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Remote sensing experiments for earth system science

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International Journal of Digital Earth 2021年第10期14卷 1237-1242页

作者： Tianjie Zhao Michael H.Cosh Alexandre Roy xihan mu Yubao Qiu Jiancheng Shi Aerospace Information Research Institute Chinese Academy of SciencesBeijingPeople’s Republic of China USDA-Agricultural Research Service Beltsville Agricultural Research CenterHydrology and Remote Sensing LaboratoryBeltsvilleMDUSA Universitédu QuébecàTrois-Rivières QuébecCanada Faculty of Geographical Science Beijing Normal UniversityBeijingPeople’s Republic of China National Space Science Center Chinese Academy of SciencesBeijingPeople’s Republic of China

The Earth system is an integrated system that can be divided into six main subsystems:geosphere,atmosphere,hydrosphere,cryosphere,biosphere,and *** subsystems are interconnected through the flows of global energy,water,and carbon,which are fundamental constituent cycles within the Earth *** improve our predictive understanding of the subsystem on our changing planet,there is a need to better represent these subsystems through modelling and *** central role of these fundamental cycles has prompted scientific institutions or meteorological centers to develop digital platforms dedicated to the integration,modelling,and assimilation of Earth observation data,e.g.,Big Earth Data Science Engineering(Guo,Li,and Qiu 2020).

关键词： system earth prompt

Quantitative Evaluation of Leaf Inclination Angle Distribution on Leaf Area Index Retrieval of Coniferous Canopies

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Journal of Remote Sensing 2021年第1期2021卷 1-15页

作者： Guangjian Yan Hailan Jiang Jinghui Luo xihan mu Fan Li Jianbo Qi Ronghai Hu Donghui Xie Guoqing Zhou State Key Laboratory of Remote Sensing Science Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Southwest China Research Institute of Electronic Equipment Chengdu 610036China Guilin University of Technology Guilin 532100China

Both leaf inclination angle distribution(LAD)and leaf area index(LAI)dominate optical remote sensing *** G-function,which is a function of LAD and remote sensing geometry,is often set to 0.5 in the LAI retrieval of coniferous canopies even though this assumption is only valid for spherical *** uncertainties are thus ***,because numerous tiny leaves grow on conifers,it is nearly impossible to quantitatively evaluate such uncertainties in LAI *** this study,we proposed a method to characterize the possible change of G-function of coniferous canopies as well as its effect on LAI ***,a multi-Directional Imager(MDI)was developed to capture stereo images of the branches,and the needles were *** accuracy of the inclination angles calculated from the reconstructed needles was ***,we analyzed whether a spherical distribution is a valid assumption for coniferous canopies by calculating the possible range of the G-function from the measured LADs of branches of Larch and Spruce and the true G-functions of other species from some existing inventory data and threedimensional(3D)tree *** show that the constant G assumption introduces large errors in LAI retrieval,which could be as large as 53%in the zenithal viewing direction used by spaceborne *** a result,accurate LAD estimation is *** the absence of such data,our results show that a viewing zenith angle between 45 and 65 degrees is a good choice,at which the errors of LAI retrieval caused by the spherical assumption will be less than 10%for coniferous canopies.

关键词： distribution function viewing

Mapping Spatially Seamless Fractional Vegetation Cover over China at a 30-m Resolution and Semimonthly Intervals in 2010-2020 Based on Google Earth Engine

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Journal of Remote Sensing

Journal of Remote Sensing 2023年第1期3卷 444-462页

作者： Tian Zhao xihan mu Wanjuan Song Yaokai Liu Yun Xie Bo Zhong Donghui Xie Lingmei Jiang Guangjian Yan State Key Laboratory of Remote Sensing Science Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Beijing Engineering Research Center for Global Land Remote Sensing Products Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China Key Laboratory of Quantitative Remote Sensing Information Technology Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China College of Arts and Sciences Beijing Normal UniversityZhuhai 519087China

Fractional vegetation cover(FVC)is a critical biophysical parameter that characterizes the status of terrestrial *** spatial resolutions of most existing FVC products are still at the kilometer ***,there is growing demand for FVC products with high spatial and temporal resolutions in remote sensing *** study developed an operational method to generate 30-m/15-day FVC products over *** datasets were employed to generate a continuous normalized difference vegetation index(NDVI)time series based on the Google Earth Engine platform from 2010 to *** NDVI was transformed to FVC using an improved vegetation index(VI)-based mixture model,which quantitatively calculated the pixelwise coefficients to transform the NDVI to FVC.A comparison between the generated FVC,the Global LAnd Surface Satellite(GLASS)FVC,and a global FVC product(GEOV3 FVC)indicated consistent spatial patterns and temporal profiles,with a root mean square deviation(RMSD)value near 0.1 and an R^(2) value of approximately *** validation was conducted using ground measurements from croplands at the Huailai site and forests at the Saihanba ***,validation was performed with the FVC time series data observed at 151 plots in 22 small *** generated FVC showed a reasonable accuracy(RMSD values of less than 0.10 for the Huailai and Saihanba sites)and temporal trajectories that were similar to the field-measured FVC(RMSD values below 0.1 and R^(2) values of approximately 0.9 for most small watersheds).The proposed method outperformed the traditional VIbased mixture model and had the practicability and flexibility to generate the FVC at different resolutions and at a large scale.

关键词： Mapping Engine Spatial

High Spatial Resolution and High Temporal Frequency(30-m/15-day) Fractional Vegetation Cover Estimation over China Using multiple Remote Sensing Datasets:Method Development and Validation

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Journal of Meteorological Research 2021年第1期35卷 128-147页

作者： xihan mu Tian ZHAO Gaiyan RUAN Jinling SONG Jindi WANG Guangjian YAN Tim RMCVICAR Kai YAN Zhan GAO Yaokai LIU Yuanyuan WANG State Key Laboratory of Remote Sensing Science Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Beijing Engineering Research Center for Global Land Remote Sensing Products Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China CSIRO Land and Water ACT2601Australia Department of Earth and Environment Boston UniversityBostonMA 02215USA Jiangsu Institute of Urban Planning and Design Nanjing 210036China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China National Satellite Meteorological Center China Meteorological AdministrationBeijing 100081China

High spatial resolution and high temporal frequency fractional vegetation cover(FVC) products have been increasingly in demand to monitor and research land surface processes. This paper develops an algorithm to estimate FVC at a 30-m/15-day resolution over China by taking advantage of the spatial and temporal information from different types of sensors: the 30-m resolution sensor on the Chinese environment satellite(HJ-1) and the 1-km Moderate Resolution Imaging Spectroradiometer(MODIS). The algorithm was implemented for each main vegetation class and each land cover type over China. First, the high spatial resolution and high temporal frequency normalized difference vegetation index(NDVI) was acquired by using the continuous correction(CC) data assimilation method. Then, FVC was generated with a nonlinear pixel unmixing model. Model coefficients were obtained by statistical analysis of the MODIS NDVI. The proposed method was evaluated based on in situ FVC measurements and a global FVC product(GEOV1 FVC). Direct validation using in situ measurements at 97 sampling plots per half month in 2010 showed that the annual mean errors(MEs) of forest, cropland, and grassland were-0.025, 0.133, and 0.160, respectively, indicating that the FVCs derived from the proposed algorithm were consistent with ground measurements [R2 = 0.809,root-mean-square deviation(RMSD) = 0.065]. An intercomparison between the proposed FVC and GEOV1 FVC demonstrated that the two products had good spatial–temporal consistency and similar magnitude(RMSD approximates 0.1). Overall, the approach provides a new operational way to estimate high spatial resolution and high temporal frequency FVC from multiple remote sensing datasets.

关键词： fractional vegetation cover(FVC) high spatial resolution and high temporal frequency data fusion normalized difference vegetation index(NDVI) pixel unmixing model multiple remote sensing datasets

A Novel Inversion Approach for the Kernel-Driven BRDF Model for Heterogeneous Pixels

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Journal of Remote Sensing

Journal of Remote Sensing 2023年第1期3卷 160-177页

作者： Hanliang Li Kai Yan Si Gao Xuanlong Ma Yelu Zeng Wenjuan Li Gaofei Yin xihan mu Guangjian Yan Ranga B.Myneni State Key Laboratory of Remote Sensing Science Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China School of Land Science and Technology China University of GeosciencesBeijing 100083China College of Earth and Environmental Sciences Lanzhou UniversityLanzhou 730020China College of Land Science and Technology China Agricultural UniversityBeijing 100083China State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China the Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China INRAE Avignon UniversitéUMR EMMAHAvignon F-84000France Faculty of Geosciences and Environmental Engineering Southwest Jiaotong UniversityChengdu 610031China Department of Earth and Environment Boston UniversityBostonMA 02215USA

The bidirectional reflectance distribution function(BRDF)of the land surface contains information relating to its physical structure and *** BRDF modeling for heterogeneous pixels is important for global ecosystem monitoring and radiation balance ***,the original kerneldriven models,which many operational BRDF/Albedo algorithms have adopted,do not explicitly consider the heterogeneity within heterogeneous pixels,which may result in large fitting *** this paper,we attempted to improve the fitting ability of the kernel-driven models over heterogeneous pixels by changing the inversion approach and proposed a dynamic weighted least squares(DWLS)inversion *** performance of DWLS and the traditional ordinary least squares(OLS)inversion approach were compared using simulated *** also evaluated its ability to reconstruct multiangle satellite observations and provide accurate BRDF using unmanned aerial vehicle *** results show that the developed DWLS approach improves the accuracy of modeled BRDF of heterogeneous *** DWLS approach applied to satellite observations shows better performance than the OLS method in study regions and exhibits smaller mean fitting residuals both in the red and near-infrared *** DWLS approach also shows higher BRDF modeling accuracy than the OLS approach with unmanned aerial vehicle *** results indicate that the DWLS inversion approach can be a better choice when kernel-driven models are used for heterogeneous pixels.

关键词： BRDF kernel Inversion

基于多时相GF-6遥感影像的水稻种植面积提取

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农业工程学报 2021年第17期37卷 189-196页

作者：张悦琦李荣平穆西晗任鸿瑞太原理工大学测绘科学与技术系太原030024 北京师范大学遥感科学国家重点实验室北京100875 中国气象局沈阳大气环境研究所沈阳110166

为获取高精度水稻种植面积提取方法和分析红边信息在作物识别能力上的优越性,该研究选取辽宁省盘锦市为研究区域,利用2020年水稻关键物候期的多时相高分6号宽幅相机(GF-6 WFV)遥感影像,构建归一化植被指数(Normalized Difference Vegeta... 详细信息

为获取高精度水稻种植面积提取方法和分析红边信息在作物识别能力上的优越性,该研究选取辽宁省盘锦市为研究区域,利用2020年水稻关键物候期的多时相高分6号宽幅相机(GF-6 WFV)遥感影像,构建归一化植被指数(Normalized Difference Vegetation Index,NDVI)、归一化水体指数(Normalized Difference Water Index,NDWI)、比值植被指数(Ratio Vegetation Index,RVI)和归一化差异红边1指数(Normalized Difference Red-Edge 1 Index,NDRE1),根据各地物类型进行时序分析,在获得水稻面积粗提取结果的基础上对其他地类进行掩膜,准确提取水稻种植面积。对2020年盘锦市水稻提取结果进行精度分析,结果表明,基于实测数据进行精度验证的总体精度为94.44%,基于目视解译数据进行精度验证的总体精度和Kappa系数分别为95.60%和0.91。根据目视解译数据对有无红边波段参与的水稻提取结果进行对比分析可知,红边波段的引入使总体分类精度、水稻制图精度和Kappa系数分别提高了3.20个百分点、6.00个百分点和0.06。该研究证明红边波段可以有效降低作物的错分、漏分情况,对水稻精准估产和丰富农作物遥感监测方法具有重要作用,显示出国产红边卫星数据在作物分类、面积提取方面具有巨大应用潜力。

关键词：遥感作物分类面积提取水稻高分六号卫星红边波段

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规则林地覆盖度照相测量法的精度分析

农业工程学报 2013年第19期29卷 152-158页

作者：赵继强谢东辉孟夏穆西晗阎广建北京师范大学地理学与遥感科学学院遥感科学国家重点实验室北京100875

为定量研究照相法测量规则林地覆盖度中采样策略、相机非垂直拍摄等因素对覆盖度计算结果的影响,该文对河北怀来的一片梨树林进行了实地测量,通过对测量数据的统计计算,利用植被结构生成软件Onyx tree professional重建梨树林场景,采用... 详细信息

为定量研究照相法测量规则林地覆盖度中采样策略、相机非垂直拍摄等因素对覆盖度计算结果的影响,该文对河北怀来的一片梨树林进行了实地测量,通过对测量数据的统计计算,利用植被结构生成软件Onyx tree professional重建梨树林场景,采用基于物理的光线追踪算法模拟相机拍摄的照片,提出了规则林地覆盖度照相法测量的采样方案,并通过计算机模拟检验了采样方案。通过精确控制模拟相机的拍摄条件,进一步分析了非垂直拍摄对测量精度的影响。结果表明,相机的非竖直拍摄对覆盖度计算结果的精度有较大的影响,误差最大可达27.9%。该文提出的测量方案为规则林地的覆盖度实地测量提供了参考。

关键词：遥感采样方案。计算机模拟覆盖度照相法

基于计算机模拟模型LESS的落叶松林木质元素影响分析

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遥感学报 2021年第5期25卷 1138-1151页

作者：许月谢东辉漆建波阎广建穆西晗张吴明北京师范大学地理科学学部遥感科学与工程研究院遥感科学国家重点实验室北京100875 北京林业大学省部共建森林培育与保护教育部重点实验室北京100083

目前大部分植被辐射传输模型在模拟太阳辐射与植被之间的相互作用过程时,将植物结构进行了简化,只保留了叶片的结构和空间分布特征,而忽略了木质元素(枝干等)对冠层反射特性的影响。计算机模拟模型LESS能够充分考虑植被的多种组分光谱... 详细信息

目前大部分植被辐射传输模型在模拟太阳辐射与植被之间的相互作用过程时,将植物结构进行了简化,只保留了叶片的结构和空间分布特征,而忽略了木质元素(枝干等)对冠层反射特性的影响。计算机模拟模型LESS能够充分考虑植被的多种组分光谱和结构特征,精确模拟植被冠层内部的光散射和辐射过程。本文以地面实测数据为基础,发展了以单木为基本单元的复杂森林三维场景重建基本流程;并在重建森林场景基础上,利用计算机模拟模型LESS模拟森林三维场景反射率,对比分析了森林木质元素对冠层反射率的影响。结果表明,忽略木质元素会引起植被冠层反射率模拟的偏差,特别是在近红外波段,在不同叶面积指数(LAI)下,其相对偏差都在40%以上。高空间分辨率是一个会突出木质元素影响的重要因素,随着空间分辨率提高,偏差也随之增大。不同等级枝干结构均对冠层反射率产生影响,即使忽略最小分枝也会引起17.7%(近红外)的估计误差。因此,在进行定量遥感研究中,必须考虑到忽略木质元素引起的偏差,即使是高LAI森林也无法忽视木质元素的影响。特别是在高分辨率遥感图像中,传统的以统计特征代替三维结构分布的辐射传输模型已经无法满足精度的要求。

关键词：辐射传输模型森林反射率木质元素三维重建 LESS

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月球卫星三线阵CCD影像模拟

北京师范大学学报（自然科学版） 2007年第3期43卷 298-302页

作者：李巧枝张吴明阎广建穆西晗北京师范大学地理学与遥感科学学院遥感科学国家重点实验室环境遥感与数字城市北京市重点实验室北京100875

讨论了由月球DEM和正射影像模拟月球卫星三线阵CCD立体影像的原理和方法,其中重点讨论了月球卫星三线阵传感器投影中心外方位元素模拟、模拟影像像元到月球DEM的投影点求解、考虑月球表面BRDF效应的影像灰度纠正三部分.本文在通常的基... 详细信息

讨论了由月球DEM和正射影像模拟月球卫星三线阵CCD立体影像的原理和方法,其中重点讨论了月球卫星三线阵传感器投影中心外方位元素模拟、模拟影像像元到月球DEM的投影点求解、考虑月球表面BRDF效应的影像灰度纠正三部分.本文在通常的基于共线方程的投影模拟方法的基础上考虑了月球表面的BRDF效应,对模拟影像进行了灰度纠正.模拟影像像元到DEM的投影点求解采用正算迭代方法,投影过程在月固坐标系下进行,进行长航带影像模拟时可减小月球曲率带来的投影误差.

关键词：月球影像模拟 BRDF效应三线阵CCD