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china's wetland change (1990-2000) determined by remote sensing

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science china Earth sciences 2010年第7期53卷 1036-1042页

作者： Peng Gong ZhenGuo Niu Xiao Cheng KuiYi Zhao DeMin Zhou JianHong Guo Lu Liang XiaoFeng Wang DanDan Li HuaBing Huang et al. 1. state key laboratory of remote sensing science jointly sponsored by Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China2. Institute of Northeast Geographical and Agricultural Ecology Research Chinese Academy of Sciences Changchun 130012 China3. Institute of Geographical Science and Resources Research Chinese Academy of Sciences Beijing 100101 China4. Beijing Yushi Lantu Information Technology Ltd. Beijing 100096 China

Two wetland maps for the entire china have been produced based on Landsat data acquired around 1990 and 2000. Wetlands in china have been divided into 3 broad categories with 15 sub-categories except rice fields. In 1990, the total wetland area in china was 355208 km2 whereas in 2000 it dropped to 304849 km2 with a net loss of 50360 km2. During an approximate 10-year period, inland wetland reduced from 318326 to 257922 km2, coastal wetland dropped from 14335 to 12015 km2, while artificial wetland increased from 22546 to 34911 km2. The greatest natural wetland loss occurred in Heilongjiang, Inner Mon- golia, and Jilin with a total loss of over 57000 km2 of wetland. In western china, over 13000 km2 of wetlands were newly formed in Xinjiang, Tibet, and Qinghai. About 12000 km2 of artificial wetlands were also added for fish farm and reservoir constructions. The newly formed wetlands in western china were caused primarily by climate warming over that region whereas the newly created artificial wetlands were caused by economic developments. china’s wetland loss is caused mainly by human activities.

关键词： wetland mapping natural wetland loss artificial wetland increase

Evaluation of nine machine learning methods for estimating daily land surface radiation budget from MODIS satellite data

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International Journal of Digital Earth 2022年第1期15卷 1784-1816页

作者： Shaopeng Li Bo Jiang Shunlin Liang Jianghai Peng Hui Liang Jiakun Han Xiuwan Yin Yunjun Yao Xiaotong Zhang Jie Cheng Xiang Zhao Qiang Liu Kun Jia The state key laboratory of remote sensing science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of SciencesBeijingPeople’s Republic of China beijing Engineering Research Center for Global Land remote sensing Products Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijingPeople’s Republic of China Department of Geographical sciences University of MarylandCollege ParkMDUSA beijing Engineering Research Center for Global Land remote sensing Products College of Global Change and Earth System ScienceBeijing Normal UniversityBeijingPeople’s Republic of China

The all-wave net radiation(Rn)at the land surface represents surface radiation budget and plays an important role in the Earth's energy and water *** studies have been conducted to estimate from satellite top-of-atmosphere(TOA)data using various methods,particularly the application of machine learning(ML)and deep learning(DL).However,few studies have been conducted to provide a comprehensive evaluation about various ML and DL methods in *** on extensive in situ measurements distributed at mid-low latitudes,the corresponding Moderate Resolution Imaging Spectroradiometer(MODIS)TOA observations,and the daily from the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)used as a priori knowledge,this study assessed nine models for daily estimation,including six classic ML methods(random forest-RF,adaptive boosting-Adaboost,extreme gradient boosting-XGBoost,multilayer perceptron-MLP,radial basis function neural network-RBF,and support vector machine-SVM)and three DL methods(multilayer perceptron neural network with stacked autoencoders-SAE,deep belief network-DBN and residual neural network-ResNet).The validation results showed that the three DL methods were generally better than the six ML methods except XGBoost,although they all performed poorly in certain conditions such as winter days,rugged terrain,and high *** had the most robust performance across different land cover types,elevations,seasons,and latitude zones,but it has disadvantages in practice because of its highly configurable implementation environment and low computational *** estimated daily values from all nine models were more accurate than the corresponding Global LAnd Surface Satellite(GLASS)product.

关键词： Net radiation energy balance mid-low latitude model comparison machine learning deep learning MODIS ERA5

New approach to calculating tree height at the regional scale

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Forest Ecosystems 2021年第2期8卷 311-329页

作者： Congrong Li Jinling Song Jindi Wang state key laboratory of remote sensing science Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of SciencesFaculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China key laboratory of Digital Earth science Aerospace Information Research institute Chinese Academy of SciencesNo.9 Dengzhuang South RoadBeijing 100094China

Background:Determining the spatial distribution of tree heights at the regional area scale is significant when performing forest above-ground biomass estimates in forest resource management *** geometric-optical mutual shadowing(GOMS)model can be used to invert the forest canopy structural parameters at the regional ***,this method can obtain only the ratios among the horizontal canopy diameter(CD),tree height,clear height,and vertical *** this paper,we used a semi-variance model to calculate the CD using high spatial resolution images and expanded this method to the regional *** then combined the CD results with the forest canopy structural parameter inversion results from the GOMS model to calculate tree heights at the regional ***:The semi-variance model can be used to calculate the CD at the regional scale that closely matches(mainly with in a range from-1 to 1 m)the CD derived from the canopy height model(CHM)*** difference between tree heights calculated by the GOMS model and the tree heights derived from the CHM data was small,with a root mean square error(RMSE)of 1.96 for a 500-m area with high fractional vegetation cover(FVC)(i.e.,forest area coverage index values greater than 0.8).Both the inaccuracy of the tree height derived from the CHM data and the unmatched spatial resolution of different datasets will influence the accuracy of the inverted tree *** the error caused by the unmatched spatial resolution is small in dense ***:The semi-variance model can be used to calculate the CD at the regional scale,together with the canopy structure parameters inverted by the GOMS model,the mean tree height at the regional scale can be *** study provides a new approach for calculating tree height and provides further directions for the application of the GOMS model.

关键词： Geometric-optical mutual shadowing(GOMS)model Semi-variance model Canopy diameter Tree height Regional scale

Vegetation NPP Distribution Based on MODIS Data and CASA Model——A Case Study of Northern Hebei Province

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chinese Geographical science 2006年第4期16卷 334-341页

作者： YUAN Jinguo NIU Zheng WANG Chenli state key laboratory of remote sensing science Institute of Remote Sensing Applications Chinese Academy of Sciences Belting 100101 China College of Resource and Environmental sciences Hebei Normal University Shifiazhuang 050016 China

Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer （MODIS） data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach （CASA） model. The spatial distribution of Absorbed Photosynthetically Active Radiation （APAR） of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation （FPAR） product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subreglons were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 10^6gC/（m^2.a）, and NPP in 2001 ranged from 2 to 608gC/（m^2-a）, with an average of 337.516gC/（m^2.a）. NPP of the study area in 2001 accumulated mainly from May to September （DOY 129-272）, high NIP values appeared from June to August （DOY 177-204）, and the maximum NPP appeared from late July to mid-August （DOY 209-224）.

关键词： NPP distribution MODIS data CASA model Northvrn Hebei Province

Photosynthetically active radiation retrieval based on HJ-1A/B satellite data

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science china Earth sciences 2010年第S1期53卷 81-91页

作者： LI Li1,XIN XiaoZhou1,SU GaoLi1,2 & LIU QinHuo1 1 state key laboratory of remote sensing science,institute of remote sensing applications,chinese academy of sciences,beijing 100101,china 2 Zhejiang Climate Center,Hangzhou 310017,china 1. state key laboratory of remote sensing science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China2. Zhejiang Climate Center Hangzhou 310017 China

Photosynthetically active radiation(PAR) is essential for plant photosynthesis and carbon cycle,and is also important for meteorological and environmental *** advance china's disaster and environmental monitoring capabilities,the HJ-1A/B satellites have been placed in Earth *** of their environmental monitoring objectives is the study of *** simulated direct solar,scattered and environment radiation between 400 and 700 nm under different atmospheric parameters(solar zenith angle,atmospheric water vapor,atmospheric ozone,aerosol optical thickness,surface elevation and surface albedo),and then established a look-up table between these input parameters and *** on the look-up table,we used HJ-1A/B aerosol and surface albedo outputs to derive the corresponding *** of inversed instantaneous and observed PAR values using HJ-1 Heihe experimental data had a root mean square error of 25.2 W m-2,with a relative error of 5.9%.The root mean square error for accumulated daily PAR and observed values was 0.49 MJ m-2,with a relative error of 3.5%.Our approach improved significantly the computational efficiency,compared with using directly radiation transfer *** also studied the sensitivity of various input parameters to photosynthetically active radiation,and found that solar zenith angle and atmospheric aerosols were sensitive PAR *** albedo had some effect on PAR,but water vapor and ozone had minimal impact on PAR.

关键词： Photosynthetically active radiation 6S HJ-1A/B satellites

Monitoring Glacier and Supra-glacier Lakes from Space in Mt. Qomolangma Region of the Himalayas on the Tibetan Plateau in china

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Journal of Mountain science 2009年第3期6卷 211-220页

作者： YE Qinghua ZHONG Zhenwei KANG Shichang Alfred Stein WEI Qiufang LIU Jingshi key laboratory of Tibetan Environment Changes and Land Surface Processes Institute of Tibetan Plateau Research Chinese Academy of Sciences (CAS) Beijing 100085 China state key laboratory of remote sensing science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China International institutefor Geo-Information science and Earth Observation (ITC) PO Box 67500 AA Enschede The Netherlands

Because of the large number and remoteness, satellite data, including microwave data and optical imagery, have commonly been used in alpine glaciers surveys. Using remote sensing and Geographical Information System （GIS） techniques, the paper presents the results of a multitemporal satellite glacier extent mapping and glacier changes by glacier sizes in the Mt. Qomolangma region at the northern slopes of the middle Himalayas over the Tibetan Plateau. Glaciers in this region have both retreated and advanced in the past 35 years, with retreat dominating. The glacier retreat area was 3.23 km2 （or o.75 km^2 yr^-1 during 1974 and 1976, 8.68 km^2 （or 0.36 km^2 yr^-1 during 1976 and 1992, 1.44 km^2 （or 0.12 km^2 yr^-1） during 1992-2ooo. 1.14 km^2 （or 0.22 km^2 yr^-1 during 2000-2003, and 0.52 km^2 （or 0.07 km^2 yr^-1 during 2003-2008, respectively. While supra-glacier lakes on the debris-terminus of the Rongbuk Glacier were enlarged dramatically at the same time, from 0.05 km^2 in 1974 increased to 0.71 km^2 in 2008, which was more than 13 times larger in the last 35 years. In addition, glacier changes also showed spatial differences, for example, glacier retreat rate was the fastest at glacier termini between 5400 and 5700 m a.s.l than at other elevations. The result also shows that glaciers in the middle Himalayas retreat almost at a same pace with those in the western Himalayas.

关键词： Glacier lake remote sensing Mr. Qomolangma region Himalayas Tibetan Plateau

Maize drought disaster risk assessment of china based on EPIC model

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International Journal of Digital Earth 2012年第6期5卷 488-515页

作者： Huicong Jia Jingai Wang Chunxiang Cao Donghua Pan Peijun Shi state key laboratory of remote sensing science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal UniversityBeijing 100101P.R.China key laboratory of Regional Geography College of Geography and Remote Sensing ScienceBeijing Normal UniversityBeijing 100875P.R.China National Disaster Reduction Center of china Ministry of Civil Affairs of the People?s Republic of ChinaBeijing 100124P.R.China state key laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875P.R.China

Digital Agriculture is one of the important applications of Digital *** the global climate changes and food security becomes an increasingly important issue,agriculture drought comes to the focus of *** is a typical monsoon climate country as well as an agricultural country with the world’s largest *** East Asian monsoon has had a tremendous impact upon agricultural ***,a maize drought disaster risk assessment,in line with the requirements of sustainable development of agriculture,is important for ensuring drought disaster reduction and food ***,soil,land use,and agro-meteorological observation information of the research area were collected,and based on the concept framework of‘hazard-inducing factors assessment(hazard)-vulnerability assessment of hazard-affected body(vulner-ability curve)-risk assessment(risk),’importing crop model EPIC(Erosion-Productivity Impact Calculator),using crop model simulation and digital mapping techniques,quantitative assessment of spatio-temporal distribution of maize drought in china was *** results showed that:in terms of 2,5,10,and 20 year return periods,the overall maize drought risk decreased gradually from northwest to southeast in the maize planting *** the 20 year return period,high risk value regions(drought loss rate]0.5)concentrate in the irrigated maize region of Northwest china,ecotone between agriculture and animal husbandry in Northern china,Hetao Irrigation Area,and north-central area of North china Plain,accounting for 6.41%of the total maize *** results can provide a scientific basis for the government’s decision-making in risk management and drought disaster prevention in china.

关键词： physical vulnerability risk assessment agriculture drought maize production EPIC model china Digital Earth GIS

Estimating surface evapotranspiration using combined MODIS and CBERS-02 data

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science china(Technological sciences) 2005年第S2期48卷 145-160页

作者： XIN Xiaozhou1,2, LIU Qinhuo1, TANG Yong1,3, TIAN Guoliang1, GU Xingfa1, LI Xiaowen1,2, ZHENG Hongsheng4 & CHEN Jiayi4 1. state key laboratory of remote sensing science, institute of remote sensing applications, chinese academy of sciences, beijing 100101, china 2. Research Center for remote sensing and GIS, Department of Geography, beijing normal university, beijing 100875, china 3. Graduate university of chinese academy of sciences, beijing 100039, china 4. Department of Atmospheric Physics, Peking university, beijing 100871, china 1. state key laboratory of remote sensing science Institute of Remote Sensing Applications Chinese Academy of Sciences 100101 Beijing China2. Research Center for Remote Sensing and GIS Department of Geography Beijing Normal University 100875 Beijing China3. Graduate University of Chinese Academy of Sciences 100039 Beijing China4. Department of Atmospheric Physics Peking University 100871 Beijing China

Spatial scale error is one of the most serious problems in the estimates of land surface heat fluxes of sensible and latent from satellite-borne data such as MODIS 1km resolution reflectance and emissive data. One of the feasible and economic ways to decrease the spatial scale error is to use high resolution land use class data together with the MODIS data. CBERS-02 data were used to produce land use class of Baiyangdian area, Hebei Province, china in the autumn of 2004. The area ratio of each class in MODIS pixel was calculated, and used to derive the heat fluxes of the mixed pixel. The results showed that the estimated heat fluxes of soil, sensible and latent have been changed remarkably after using the high resolution land class data. It could be concluded from the comparison between simulated and ground-measured fluxes as well as the theoretical analysis that high resolution land class data are useful to diminishing the scale error of heat fluxes estimated from low resolution satellite data.

关键词： surface evapotranspiration spatial scale error MODIS CBERS land class.

Desertification in the Mu Us Sandy Land in china:Response to climate change and human activity from 2000 to 2020

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Geography and Sustainability 2022年第2期3卷 177-189页

作者： Xin Wang Jinling Song Zhiqiang Xiao Jing Wang Fangze Hu state key laboratory of remote sensing science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of SciencesBeijing 100875China beijing Engineering Research Center for Global Land remote sensing Products Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China

china is a country largely affected by *** main purpose of this article is to analyze interannual and seasonal changes in fractional vegetation cover(FVC)in the Mu Us Sandy Land(MUSL).It uses fused remote sensing data to quantitatively analyze the response of FVC to climate change and human *** results showed that desertification in the MUSL had improved over the past 20 *** V desertification decreased from more than 60%in 2000 to about 15%in *** some years,degradation appeared to be affected by climate factors and human activity,especially in the northwestern portion of the study *** FVC in summer was slightly higher than that in autumn and far higher than recorded in spring and ***,the northwestern and central parts of the study area were unstable,with high coefficients of *** gradually increased from northwest to southeast,and areas with the fastest increase in FVC were concentrated along the eastern and southern edges of the study *** correlations between FVC and precipitation and dryness were slightly pos-itive,but the correlation between FVC and temperature showed regional *** increase of population density is not a key factor limiting the growth of vegetation;the policy of“grazing prohibition,grazing rest,and rotational grazing”has allowed the restoration of vegetation;and afforestation is an effective way to promote the increase in FVC.

关键词： Mu Us Sandy Land(MUSL) Mann-Kendall test STARFM model