 2019 were obtained. Results show that the maximum settlement of deformation prediction in the study area is 152 mm. The modeling accuracy showed an improvement of 38.2% compared with traditional SBAS-InSAR, and the deformation prediction accuracy exhibited an improvement of 39.1% compared with the traditional static PIM prediction method.CT-PIM was used as a substitute for traditional MT-InSAR pure empirical models and was applied for predicting the dynamic deformation over the salt mining area, which provides a more robust tool for the forecasting of mining-induced hazards. The above results show that CT-PIM can describe the temporal dynamic characteristics of the mining-induced subsidence more realistically, which can avoid the secondary error propagation, and can serve as a reference for safety management and ensuring environment protection.关键词：remote sensing;InSAR;mine;Coordinate-Time Function;land subsidence;deformation prediction- 779
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发布时间：2024-07-19 - “在森林生物量估算领域，研究者通过对比分析ICESat-2和GEDI激光雷达数据，建立了森林地上生物量估算模型，为森林碳储量监测提供新方法。”
摘要：Forest Aboveground Biomass (AGB) plays an important role in the study of carbon cycle and global change. Spaceborne LiDAR can provide information about forest vertical structures that is advantageous in AGB estimation, among which ICESat-2 and GEDI are the latest available spaceborne data. In this study, we investigated the applicability of ICESat-2 and GEDI for forest AGB estimation at regional scale, and analyzed the effect of data fusion of ICESat-2 and GEDI to find an optimal method to map the spatial distribution of forest AGB accurately in Zhejiang Province.First, we built footprint-level forest AGB estimation models by stepwise regression in the typical study area of Gutian Mountain based on ICEsat-2 and GEDI spaceborne LiDAR data, respectively. Then, combined with MODIS data and ASTER GDEM terrain information, forest AGB estimation models with spatial continuity at 250m pixel scale for different forest types were constructed by Random Forest algorithm throughout Zhejiang Province. Estimation results were validated using 40 forest AGB field plots. Finally, by comparing validation results of AGB estimation based on ICESat-2 or GEDI solely and the combination of the two spaceborne LiDAR data, the optimal method of forest AGB scaling was selected and the spatial distribution of forest AGB of the year 2020 was mapped in Zhejiang Province.The accuracy of segment-level forest AGB estimation based on ICESat-2 (R2=0.7057, RMSE=0.3571 ln(t/ha)) outmatches footprint-level forest AGB estimation based on GEDI (R2=0.5186, RMSE=0.2805 ln(t/ha)) in the typical study area of Gutian Mountain. Validation accuracy of forest AGB estimation result based on ICEsat-2 (R2=0.59, RMSE=31.2525 t/ha) is superior to GEDI (R2=0.4113, RMSE=39.2652 t/ha) in Zhejiang Province. The difference of forest AGB estimation performance between ICESat-2 and GEDI is mainly related to elevation, validation accuracy based on GEDI is higher when filtering footprints that are acquired in high elevation areas with an elevation threshold of 600m (R2=0.5387, RMSE=25.4017 t/ha). Combining ICESat-2 and GEDI data (elevation ≤ 600 m) to build scaling model is the optimal method to estimate forest AGB in Zhejiang Province (R2=0.678, RMSE=27.3592 t/ha).We have obtained a reliable estimation of forest AGB in Zhejiang Province based on ICESat-2 and GEDI data, which is a significant practice of regional scale forest AGB estimation. Our study can provide an effective method for forest carbon dynamic and sequestration potential monitoring using spaceborne LiDAR data.关键词：remote sensing;forest aboveground biomass;ICESat-2;GEDI;stepwise regression;Random Forest;scaling extrapolation;Zhejiang Province- 1765
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发布时间：2024-07-19
Models and Methods
- “嫦娥六号着陆点精确定位，为工程任务实施和科学研究提供重要支撑。”
摘要：China’s Chang’e-6 (CE-6), the world’s first lunar farside sample-return mission, successfully landed on the preselected landing site in the Apollo basin inside the South Pole-Aitken basin on June 2, 2024. The high-precision localization of the lander is of considerable importance for supporting engineering operations and scientific studies of the landing site and the returned samples. This study presents the localization techniques and results of the CE-6 lander. Using the Digital Orthophoto Maps (DOMs) produced from images taken by Chang’e-2 (CE-2) and the Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) as base maps, the CE-6 lander has been localized through a visual localization method based on image feature matching between descent images acquired by the lander and the base maps. A new descent image simulation technique has been developed based on orbital base maps and terrain data before landing to automate image matching between descent images and orbital base maps. After landing, descent images are downlinked and lander localization is performed using the developed visual localization method. The location of the CE-6 lander location is determined to be (153.9780°W, 41.6252°S) on the CE-2 base map and (153.9855°W, 41.6384°S) on an LROC NAC base map (Image ID: M166854798LE). The average location of the lander from five LROC NAC base maps is (153.9856°W, 41.6383°S). The location of the high-precision CE-6 lander has been directly supported by engineering operations, and it will be valuable for comprehensive studies on the landing site by using remote sensing data and studies on the provenance of the samples.关键词：remote sensing;Chang’e-6;lander localization;descent camera image;image simulation;image matching- 549
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发布时间：2024-07-19
Short Communications
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