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Simulations of GaoFen-5 Directional Polarimetric Camera(DPC) Observations Using the Advanced Vector Discrete Ordinate Radiative Transfer Model

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Advances in Atmospheric Sciences 2025年第3期42卷 486-500页

作者： Yuchen XIE Ziqiang ZHU Fuzhong WENG Zhengqiang LI Xiuzhen HAN School of remote sensing&Geomatics Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Earth System Modeling and Prediction Centre China Meteorological AdministrationBeijing 100081China University of Chinese Academy of Sciences Beijing 100049China Environmental Protection Key Laboratory of satellite remote sensing&Key Laboratory of remote sensing and Digital Earth Aerospace Information Research InstituteChinese Academy of Sciences.Beijing 100101China National satellite Meteorological Center China Meteorological AdministrationBeijing 100081China

In recent years,polarization remote sensing has garnered increasing attention,particularly within the realm of *** accurately simulate polarization information,the vector discrete-ordinate radiative transfer(VDISORT)model developed earlier by the community is further enhanced to an advanced version(referred to as A-VDISORT)through an improved ocean surface *** Fresnel reflection matrix,which includes wind-generated roughness and shading effects,is served by an ocean bidirectional reflection distribution function(BRDF).The simulation from AVDISORT is compared with SCIATRAN for a Rayleigh scattering atmosphere,and the influence of water-leaving radiance is analyzed by the PSTAR(Polarized System for Transfer of Atmospheric Radiation) *** GaoFen-5 Directional Polarimetric Camera(DPC) observations with polarization and multi-angle information,clear-sky pixel recognition over the ocean is first carried *** DPC reflectance of clear conditions is normalized and compared with the *** is shown that A-VDISORT has a high simulation accuracy with a bias of –*** difference between simulation and observation exhibits a standard normal probability distribution function.

关键词： vector radiative transfer equation A-VDISORT ocean BRDF GF-5 DPC

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Unveiling urbanization effects on trees outside forests along the urban-rural gradient in megacity Bengaluru

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Forest Ecosystems 2025年第1期12卷 56-65页

作者： Tao Jiang Maximilian Freudenberg Christoph Kleinn V.P.Tewari B.N.Diwakara Nils Nolke Forest Inventory and remote sensing Department Faculty of Forest Sciences and Forest EcologyUniversity of GottingenGottingenGermany Himalayan Forest Research institute ICFREShimlaIndia institute of Wood Science and Technology IWSTMalleswaramBengaluruIndia

Rapid urbanization has caused significant changes along the urban-rural gradient,leading to a variety of landscapes that are mainly shaped by human *** dynamic interplay also influences the distribution and characteristics of trees outside forests(TOF).Understanding the pattern of these trees will support informed decision-making in urban planning,in conservation strategies,and altogether in sustainable land management practices in the urban *** this study,we employed a deep learning-based object detection model and high resolution satellite imagery to identify 1.3 million trees with bounding boxes within a 250 km^(2)research transect spanning the urban-rural gradient of Bengaluru,a megacity in Southern ***,we developed an allometric equation to estimate diameter at breast height(DBH)from the tree crown diameter(CD)derived from the detected bounding *** study focused on analyzing variations in tree density and tree size along this *** findings revealed distinct patterns:the urban domain displayed larger tree crown diameters(mean:8.87 m)and DBH(mean:43.78 cm)but having relatively low tree density(32 trees per hectare).Furthermore,with increasing distance from the city center,tree density increased,while the mean tree crown diameter and mean tree basal area decreased,showing clear differences of tree density and size between the urban and rural domains in *** study offers an efficient methodology that helps generating instructive insights into the dynamics of TOF along the urban-rural *** may inform urban planning and management strategies for enhancing green infrastructure and biodiversity conservation in rapidly urbanizing cities like Bengaluru.

关键词： Individual tree detection Urbanization Tree density Tree crown diameter

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On-orbit attitude planning for Earth observation imaging with star-based geometric calibration

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Science China(Technological Sciences) 2025年第2期68卷 243-256页

作者： Di HUANG Zhifu WANG Jianya GONG Haoran JI institute of Aerospace Science and Technology School of Remote Sensing and Information EngineeringWuhan UniversityWuhan 430072China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingSchool of Remote Sensing and Information EngineeringWuhan UniversityWuhan 430072China National Key Laboratory of Air-based Information Perception and Fusion Luoyang 471009China Intelligent Game and Decision Laboratory Beijing 100071China

To improve the quality of remote sensing images,a novel on-orbit attitude planning method for Earth observation imaging with star-based geometric calibration is presented in this *** traditional imaging processes,the proposed method includes both pre-calibration and post-calibration stages to enhance the accuracy of satellite geometric positioning.A multiple-constraint attitude planning algorithm was developed to ensure star-based calibration,wherein the satellite camera and star sensors simultaneously capture the images of *** integration of cameras and multiple star sensors enables effective attitude *** the Earth imaging stage,a fast on-orbit attitude planning algorithm was developed to determine the satellite attitude and the optimal imaging times for ground *** with existing methods,the fast on-orbit attitude planning algorithm can significantly reduce computational time and resource consumption via initial value selection and *** demonstrate the effectiveness of the proposed attitude planning method,which was successfully applied to Wuhan 1 satellite.

关键词： attitude planning Earth observation imaging geometric calibration attitude constraints

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Human activities rather than climate change dominate the growth of carbon fluxes in the Hexi Corridor oasis area, China

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Journal of Geographical Sciences 2025年第2期35卷 252-277页

作者： ZHOU Xuqiang WANG Xufeng REN Zhiguo ZHANG Yang TAN Junlei NAWAZ Zain Key Laboratory of Cryospheric Science and Frozen Soil Engineering Key Laboratory of Remote Sensing of Gansu Province Heihe Remote Sensing Experimental Research Station Northwest Institute of Eco-Environment and Resources CAS University of Chinese Academy of Sciences Department of Geography Government College University Faisalabad

Carbon fluxes are essential indicators assessing vegetation carbon cycle ***,the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes in arid oasis and non-oasis area remains ***,we assessed and predicted the future effects of climate change and human activities on carbon fluxes in the Hexi *** results showed that the annual average gross primary productivity （GPP）,net ecosystem productivity （NEP）,and ecosystem respiration （Reco） in the Hexi Corridor oasis increased by 263.91 g C·m–2·yr–1,118.45 g C·m–2·yr–1and 122.46 g C·m–2·yr–1,respectively,due to the expansion of the oasis area by 3424.84 km2caused by human activities from 2000 to *** oasis and non-oasis arid ecosystems in the Hexi Corridor acted as carbon *** to the non-oasis area,the carbon fluxes contributions of oasis area increased,ranging from 10.21%to 13.99%for GPP,8.50%to11.68%for NEP,and 13.34%to 17.13%for *** contribution of the carbon flux from the oasis expansion area to the total carbon flux change in the Hexi Corridor was 30.96%(7.09 Tg C yr–1) for GPP,29.57%(3.39 Tg C yr–1) for NEP and 32.40%(3.58 Tg C yr–1) for *** changes in carbon fluxes in the oasis area were mainly attributed to human activities （oasis expansion） and temperature,whereas non-oasis area was mainly due to climate ***,the future increasing trends were observed for GPP （64.99%）,NEP（66.29%） and Reco （82.08%） in the Hexi *** study provides new insights into the regulatory mechanisms of carbon cycle in the arid oasis and non-oasis area.

关键词： carbon fluxes climate change Hexi Corridor oasis human activities random forest

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Unveiling urbanization effects on trees outside forests along the urban-rural gradient in megacity Bengaluru

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Forest Ecosystems 2025年第01期 56-65页

作者： Tao Jiang Maximilian Freudenberg Christoph Kleinn V.P.Tewari B.N.Diwakara Nils N?lke Forest Inventory and remote sensing Department Faculty of Forest Sciences and Forest Ecology University of G?ttingen Himalayan Forest Research institute ICFRE institute of Wood Science and Technology IWST

Rapid urbanization has caused significant changes along the urban-rural gradient, leading to a variety of landscapes that are mainly shaped by human activities. This dynamic interplay also influences the distribution and characteristics of trees outside forests(TOF). Understanding the pattern of these trees will support informed decision-making in urban planning, in conservation strategies, and altogether in sustainable land management practices in the urban context. In this study, we employed a deep learning-based object detection model and high resolution satellite imagery to identify 1.3 million trees with bounding boxes within a 250 km2research transect spanning the urban-rural gradient of Bengaluru, a megacity in Southern India. Additionally, we developed an allometric equation to estimate diameter at breast height(DBH) from the tree crown diameter(CD) derived from the detected bounding boxes. Our study focused on analyzing variations in tree density and tree size along this gradient. The findings revealed distinct patterns: the urban domain displayed larger tree crown diameters(mean:8.87 m) and DBH(mean: 43.78 cm) but having relatively low tree density(32 trees per hectare). Furthermore,with increasing distance from the city center, tree density increased, while the mean tree crown diameter and mean tree basal area decreased, showing clear differences of tree density and size between the urban and rural domains in Bengaluru. This study offers an efficient methodology that helps generating instructive insights into the dynamics of TOF along the urban-rural gradient. This may inform urban planning and management strategies for enhancing green infrastructure and biodiversity conservation in rapidly urbanizing cities like Bengaluru.

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Extracting ship and heading from Sentinel-2 images using convolutional neural networks with point and vector learning

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Journal of Oceanology and Limnology 2025年第1期43卷 16-28页

作者： Xiunan LI Peng CHEN Jingsong YANG Wentao AN Dan LUO Gang ZHENG Aiying LU Ocean College Zhejiang UniversityZhoushan 316021China State Key Laboratory of satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China National satellite Ocean Application Service Ministry of Natural ResourcesBeijing 100081China

Obtaining accurate ship positions and headings in remote sensing images plays a crucial role in various ***,current deep learning-based methods primarily focus on ship position detection,while the detection of ship wakes relies on traditional non-deep learning approaches,which often underperform in complex marine *** proposed a novel,simple,and efficient method called Point-Vector *** proposed method leverages convolutional neural networks(CNN)for feature extraction and subsequently integrates multi-scale features to generate high-resolution feature *** the final stage,ship positions and headings are represented using a combination of points and *** experiments with results from automatic identification system(AIS)reports demonstrate that our method achieved impressive performance in two-class ship target detection,with an average precision of 96.4%,recall rate of 94.3%,and an F 1 score of 95.2%.Notably,the average heading error was 3.3°.The proposed model achieved a practical inference speed(FPS>30),and the average processing time for inferring a large-scale Sentinel-2 remote sensing image was 11.4 s.

关键词： deep learning ship detection heading remote sensing Sentinel-2

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satellite-assisted 6G wide-area edge intelligence:dynamics-aware task offloading and resource allocation for remote IoT services

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Science China(Information Sciences) 2025年第2期68卷 248-268页

作者： Di ZHAO Rui DING Bin SONG State Key Laboratory of Integrated Services Networks Xidian University Hangzhou institute of Technology Xidian University China satellite Network Group Co. Ltd.

Future 6G networks will integrate non-terrestrial communication with mobile edge computing to enable wide-area edge intelligence, providing ubiquitous communication and computation services for everyone and everything. In this paper, we introduce the intelligent cloud-edge-device architecture into low Earth orbit(LEO) satellite-supported remote Internet of Things(IoT) networks to facilitate latency-sensitive and compute-intensive IoT applications. However, the dynamic spatio-temporal characteristics inherent in LEO satellite networks, such as the high volatility of task traffic and the high mobility of space nodes, pose severe challenges. For efficient task execution, we investigate the joint optimization of cross-region task offloading and cross-domain resource allocation, and innovatively propose a spatio-temporal attention-based proximal policy optimization(STA-PPO) algorithm. Specifically, the temporal attention-based actor network analyzes the timing dependencies of task arrival and makes time-variant decisions. Simultaneously, the spatial attention-based critic network captures the spatial variations of satellite motion and evaluates the topology-related value. We verify the effectiveness of the cloud-edge-device collaboration through extensive simulations. Numerical results demonstrate that the STA-PPO algorithm outperforms benchmarks, showing the lowest system delay and the highest link throughput.

关键词： 6G wide-area edge intelligence cross-region task offloading cross-domain resource allocation spatio-temporal attention proximal policy optimization

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Simulations of GaoFen-5 Directional Polarimetric Camera(DPC) Observations Using the Advanced Vector Discrete Ordinate Radiative Transfer Model

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Advances in Atmospheric Sciences 2025年第3期 486-500页

作者： Yuchen XIE Ziqiang ZHU Fuzhong WENG Zhengqiang LI Xiuzhen HAN School of remote sensing & Geomatics Engineering Nanjing University of Information Science & Technology Earth System Modeling and Prediction Centre China Meteorological Administration University of Chinese Academy of Sciences Environmental Protection Key Laboratory of satellite remote sensing & Key Laboratory of remote sensing and Digital Earth Aerospace Information Research Institute Chinese Academy of Sciences National satellite Meteorological Center China Meteorological Administration

In recent years, polarization remote sensing has garnered increasing attention, particularly within the realm of meteorology. To accurately simulate polarization information, the vector discrete-ordinate radiative transfer(VDISORT)model developed earlier by the community is further enhanced to an advanced version(referred to as A-VDISORT)through an improved ocean surface reflection. The Fresnel reflection matrix, which includes wind-generated roughness and shading effects, is served by an ocean bidirectional reflection distribution function(BRDF). The simulation from AVDISORT is compared with SCIATRAN for a Rayleigh scattering atmosphere, and the influence of water-leaving radiance is analyzed by the PSTAR(Polarized System for Transfer of Atmospheric Radiation) model. For GaoFen-5 Directional Polarimetric Camera(DPC) observations with polarization and multi-angle information, clear-sky pixel recognition over the ocean is first carried out. The DPC reflectance of clear conditions is normalized and compared with the observations. It is shown that A-VDISORT has a high simulation accuracy with a bias of –0.0053. The difference between simulation and observation exhibits a standard normal probability distribution function.

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Impact of net-zero emissions on atmospheric CO2 concentration in China: Ideal simulations based on the GEOS-Chem model

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Science China Earth Sciences 2025年第3期68卷 867-881页

作者： Jingye TAN Jun WANG Huiqin MAO Hengmao WANG Zhiqiang LIU Meirong WANG Ran YAN Xunmei WANG Fei JIANG Frontiers Science Center for Critical Earth Material Cycling International Institute for Earth System Science Nanjing University Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University satellite Environmental Application Center Ministry of Environmental Protection CMA Key Open Laboratory of Transforming Climate Resources to Economy Chongqing Institute of Meteorological Sciences State Key Laboratory of Climate System Prediction and Risk Management Key Laboratory of Meteorological Disaster Ministry of EducationCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Xizang Field Station for Scientific Observation and Research on Atmospheric Water Cycle in Mêdog Xigazê and Mêdog National Climate ObservatoryXizang Meteorological Service

Elevated atmospheric carbon dioxide（CO2） concentrations have caused global climate change such as global warming and more frequent climate extremes. Countries worldwide have proposed carbon neutrality strategies to curb the rising CO2concentrations. To investigate the impact of China's carbon neutrality goal on atmospheric CO2concentrations, we conducted a series of ideal simulations from 2015 to 2019 using a global 3D chemistry transport model, Goddard Earth Observing System Chemistry（GEOS-Chem）. Compared with the column-averaged dry-air mole fraction of atmospheric CO2（XCO2） from Orbiting Carbon Observatory-2（OCO-2） and surface CO2measurements in Obs Pack, we find that GEOS-Chem effectively reproduces the spatiotemporal variability of CO2. The model exhibits a root mean square error（RMSE） of 1.51 ppm（R2=0.89） for OCO-2 XCO2in China and 2.65 ppm（R2=0.75） for surface CO2concentrations at the WLG station. Further, compared to 2.83 ppm yr-1in the control experiment, we suggest that net-zero CO2emissions in China decelerate the increasing trends of XCO2to 1.81 ppm yr-1,making a decrease of approximately 35.89%. Meanwhile, the seasonal cycle amplitude（SCA） of XCO2is moderately reduced from 7.39±0.81 to 6.75±0.70 ppm, representing a relative reduction of 9.91%. Spatially, net-zero CO2emissions induce a more significant decrease in XCO2trends over northern and southern China, while their impact on SCA is more evident in northern and northeastern China. Moreover, ideal experiments demonstrate that zero fossil CO2emissions lead to a greater attenuation of the linear trends of XCO2by 40.81%, while the absence of terrestrial CO2sinks largely diminishes the SCA by 16.61%. Additionally,trends and SCA in surface CO2concentrations exhibit almost identical decreasing responses to net-zero CO2emissions but display greater sensitivities compared to XCO2. Overall, our study underscores the potential of China's carbon neutrality goal in mitigating global warming, underscoring the need

关键词： XCO2 GEOS-Chem Carbon neutrality Net-zero emissions Surface CO2 concentrations

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Distribution and mapping of temperate savanna in the sandy lands of eastern China

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Science China Earth Sciences 2025年第1期68卷 128-141页

作者： Xiaoya LI Feng WANG Tao DUAN Kaijie YANG Bin YANG Chunmei WANG Xin TIAN Qi LU institute of Ecological Conservation and Restoration Institute of Desertification StudiesChinese Academy of ForestryBeijing100091China institute of Desertification Institute of Desertification StudiesChinese Academy of ForestryBeijing100091China institute of Great Green Wall Bayan Nur015200China satellite Application Centre for Ecology and Environment MEEBeijing100094China institute of Microelectronics Chinese Academy of SciencesBeijing100029China Aerospace Information Research institute Chinese Academy of SciencesBeijing100094China institute of Forest Resource Information Techniques Chinese Academy of ForestryBeijing100091China

Savannas are distributed globally across various *** perform a significant socioeconomic role in regulating net primary productivity and the terrestrial carbon *** to the high spatial heterogeneity induced by the mixed distribution of trees and grasses,current global land-cover classification maps often classify savannas as forests or grasslands Temperate savannas in China cover a vast area,yet their spatial patterns and extent remain poorly *** study developed a novel remote sensing temperate savannas mapping method by integrating very high-resolution(VHR)unmanned aerial vehicle(UAV)and GF-6 satellite imagery based on the vegetation structure characteristics of temperate savannas using the FAO definition of *** and validation datasets were collected from VHR UAV imagery covering the main temperate savannah types with a ground area of 1818 *** fractional woody vegetation cover(FWVC)and fractional herbaceous vegetation cover(FHVC)in temperate savannas were estimated by integrating Classification and Regression Tree and Random Forest *** current distribution of temperate savannas in the Horqin and Otindag Sandy Lands of Eastern China was mapped to a unit area of 0.5 *** root-mean-square error(RMSE)values for the FWVC and FHVC models were 10.69%and 11.67%,and the R^(2)values were 0.66 and 0.63,*** assessment indicated that the new temperate savanna map had high identification accuracy,with a Kappa coefficient of 0.70,overall accuracy of 0.88,and average accuracy of *** savannas in the sandy lands of eastern China were primarily distributed in the northern Horqin Sandy Land the central and eastern regions of the Otindag Sandy Land,and the transition zone from the southern slopes of the Greater Khingan Mountains to the plains,covering a total area of 3.27×10^(6)*** main savannah types were elm,oak/maple,and shrub *** savannas were widely distributed in the Otindag Sandy Land a

关键词： Temperate savanna UAV imagery GF-6 Fractional woody vegetation cover Fractional herbaceous vegetation cover Machine learning

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