最新刊期
卷 23 ， 期 1 ， 2019
- 摘要：Academician Li Xiaowen devoted his time in fundamental research in remote sensing. He was the pioneer in the field of geometric–optical modeling of vegetation canopy and had a great reputation in international remote sensing community. The Li–Strahler geometric–optic model was selected as the SPIE milestone series. Li Xiaowen, who was the chief scientist, led the scientific team to obtain outstanding achievements in bidirectional reflectance distribution modeling, directional thermal emission modeling, spatial- and temporal-scale effects of remote sensing information, quantitative remote sensing inversion, and comprehensive experiments. In this paper, Li Xiaowen’s biography was briefly introduced, and his academic contributions in quantitative remote sensing theory and methodology were summarized.关键词：geometric-optical model;thermal radiation directionality;quantitative remote sensing inversion;scale effect;remote sensing comprehensive experiment
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发布时间：2021-06-07
Review
- 摘要：Validation of satellite-derived albedo products is an essential precursor to scientific research and subsequent environmental monitoring. Unlike the simple comparison between two datasets, validation involves determining the ground truth at pixel scale that exists independently. The reliability of validation results depends on the accurate treatment of ground-based measurements, upscaling, and assessment methods. This study analyzed the current state and development trends of validation technique specifically for remote sensing of albedo products. Ground-based measurements are the primary source of truth value at pixel scale to validate remote sensing products. The balance between the comprehensiveness and strictness of a validation can be achieved by selecting either the extensively distributed but sparse networks or small-scale but dense networks depending on each specific goal. However, ground measurements cannot provide sufficient information for the acquisition of truth value at pixel scale due to their limited spatial scales. Moreover, this finding was especially true for heterogeneous surfaces. Therefore, an upscaling technique should be explored to minimize errors due to the large spatial-scale difference between ground measurements and satellite product pixels. High-resolution imageries can provide spatial distribution characteristics of surface albedo within a coarse pixel, and these imageries can address the severity of the upscaling problem. Apart from these factors, the quality index, the effect of solar zenith angle, and the choice of albedo can all affect the quality of validation. The sparse networks can ensure the comprehensiveness of the validation but ignore the scale problems embodied in the validation. The dense networks can address the scale problem but cannot support the validation on a global scale. With regard to upscaling issues, the combination of ground measurements and high-resolution imageries can provide ideal upscaling results. However, differences remained among different methods. The traditional multi-scale validation strategy suffered from critical uncertainties caused by high-resolution albedo maps’errors, geometric mismatches, and calibration model errors. Recently, the upscaling method based on the idea of trend surface has attracted the attention of scholars whose interest is the validation field. This method compensates the errors of high-resolution maps and calibration model, thus improving the quality of upscaling results. The quality index of satellite albedo products should be considered in validation. Otherwise, wrong results may be obtained. Moreover, ground measurements with solar zenith angle exceeding 75° should be discarded. Great achievements have been obtained with regard to ground measurements, upscaling, and assessing methods in the past few years. Nevertheless, the accuracy of validation results remained hindered by several problems, which had not been seriously considered. This study provided an overview of existing validation activity, including ground-based data acquisition and processing, upscaling method for calculating the reference at pixel scale, and assessment method. Furthermore, their key challenges were also presented.关键词：validation;heterogeneous surfaces;scale effect;albedo
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发布时间：2021-06-07 - 摘要：Surface net radiation is a key variable of energy and water exchange processes in land–atmosphere interactions. Accurate estimation of spatial–time changes on land-surface net radiation flux is a critical study in global warming for climate change research. This study aims to summarize the three main methods for estimating net radiation at present, to analyze the advantages and disadvantages of the different methods used for surface net radiation, and to propose an effective method using data assimilation to improve net radiation at present and in the future. This paper summarizes the main methods, including observation, simulation, and assimilation, used at present for surface net radiation. Observations include ground-based measurement and remote-sensing estimation. Simulation is mainly concerned with the estimation of land-surface process models. The advantages and disadvantages of observation and simulation are analyzed, and the current status and progress of surface net radiation observation and simulation are reviewed in this study. Moreover, a method of data assimilation is proposed to compensate for the shortcomings of observation and simulation. The advantages and disadvantages of popular assimilation algorithms, such as sequential (Kalman filter algorithm and its derivative, particle filter algorithm) and variational (four dimensional variational assimilation algorithm or 4D–Var) assimilation algorithms, are introduced and analyzed in this study. Furthermore, the research progress and existing problems of assimilation algorithms in surface net radiation flux estimation are summarized. At present, progress has been made in estimating the surface net radiation using data assimilation combined with multisource observations. However, problems exist in these methods. A model is calibrated by the observation data of different sources to obtain the continuous and consistent high-precision surface net radiation prediction value in time and space in the process of data assimilation using different assimilation algorithms. The adaptability of different land-surface process models varies in different research areas based on the simulation results of the model, and the precision and accuracy of the different models in describing the surface water thermal process are significant. Based on the assimilation of remote sensing data, the study of assimilating an optical remote sensing data product has been successful in estimating the net radiation of the surface.关键词：surface net radiation flux;observation;simulation;data assimilation;algorithm of assimilation
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发布时间：2021-06-07 -
摘要：The emerging technique of remotely sensed sun-induced fluorescence (SIF) offers great advantages for estimating the gross primary photosynthetic (GPP) and investigating carbon cycles at regional and global scales. This novel satellite product is a state-of-the-art and booming avenue in recent years. Particularly, the flourishing progressions in retrieval techniques, vegetation monitoring, and applications in carbon cycle model have been accelerated to implement a satellite-based inversion at a global scale since 2011. During photosynthesis, part of solar radiation absorbed by chlorophyll is re-emitted at long wavelengths (fluorescence). Chlorophyll fluorescence is an electromagnetic emission in the 650–800 nm range originating at the core of the photosynthetic machinery. It been used in leaf-scale studies of photosynthesis in laboratory conditions for several decades. By using new, high-resolution spectrometers, chlorophyll fluorescence can be readily retrieved from satellite platforms. This scheme can be used to quantify the photosynthetic activity and efficiency globally. Satellite observations of chlorophyll fluorescence are important to reduce the uncertainties in research of global carbon cycle and climate change. In this review, we introduced the recent development in the remote sensing of SIF. First, recent instrumental and methodological developments in the field of spaceborne spectroscopy have rendered the measurement of SIF from space possible, which can alleviate the current limitations for the monitoring of terrestrial photosynthesis. Since 2011, the global data of SIF have been retrieved from a series of spaceborne instruments providing high-resolution spectra, such as the GOSAT’s Fourier transform spectrometer, ENVISAT/SCIAMACHY, MetOp-A/GOME-2, and OCO-2. The spatial coverage and resolution, wavelength, acquisition time, and amount of data available for analysis depend on the instrument from which they are derived. As a complement to reflectance-based vegetation indices, SIF offers new possibilities to monitor photosynthesis and GPP of terrestrial ecosystem from space. The potential of SIF, which is an indicator of large-scale GPP, has been demonstrated in a relatively short life time of global SIF data. Recent studies have shown that satellite observations of SIF are an excellent proxy for GPP at canopy and ecosystem scales. Meanwhile, spaceborne SIF data have also been used to monitor large-scale vegetation status in drought conditions, thereby suggesting that SIF provides unique, perhaps most direct, information from space for early warning and accurate monitoring of emerging drought. The potential of SIF as a constraint on regional and global carbon cycle variations has also been demonstrated together with the XCO2 data from GOSAT and OCO-2. Despite this experimental evidence of a direct and linear correlation between spatio-temporal aggregates of remotely sensed SIF data and large-scale GPP, the relationship between instantaneous photosynthesis and SIF is relatively complicated. Further study is necessary to investigate how the remotely sensed SIF signal can be used for plant photosynthesis monitoring, how we can interpret the SIF signal at various spatial and temporal scales, and how we link the active PAM measurements with canopy SIF at the seasonal scale. At the end of this review, we proposed a number of areas where further research can be conducted to better understand the mechanisms that govern the seasonality of canopy- and leaf-level SIF signal and its relation with photosynthesis. Several prospective areas for future work include improving the accuracy of retrievals with additional data, characterizing the mechanistic relationship between SIF and GPP across scales, measurements of near-surface continuous SIF along with eddy covariance flux system, data assimilation of SIF into land surface models, and development of new index for stress detection from SIF.关键词：sun-induced chlorophyll fluorescence;GPP modeling;global carbon cycle;phenology monitoring;stress monitoring- 1114
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发布时间：2021-06-07 -
摘要：Surface albedo is one of the key parameters in the investigation of surface energy balance. Accurate inversion of surface albedo is important for the evaluation on climate change. For the multi-angle reflectance data of an airborne Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS) in Genhe Region, Inner Mongolia, the Bidirectional Reflectance Distribution Function (BRDF) archetype-based algorithm was initially applied in forest experimental area. First, we extracted four BRDF archetypes based on the hotspot-corrected linear kernel-driven BRDF models, i.e., RossThickChen-LiSparseReciprocal and anisotropic flat index, in the experimental region of Genhe. Then, we applied these archetypes as a priori knowledge to the albedo inversion of WIDAS airborne data in the forest of the region. Finally, the albedo of WIDAS and the data observed by surface flux tower were used to verify Landsat albedo. In this study, we analyzed the robustness of the BRDF archetype-based algorithm in retrieving small-angle observations in forest experimental area. The results are as follows. (1) The surface albedo retrieved by the BRDF archetype-based algorithm has high accuracy and stability, and the total Root Mean Square Error (RMSE) of Landsat albedo was approximately 0.02 and deviation was 0.0057. (2) Given the available observation range of WIDAS in the experimental area of Genhe in 2016 was 25°, the BRDF archetype-based algorithm showed robust inversion capability in small observation angles. Therefore, when the multi-angle observation range was narrow, the albedo of airborne WIDAS retrieved by the BRDF archetype-based algorithm can be in good agreement with that of the Landsat, providing a means to effectively address the problem and validate the satellite albedo.关键词：Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS);kernel-driven BRDF model;AFX;BRDF archetype;Landsat;surface albedo- 599
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发布时间：2021-06-07 - 摘要：Wildfire is a natural agent of many ecosystems since fire can affect nutrient cycles, vegetation succession patterns, and insect plague resistance. However, wildfire also has a wide range of negative impacts on ecosystems, such as soil erosion and degradation, destruction of vegetation water conservation function, emissions of atmospheric greenhouse gases, and human life and welfare. The three major forces that are essential for understanding forest fire risk and its behavior are as follows: weather, fuel, and topography. In this context, fuel moisture content (FMC), which is the proportion of water content over dry mass, is one of the key factors used for the risk assessment of wildfire because it affects fire ignition and spreading. However, traditional field measurement of the variable is time consuming, and extending to large-scale and dynamic application is impossible. Thus, a near real-time, multi-temporal and multi-spatial remotely sensed data can address the solution. In this work, the FMC of grassland and forest for six study areas distributed in the Western China were retrieved using the PROSAIL and PROGeoSAIL radiative transfer models from Landsat-5 TM and Landsat-8 OLI data. For accurate and robust retrieval of FMC, the ill-posed inversion problem, the weak sensitivity characteristic of FMC, and the way in modeling the spectra of two-layered forest canopy should be addressed. In this study, we focused on alleviating the ill-posed inverse problem based on the ecological rule to obtain the improvement of the FMC retrieval. Previous studies generally treated the free parameters independent while ignoring that these parameters were naturally correlated. The correlations that naturally existed between the model parameters were introduced into their prior joint probability distribution of the requried free parameters. This treatment can reduce the probabilities of unrealistic combinations that may confuse the retrieval process and therefore increase the accuracy level of the retrieved FMC. FMC is calculated from the ratio of the model input parameters, namely, equivalent water thickness (EWT) and dry matter content (DMC). Both these two variables have the sensitivity in the near infrared (NIR) and shortwave infrared (SWIR) bands. However, the effect of DMC in NIR and SWIR is often confused by the EWT, which renders the accurate estimation of DMC (or FMC) slightly challenging. For the accurate retrieval of FMC, all available bands from Landsat-5 TM and Landsat-8 OLI data were used for obtaining additional information from these remotely sensed data. Regarding to the forest with two-layered canopy (lower grass and upper tree canopies), this study coupled two radiative transfer models, namely, PROSAIL and PROGEOSAIL to characterized its spectra. First, the spectra of the lower grass canopy were simulated via the PROSAIL model. Then, the soil spectra required in the PROGeoSAIL model were replaced using the simulated spectra of the low grass canopy layer. These coupled models allowed to better resemble the two-layered canopy configuration in the study area. Result show that the accuracy of the retrieved forest FMC (R2=0.71, RMSE=30.82%) was better than the grassland FMC (R2 = 0.64, RMSE = 47.57%) with overall accuracy of R2 = 0.64, RMSE = 44.86%. The multi-temporal FMC maps were generated to further demonstrate the performance of the retrieved FMC in assessing the wildfire risk in Jinhe Village of Yunnan Province where a forest fire occurred in March 02, 2011. Result further show that FMC noticeably decreased during the fire, thereby implying the potential usage of retrieved FMC in the early warning of the wildfire risk.关键词：fuel moisture content;radiative transfer model;weak sensitivity of FMC;two-layered forest canopy;wstern China;wildfire
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发布时间：2021-06-07
Fundamental Research
- 摘要：Interferogram filtering is an important procedure in multi-temporal INSAR analysis and application in monitoring regional surface deformation. Researchers have introduced a series of filtering methods, such as Empirical Mode Decomposition (EMD) filter, based on time-frequency analysis to determine the characteristics of the interferometric phase for non-stationary signals. Given the differences in time-frequency distribution between signal and noise of interferogram, InSAR interference phase filtering method based on EMD is proposed and effectively applied in InSAR interferogram filtering with improved capability of phase noise filtering and detail preserving in edge area. However, in existing EMD filtering methods, some high-frequency modal components are eliminated as noise directly without objective assessment. The mode-mixing problem of EMD also influences the filtering effect. To address the problems of interferometry phase filtering in EMD, a newly improved InSAR interference phase filtering method based on EMD and noise-screening assessment is proposed. In the new algorithm, ensemble EMD (EEMD) is applied to obtain modal components of different time scales to the two-dimensional real and imaginary parts of the interferogram by fully utilizing the capability of EEMD in effectively reducing modal aliasing. Then, Kernel Entropy Component Analysis (KECA) algorithm is used for nonlinear analysis of signal noise identification and separation. Finally, interferogram is reconstructed with modal components after noise elimination. After the decomposition and reconstruction of mixed signals, the noise in the interferogram is effectively filtered out. The performance of the proposed filtering method is tested on simulated data and real SAR images by comparing the filtering effects of Goldstein filter, periodic-median filter, EMD, and EMD–PCA filter with the proposed EEMD–KECA filter. Speckle, variance, and edge-keeping indexes are used for quantitative evaluation. Unlike the classical InSAR interferogram filtering, the proposed method combined with EEMD–KECA filtering algorithm can effectively filter out the interference noise figure and has an advantage in maintaining the fringe edge details. In the proposed method, EEMD is used to decompose interferogram signal instead of EMD, and KECA is applied to evaluate the phase noise quantitatively. The proposed method can achieve good filtering results while preserving the advantages of strong edge detail maintenance and can avoid the incomplete and partly filtering of image information caused by modal aliasing. Experimental results show that the proposed method not only can obtain excellent filtering performance in the slowly changing region of fringe but also has excellent filtering effect and high phase fidelity in the dense fringe area and phase edge details. The proposed filtering method is suitable for interference fringes of different densities.关键词：EEMD algorithm;modal aliasing;KECA;noise separation;INSAR interferogram;filtering
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发布时间：2021-06-07 - 摘要：The echoes of full-waveform light detection and ranging (LiDAR) contain information on the targets such as distances and properties. To access such information, we demonstrate an echo decomposition method based on soft-thresholding Empirical Mode Decomposition (EMD-soft) filter, Levenberg–Marquardt (LM) optimization, and a method to estimate the initial parameters consisting of a variety of waveforms. This method decomposes raw full-waveform echoes into independent Gaussian pulses and derives their function expressions. Distances and properties of the targets can be extracted from the parameters of these Gaussian pulses. First, EMD-soft is used to filter the noise of raw echoes and estimate the amount of noise. Then, initial parameters for follow-up optimization are estimated through peak and inflection points of the filtered echoes by a given process. Lastly, after these initial parameters are input, LM optimization is applied to optimize the parameters, and function expressions of Gaussian pulses can be obtained through the parameters. Finally, information on the targets can be accurately extracted. Simulations and experiments are carried out to evaluate the performance of the proposed method. Simulated waveforms are generated by adding Gaussian white noise into a waveform consisting of several independent Gaussian pulses. Decomposition experiments of these simulated waveforms indicate that the decomposition error of this method is around 0.1 ns, which means 15 mm in ranging error. In actual experiments, a laboratory-built full-waveform LiDAR experimental system is utilized to generate and obtain echoes. Decomposition experiments of these real waveforms also show that the ranging error of this method is less than 0.1 m. Compared with two other Gaussian decomposition methods in decomposing the same echoes mentioned above, this method shows enhanced decomposition success rate and accuracy. The proposed method realizes high success rate and accuracy decomposition. It can provide reliable data for the subsequent analysis and will play an important role in many fields, such as remote sensing and mapping. Compared with other decomposition methods, the EMD-soft we used does not have a threshold of filter frequency, that is, it will be effective in any frequency, unlike some other filters that will make mistakes when close to their thresholds. In addition, EMD-soft does not need a given kernel function or parameter, which means it is a more generic method to deal with various LiDAR echoes. LM optimization is one of the most popular algorithms for optimizing LiDAR echoes, but requiring high-accuracy initial parameters is a big problem for the algorithm. Sometimes if the initial parameters do not have enough accuracy, the algorithm may converge to a local minimum instead of a global minimum and lead to a wrong fitting. Thus, in this method, a special process is realized in the section on evaluating initial parameters and enhancing the optimization effect from another way. Echo decomposition is the foundation of echo analysis. We will try to extract more properties of targets from the decomposed waveforms and build the functional relationship of these properties with the parameters of waveforms in future work.关键词：full-waveform LiDAR;echo decomposition;Empirical Mode Decomposition (EMD);LM (Levenberg–Marquardt) optimization
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发布时间：2021-06-07 - 摘要：The development and application of the multi-channel Synthetic Aperture Radar (SAR) have greatly enhanced the information acquisition and anti-jamming capabilities of the imaging radar and led to its development direction. Compared with the traditional SAR, the multi-channel SAR can extract more useful information from the phase of echo signals and has a higher degree of freedom. As one of several types of mature multi-channel techniques, SAR multi-channel cancellation technique can suppress various kinds of jamming signals, including scatter-wave jamming signals, by using the phase relation of jamming signals received by different channels, making it an efficient and direct type of anti-jamming method. In the process of multi-channel cancellation, the phase difference of jamming signals reaching different channels can be generally estimated by the automatic phase searching algorithm, and then the phase difference is used for compensation to finish the jamming signal cancellation. At present, regardless of the channels distributed along the track or across the track, multi-channel SAR systems can employ this anti-jamming technique. However, jamming technology against multi-channel cancellation has rarely been researched. Therefore, a cosinusoidal phase-modulated scatter-wave jamming method aimed at countering the multi-channel cancellation technique is proposed in this paper. First, multi-channel cancellation theory of traditional scatter-wave jamming is analyzed through the dual-channel cancellation technique, and the process of automatic phase searching algorithm based on the rule of minimum energy is summarized. Second, the cosinusoidal phase-modulated signal model is presented and used to improve the traditional scatter-wave jamming signal. Cosinusoidal phase modulation in slow time directly leads to the Doppler spectrum moving and the extension of jamming in the azimuth, according to which the imaging characteristic of the novel jamming signal for SAR is analyzed in detail. Then, the effect of the proposed jamming method working on the dual-channel cancellation system is derived and analyzed. Cosinusoidal phase modulation severely changes the original phase difference, which exerts an effect on the automatic phase searching link to alter the estimated results of the compensation phase in the cancellation process. The changed compensation phase will seriously destroy the real scene imaging. Finally, the simulation experiment results and analysis are presented in which four groups of jamming parameters are set and compared to verify the controllability of jamming. Theoretical analysis and experiment result show that the proposed jamming method can produce multiple false scattering scenes in traditional SAR imaging. In the dual-channel cancellation process, this method causes the estimated compensation phase to vary with slow time sinusoidally. It also causes the real scene image to move repeatedly, which leads to serious image overlapping and produces many dark and bright speckles distributed along the azimuth. The jamming effect can be controlled by setting different jamming parameters, such as modulation frequency and so on. The proposed jamming method is flexible, controllable, and has good stealthiness. It can deactivate the multi-channel cancellation jamming suppression and enhance the jamming effect by utilizing the characteristics of the cancellation process. Importantly, the jamming signal after phase modulation in the azimuth can influence the extraction result of phase information of the signal received by the multi-channel SAR system. Such effect can provide additional ideas and methods for multi-channel SAR jamming research.关键词：synthetic aperture radar (SAR);dual-channel cancellation;scatter-wave jamming;cosinusoidal phase-modulated;compensation phase;electronic countermeasures (ECM)
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发布时间：2021-06-07 -
摘要：The ocean covers more than 71% of the Earth. Studies on vast oceans are of great significance for resource utilization and climate change. Several methods have been employed to detect the interior of the ocean. In-situ methods can accurately obtain marine information but their efficiency is limited. Ocean color remote sensing can collect global data. However, the limited information about the depth and dependence on natural light restrict its applications. Acoustics are widely used for seawater profiling, but they can only work under water due to the high loss in air–water interface. LiDAR is an effective method used to deal with seawater profiling with few limitations of platforms and natural light, in which its applicable coverage is from the water surface to the depth with several tens of meters. A polarized lidar with high vertical resolution (approximately 0.225 m in the water and 0.3 m in the atmosphere) and real-time detecting capability was developed to detect the profile information of atmospheric-water particulates. The laser was linearly-polarized to obtain the polarized information about the water column. Two refractive telescopes were used to collect the backscattering light from the water. Two polarizers were set in front of the telescopes, which only transmitted return signals that were co-polarized or cross-polarized with the laser. A retrieval algorithm based on polarized lidar returns was proposed to obtain atmospheric-water attenuation and depolarized optical products, such as, extinction coefficient (atmosphere), diffuse attenuation coefficient (water), depolarized ratio (atmosphere and water), forward depolarized coefficient (water), and backward depolarized ratio (water). An experimental sample from the inland water in Xiakou Reservoir, China during the night between April 6 and 7, 2017 was presented to discuss the physical meanings and scientific values of the optical products. The retrieved optical products presented the variation of atmospheric aerosols and water turbidity during the night. For the clear atmosphere, the depolarized ratio was approximately 0.01 and the extinction coefficient was approximately 0.08 m –1. However, they became 0.06 and 0.02 m–1, respectively, when the atmosphere was interrupted by several aerosols. For the water column, the diffuse attenuation coefficient varied from 0.6 m–1 to 0.4 m–1, depolarized ratio was from 0.6 to 0.4, and forward depolarized coefficient was from 0.06 m–1 to 0.02 m–1 when water turbidity became constantly clear after the rainfall. The analysis showed that depolarized ratio can be divided into depolarizations caused by forward multiple scattering and backward single scattering. Diffuse attenuation coefficient can be employed to describe the intensity of multiple scattering and is related to the depolarization caused by forward multiple scattering. Furthermore, depolarized ratio depends on the depolarization caused by forward multiple scattering when multiple scattering is strong. Otherwise, depolarized ratio depends on the depolarization caused by backscattering. A polarized lidar was developed to detect atmospheric-water particulate profile information. A retrieval algorithm based on polarized lidar returns was proposed to obtain atmospheric-water attenuation and depolarized optical products. An experimental sample from the inland water in Xiakou Reservoir, China was presented. High-range-resolution optical products were obtained, and the variations of aerosols and water were observed. The analysis presented that depolarized ratio can be divided into depolarizations caused by forward multiple scattering and backward single scattering. Furthermore, depolarized ratio depends on the depolarization caused by forward multiple scattering when multiple scattering is strong. Otherwise, depolarized ratio depends on the depolarization caused by backscattering.关键词：optical remote sensing;lidar;diffuse attenuation coefficient;polarization;multiple scattering- 601
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发布时间：2021-06-07 -
摘要：High-performance Charge-Coupled Devices (CCDs) are the preeminent detectors for space-based photoelectric detection. However, the vulnerability of CCDs to radiation damage in the space radiation environment is a serious threat to space imaging applications in terms of earth-observing spectral measurement and space debris detection. Observing the in-orbit radiation effects of CCDs used in a space imaging system is crucial. This kind of work can provide essential data for the in-orbit maintenance and future design of a space mission. Through calculation and analysis using plenty of in-orbit images generated by a space debris detection experiment satellite, several kinds of imaging abnormalities caused by the space radiation environment of the satellite are observed. The radiation damage on the CCD imager used in the satellite’s visible camera is assessed. First, the abnormal phenomenon of imaging functions is described. Second, transient effects and hot pixels induced by protons in the space environment are analyzed. In addition, the total ionizing dose effects and displacement damage of the CCD imager are estimated to help predict the long-term in-orbit performance of the device. The transient effects mainly result from the instantaneous ionization in pixel structures induced by protons from the South Atlantic Anomaly (SAA). When the satellite traversed the SAA, the number of transient effects is changed in proportion to the proton flux in this position in the SAA. The number of transient effects for one traversing agrees with the Gaussian distribution. All the hot pixels present a high dark current several times larger than that of most normal pixels. The number of hot pixels increase with the time in-orbit of the satellite. The increase is almost linear with the run time or the times passed through the SAA. The hot pixels are mainly attributed to the single particle displacement damage induced by energetic protons in the SAA. No observable correlation is noted between hot pixels and transient effects. The principal influence on the CCD imager is the increase of hot pixels with the time in-orbit. Even in the early stage after the launch of the satellite, the influence of CCD’s hot pixels may be significant, an outcome that is clearly different from the accumulated radiation damage (total ionizing dose effects and accumulated displacement damage) on CCDs. The results of the above work suggest that critical information is obtained for operational risk assessment and in-orbit management of the satellite. In addition, the methodology is formed for in-orbit radiation degradation prediction on image sensor and optical payload. The method may be useful for radiation hardness on a space-based debris detection satellite, which is situated in either low or high earth orbit. The mechanisms of hot pixels generated by proton bombardment still require further study.关键词：space debris detection;charge-coupled device;radiation effects;in-orbit analysis;transient effects;hot pixels- 539
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发布时间：2021-06-07
Technology and Methodology
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摘要：The precise location and identification of buildings are of importance to many geospatial applications. High-resolution satellite images with multispectral channels contain abundant spectral and structural information about ground objects, making these images more suitable for automatic building detection. However, the automatic detection of buildings is still very difficult owing to many obstacles, such as different imaging conditions, complex background, and various types of buildings. Therefore, this paper proposes a novel hierarchical building extraction method based on object-oriented and morphological models for automatic building detection from high-resolution satellite images captured in complex scenes. The proposed method first extracts build-up areas from high-resolution satellite images and then detects buildings from the extracted build-up areas. In the procedure of build-up areas extraction, the multi-scale and multi-directional Gabor wavelet transform is first applied to high-resolution satellite images. Then, a scale-invariant feature point detection algorithm that considers the multi-scale and multi-directional texture properties of build-up areas is proposed for the detection of building feature points. Subsequently, watershed segmentation algorithm with threshold mark is utilized to obtain homogeneous regions, and a spatial voting matrix is computed based on these homogeneous regions and the detected feature points to obtain confidence map. Finally, build-up areas are extracted by segmenting the confidence map using adaptive thresholding algorithm. In the procedure of building extraction, the morphological building index (MBI) is first applied to the extracted build-up areas, and then the initial building results are obtained by performing threshold segmentation on the MBI feature image. Finally, shape attributes such as length–width ratio are used to further refine the initial building extraction results. The performance of the proposed method is evaluated using three high-resolution satellite images captured in complex environments. Evaluation results show that the proposed method can efficiently and accurately detect buildings in complex scenes with an overall accuracy and Kappa coefficient greater than 90% and 0.8, respectively. The proposed method also improves the omission and commission errors by 10.03% and 6.86% on average, respectively, as compared with the performance of the PanTex algorithm. A novel hierarchical building extraction method based on object-oriented and morphological models is proposed in this study. The experimental results highlight the advantages of the hierarchical extraction strategy and demonstrate that the proposed method outperforms the PanTex algorithm. However, good performance of the proposed method relies heavily on the detection of built-up areas, and further improvements should be performed in the future.关键词：high resolution remote sensing imagery;building extraction;Gabor wavelet transform;object-oriented method;spatial voting matrix;morphological building index- 973
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发布时间：2021-06-07 -
摘要：High-level tropospheric formaldehyde (HCHO) columns were observed in Guangdong and Jiangsu Provinces in China by using the long-term records (2005–2016) of Aura OMI measurements. Given the socioeconomic status of Guangdong and Jiangsu Provinces, research concerning the widespread air pollution issues throughout these regions was imperative. Hence, the spatiotemporal variations in HCHO and the potential contributors were analyzed accordingly. We evaluated the spatiotemporal characteristics of HCHO columns in province- and prefecture-level cites to investigate the region of interest in various spatial resolutions. Hence, administrative shapefiles were used to clip the HCHO distributions to represent various sample regions. The spatial resolution of the OMI monthly gridded HCHO columns was 0.25° × 0.25°, but some ancillary data have finer resolutions than that of the level-3 gridded HCHO columns. Accordingly, the inverse distance-weighted interpolation algorithm and KD-Tree method were adopted for re-sampling fine spatial resolutions into 0.25° × 0.25°. The linear least square regression adopted in this study was the approach used to infer the potential trends exhibited in the HCHO images. The trends were fitted pixel by pixel, and the regional trends were calculated via zonal averaging of the administrative regions selected in the previously mentioned shapefiles. The Spearman correlation coefficients were employed to evaluate the similarity of the HCHO distribution and multitude sources (e.g., isoprene and anthropogenic VOCs). In Guangdong Province, HCHO columns concentrated in the Pearl River Delta (PRD), but an increasingly widespread distribution was observed in Jiangsu Province. An upward trend was found in both provinces from 2005 to 2010 that may be closely related to the rapid economy development in that period. Meanwhile, from 2011 to 2016, an overall downward trend was observed in these two regions, given the enacted multitude controls. With regard to seasonality, the highest HCHO columns were observed in spring and autumn, whereas the HCHO during summertime had the lowest concentration in Guangdong. The HCHO seasonal patterns corresponded to the seasonal patterns of sunlight intensity. Among all source sectors, industrial and transportation may contribute the most in the PRD, but all sectors may also contribute in the same order of magnitude in Jiangsu. In addition, biogenic sources may have a comparatively large contribution in the Northeastern Guangdong, and the biomass burning in summertime possibly played a substantial role in the summertime HCHO concentration in Jiangsu Province. Although isoprene plays significant role in HCHO concentration in global scale, the anthropogenic impact cannot be neglected as well. According to previous studies, anthropogenic sources have more than 40% influence. In addition, in comparison with isoprene, the Spearman correlation coefficients were high for anthropogenic VOCs with HCHO columns. Given the relatively large amount of emissions, industrial sources may be influential for more than 40%. Biomass burning sources cannot be ignored in woodlands, such as in Northeastern Guangdong. Transportation sources exhibited the most similar Spearman correlation coefficients in Guangdong, especially in PRD. Therefore, even a downward trend of transportation emissions was observed in PRD. They may account for a large amount of HCHO concentration. After a comparison, power-based emissions only took a small fraction of approximately 1% for Guangdong and Jiangsu.关键词：HCHO;OMI;VOC;photochemical reaction;anthropogenic emissions;trend analysis- 627
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- 10
发布时间：2021-06-07 -
摘要：The distinction of local biodiversity in arid areas is complicated and controversial. Hence, the investigation of the spatial pattern of species richness and its causes in Xinjiang can be used as the basis for biodiversity conservation in the region, and it is also important for regional biodiversity research. On the basis of the data on the distribution of birds and mammals in Xinjiang and long-time series environmental data, such as climate, topography, and remote sensing (FAPAR), this study investigated the species richness and environmental spatial pattern of birds and mammals. Furthermore, the forming mechanism of the disparity pattern of species richness was evaluated through a single-factor correlation analysis used in various land-use types and elevation zones. This research was based on the analysis of the richness of bird and mammal species and the temporal and spatial distribution of environmental factors in Xinjiang. A range of relevant environmental elements were utilized. Then, correlation and linear regression analyses were used to investigate the independent influence of environmental factors on the overall abundance pattern of birds and mammals in a specific living environment in Xinjiang. Finally, the main environmental factors that determine the richness pattern of birds and mammals in specific habitats were selected according to the correlation coefficient. Statistical analysis was realized via the MATLAB software. In general, among the various habitat types, the remote sensing parameter factors (e.g., DHI, NDVI, etc.) are more closely related to the species richness distribution of the two groups than to the climatic factors (e.g., temperature and precipitation). Specifically, among remote sensing parameter factors, the correlation between the habitat index factor based on FAPAR and richness was greater than that of the environmental factor based on vegetation index (DHI_cum>NDVI-cum>EVI-cum). Among the climatic factors, in grassland habitats or at low altitudes, the average annual precipitation factor was better than the average annual temperature factor in verifying the richness distribution. In Xinjiang, the dominant factors affecting the distribution of the richness of bird and mammal species were habitat heterogeneity and environmental stability. Their explanatory power was stronger than the productivity and the environment heat in many types of generation territories. Habitat heterogeneity was the main factor affecting the spatial distribution pattern of richness of birds and mammalian species in Xinjiang, where 70% of the arid areas are not covered by vegetation. Hence, habitat heterogeneity was the main factor affecting the spatial distribution pattern of the richness of bird and mammal species in Xinjiang. Species resources in Xinjiang were abundant, and the overall pattern was complex. The covariation trend of various species and environmental factors was not completely consistent. However, a considerable number of species.关键词：Xinjiang;patterns of species richness;environmental variables;parameter;correlativity- 569
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- 4
发布时间：2021-06-07 -
摘要：A bamboo forest is a special and important forest resource that is distributed in subtropics of China. However, present methods cannot quickly and accurately extract spatiotemporal distribution information of a bamboo forest at the national scale. This study presents a method for extracting bamboo forest information in China by combining decision tree and linear spectral unmixing methods using MODIS NDVI, reflectance product, and provincial Landsat classification data in 2003, 2008, and 2014. The steps are as follows: First, forest information was extracted based on the maximum likelihood method; second, a decision tree model was constructed to extract bamboo forest distribution information based on a forest information map; finally, the linear spectral unmixing method was applied to obtain the abundance map of a bamboo forest in China, and the bamboo forest area was calculated. The main experimental results are as follows: (1) The forest information in China was extracted through the maximum likelihood method. The accuracy of a producer and a user was higher than 90%, and the Kappa coefficient was 0.93, thereby establishing the extraction of bamboo forest information. (2) The decision tree constructed by using a C5.0 algorithm satisfactorily extracted the bamboo forest spatiotemporal distribution information in China, with an average classification accuracy of 80%. (3) The estimated bamboo forest area of each province in China was highly correlated with the observations, with the R2 values of 0.98, 0.97, and 0.95, correspondingly. The RMSE ranged from 3.92×104 to 9.58×104 ha, thus indicating that the estimated bamboo forest area was essentially consistent with the actual situation. In this study, the C5.0 algorithm decision tree, which is based on the MODIS remote sensing data, combined with the mixed pixel decomposition presents accurate extraction of bamboo forest spatiotemporal distribution information in China. This method provides the technical approach and data support for the dynamic monitoring and management of bamboo forest resources.关键词：Chinese bamboo forest;MODIS data;C5.0 algorithm;decision tree classification;mixed pixel decomposition- 747
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- 194
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- 7
发布时间：2021-06-07
Remote Sensing Applications
- “Chang'e-4 lander achieves high-precision localization, crucial for mission safety and efficiency. The paper introduces localization techniques using Chang'e-2 and LROC NAC images, as well as Chang'e-4 camera images, determining the lander's precise location at (177.588°E, 45.457°S). This multi-dataset localization is valuable for comprehensive scientific exploration of the landing site.”
摘要：High precision localization of Chang’e-4 lander is critical to support safe and efficient mission operations. This paper presents the lander localization techniques, including image feature matching and monoscopic image measurement, using digital orthophoto maps of Chang’e-2 and LROC NAC images, descent camera images and monitoring camera image of Chang’e-4 lander. The lander location is precisely determined to be (177.588°E, 45.457°S) using these techniques. Localization of the lander in multiple datasets is valuable for synergistic scientific investigation of the landing site.关键词：Chang’e-4;lander localization;descent camera image;monitoring camera image;multi-source data- 415
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发布时间：2024-10-10 -
Progress
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