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A long-term daily gridded snow depth dataset for the Northern Hemisphere from 1980 to 2019 based on machine learning

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Big Earth Data 2024年第2期8卷 274-301页

作者： Yanxing Hu Tao Che Liyun Dai Yu Zhu Lin Xiao Jie Deng Xin Li key laboratory of remote sensing of Gansu Province Heihe Remote Sensing Experimental Research StationNorthwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhouChina College of Resources and Environment University of Chinese Academy of SciencesBeijingChina state key laboratory of Tibetan Plateau Earth System Resources and Environment(TPESRE)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijingChina Yunnan key laboratory of International Rivers and Transboundary Eco-Security Institute of International Rivers and Eco-SecurityYunnan UniversityKunmingChina National Forestry and Grassland Administration key laboratory of Forest Resource Conservation and Ecological Safety on the Upper Reaches of the Yangtze River Sichuan Province Key Laboratory of Ecological Forestry Engineering on the Upper Reaches of the Yangtze RiverCollege of ForestrySichuan Agricultural UniversityChengduChina

A high-quality snow depth product is very import for cryospheric science and its related *** long time-series snow depth products covering the Northern Hemisphere can be divided into two categories:remote sensing snow depth products and reana-lysis snow depth ***,existing gridded snow depth products have some *** sensing-derived snow depth products are temporally and spatially discontinuous and tend to underestimate snow depth,while reanalysis snow depth products have coarse spatial resolutions and great *** overcome these problems,in our previous work we proposed a novel data fusion framework based on Random Forest Regression of snow products from Advanced Microwave Scanning Radiometer for the Earth Observing System(AMSR-E),Advanced Microwave Scanning Radiometer-2(AMSR2),Global Snow Monitoring for Climate Research(GlobSnow),the Northern Hemisphere Snow Depth(NHSD),ERA-Interim,and Modern-Era Retrospective Analysis for Research and applications,ver-sion 2(MERRA-2),incorporating geolocation(latitude and longitude),and topographic data(elevation),which were used as input indepen-dent *** than 30,000 ground observation sites were used as the dependent variable to train and validate the model in different time *** fusion framework resulted in a long time series of continuous daily snow depth product over the Northern Hemisphere with a spatial resolution of 0.25°.Here,we compared the fused snow depth and the original gridded snow depth products with 13,272 observation sites,showing an improved precision of our *** evaluation indices of the fused(best original)dataset yielded a coeffi-cient of determination R2 of 0.81(0.23),Root Mean Squared Error(RMSE)of 7.69(15.86)cm,and Mean Absolute Error(MAE)of 2.74(6.14)*** of the bias(88.31%)between the fused snow depth and in situ observations was in the range of−5 cm to 5 *** accuracy assessment of independent snow observation sites-Sodank

关键词： Snow depth datasets machine learning data fusion Northern Hemisphere

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Reconciled estimation of Antarctic ice sheet mass balance and contribution to global sea level change from 1996 to 2021

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science china Earth sciences 2024年第11期67卷 3562-3578页

作者： Rongxing LI Guojun LI Gang HAI Huan XIE Yuan CHENG Wei CHEN Xiangbin CUI Minghu DING Chunchun GAO Tong HAO Changqing KE Chuanjin LI Jin LI Yan LIU Jiangjun RAN Jiawen REN Qiang SHEN Yunzhong SHEN Hongling SHI Songyun WANG Zemin WANG Jingang ZHAN Baojun ZHANG Min ZHONG Chunxia ZHOU Center for Spatial Information science and Sustainable Development applications Tongji University College of Surveying and Geo-informatics Tongji University institute for the Conservation of Cultural Heritage School of Cultural Heritage and Information Management Shanghai University College of Resource Environment and Tourism Hubei University of Arts and Science Polar Research institute of china state key laboratory of Severe Weather Chinese Academy of Meteorological Sciences College of Geodesy and Geomatics Shandong University of Science and Technology School of Geography and Ocean science Nanjing University Shanghai Astronomical Observatory Chinese Academy of Sciences state key laboratory of remote sensing science Faculty of Geographical Science Beijing Normal University Department of Earth and Space sciences Southern University of Science and Technology state key laboratory of Cryospheric science Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences state key laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of Sciences Center for Space Research University of Texas at Austin chinese Antarctic Center of Surveying and Mapping Wuhan University School of Geospatial Engineering and science Sun Yat-sen University

The Antarctic Ice Sheet（AIS） has been losing ice mass and contributing to global sea level rise（GSLR）. Given its mass that is enough to cause ～58 m of GSLR, accurate estimation of mass balance trend is critical for AIS mass loss monitoring and sea level rise forecasting. Here, we present an improved approach to reconciled solutions of mass balance in AIS and its regions from multiple contributing solutions using the input-out, altimetric, and gravimetric methods. In comparison to previous methods, such as IMBIE 2018, this approach utilizes an adaptive data aggregation window to handle the heterogeneity of the contributing solutions, including the number of solutions, temporal distributions, uncertainties, and estimation techniques. We improved the regression-based method by using a two-step procedure that establishes ensembled solutions within each method（input-output, altimetry, or gravimetry） and then estimates the method-independent reconciled solutions. For the first time, 16contributing solutions from 8 chinese institutions are used to estimate the reconciled mass balance of AIS and its regions from1996 to 2021. Our results show that AIS has lost a total ice mass of ～3213±253 Gt during the period, an equivalent of～8.9±0.7 mm of GSLR. There is a sustained mass loss acceleration since 2006, from 88.1±3.6 Gt yr-1during 1996–2005 to 130.7 ±8.4 Gt yr-1during 2006–2013 and further to 157.0±9.0 Gt yr-1during 2014–2021. The mass loss signal in the West Antarctica and Antarctic Peninsula is dominant and clearly presented in the reconciled estimation and contributing solutions, regardless of estimation methods used and fluctuation of surface mass balance. Uncertainty and challenges remain in mass balance estimation in East Antarctica. This reconciled estimation approach can be extended and applied for improved mass balance estimation in the Greenland Ice Sheet and mountain glacier regions.

关键词： Antarctic Ice Sheet Ice mass loss acceleration Sea level rise Reconciled estimation

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Advances in Atmospheric Radiation:Theories,Models,and Their ***Ⅱ:Radiative Transfer Models and Related applications

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Journal of Meteorological Research 2024年第2期38卷 183-208页

作者： Hua ZHANG Feng ZHANG Lei LIU Yuzhi LIU Husi LETU Yuanjian YANG Zhengqiang LI Kun WU Shuai HU Ming LI Tie DAI Fei WANG Zhili WANG Yuxiang LING Yining SHI Chao LIU state key laboratory of Severe Weather and institute of Climate System Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing 210044 Department of Atmospheric and Oceanic sciences&institute of Atmospheric sciences Fudan UniversityShanghai 200438 College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073 College of Atmospheric sciences Lanzhou UniversityLanzhou 730000 state key laboratory of remote sensing science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101 School of Atmospheric Physics Nanjing University of Information Science&TechnologyNanjing 210044 School of Atmospheric sciences Nanjing University of Information Science&TechnologyNanjing 210044 institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029 CMA Earth System Modeling and Prediction Centre China Meteorological Administration(CMA)Beijing 100081

The subject of“atmospheric radiation”includes not only fundamental theories on atmospheric gaseous absorption and the scattering and radiative transfer of particles(molecules,cloud,and aerosols),but also their applications in weather,climate,and atmospheric remote sensing,and is an essential part of the atmospheric *** review includes two parts(Part I and PartⅡ);following the first part on gaseous absorption and particle scattering,this part(PartⅡ)reports the progress that has been made in radiative transfer theories,models,and their common applications,focusing particularly on the contributions from chinese *** recent achievements on radiative transfer models and methods developed for weather and climate studies and for atmospheric remote sensing are firstly ***,the associated applications,such as surface radiation estimation,satellite remote sensing algorithms,radiative parameterization for climate models,and radiative-forcing related climate change studies are summarized,which further reveals the importance of radiative transfer theories and models.

关键词： atmospheric radiation radiative transfer remote sensing radiative forcing climate change

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Lanthanide-based microlasers:Synthesis,structures,and biomedical applications

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Nano Research 2024年第1期17卷 97-111页

作者： Qian Zhang Yawei Liu Kai Liu Hongjie Zhang Engineering Research Center of Advanced Rare Earth Materials(Ministry of Education) Department of ChemistryTsinghua UniversityBeijing 100084China state key laboratory of Rare Earth Resource Utilization Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022China Xiangfu laboratory Jiaxing 314102China

The large size of lasers limits their applications in confined spaces,such as in biosensing and in vivo brain tissue *** this regard,micron-sized lasers have been *** exhibit great potential for biological detecting,remote sensing,and depth tracking due to their small sizes,sensitive properties of their spectral fingerprints,and flexible positional modulation in the ***-based luminescent materials that possess long excited-state lifetime,narrow emission bandwidth,and upconversion behaviors are promising as gain mediums for novel *** addition,lanthanide-based microlasers could be generated under natural ambient conditions with pumped or continuous light sources,which significantly promotes the practical applications of *** progress in the design,synthesis,and biomedical applications of lanthanide-based microlasers has been outlined in this *** ions doped and upconverted lanthanide-based microlasers are highlighted,which exhibit advantageous structures,miniaturized dimensions,and high lasing *** applications of lanthanide-based microlasers are further discussed,the upconverted microlasers show great advantages for biological applications owing to their tunable excitation and emission characteristics and excellent environmental ***,perspectives and challenges in the field of lanthanide-based microlasers are presented.

关键词： microlasers lanthanide-based luminescent materials upconversion nanoparticles biological applications

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Towards seamless environmental prediction-development of Pan-Eurasian EXperiment(PEEX)modelling platform

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Big Earth Data 2024年第2期8卷 189-230页

作者： Alexander Mahura Alexander Baklanov Risto Makkonen Michael Boy Tuukka Petäjä Hanna KLappalainen Roman Nuterman Veli-Matti Kerminen Stephen R.Arnold Markus Jochum Anatoly Shvidenko Igor Esau Mikhail Sofiev Andreas Stohl Tuula Aalto Jianhui Bai Chuchu Chen Yafang Cheng Oxana Drofa Mei Huang Leena Järvi Harri Kokkola Rostislav Kouznetsov Tingting Li Piero Malguzzi Sarah Monks Mads Bruun Poulsen Steffen M.Noe Yuliia Palamarchuk Benjamin Foreback Petri Clusiu Till Andreas Soya Rasmussen Jun She Jens Havskov Sørensen Dominick Spracklen Hang Su Juha Tonttila Siwen Wang Jiandong Wang Tobias Wolf-Grosse Yongqiang Yu Qing Zhang Wei Zhang Wen Zhang Xunhua Zheng Siqi Li Yong Li Putian Zhou Markku Kulmala Faculty of science Institute for Atmospheric and Earth System Research(INAR)/PhysicsUniversity of Helsinki(UHEL)HelsinkiFinland science and Innovation Department World Meteorological Organization(WMO)GenevaSwitzerland Niels Bohr institute University of CopenhagenCopenhagenDenmark Climate System Research Finnish Meteorological Institute(CSR-FMI)HelsinkiFinland School of Engineering sciences Lappeenranta University of TechnologyLappeenrantaFinland institute for Climate and Atmospheric science School of Earth and EnvironmentUniversity of LeedsLeedsUK Biodiversity and Natural Resources Program International Institute for Applied Systems Analysis(IIASA)LaxenburgAustria Department of Physics and Technology UiT-The Arctic University of NorwayTromsoNorway Nansen Environmental and remote sensing Center(NERSC) BergenNorway Atmospheric Composition Finnish Meteorological Institute(AC-FMI)HelsinkiFinland Norwegian institute for Air Research(NILU) KjellerNorway LAGEO Institute of Atmospheric PhysicsChinese Academy of Sciences(IAP-CAS)BeijingChina Max Planck institute for Chemistry(MPI-Chem) MainzGermany institute of Atmospheric sciences and Climate National Research Council of Italy(CNR-15SAC)BolognaItaly institute of Geographic sciences and Natural Resources Research(IGSNRR) Chinese Academy of Sciences(CAS)BeijingChina Faculty of science Helsinki Institute of Sustainability Science(HELSUS)University of Helsinki(UHEL)HelsinkiFinland Atmospheric Research Centre of Eastern Finland Finnish Meteorological Institute(ARCEF-FMI)KuopioFinland institute of Atmospheric Physics Chinese Academy of Sciences(IAP-CAS)BeijingChina Department of Plant Physiology Estonian University of Life Sciences(EULS)Institute of Agricultural and Environmental Sciences(IAES)TartuEstonia Danish Meteorological institute(DMI) CopenhagenDenmark state key laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry LAPC) Institute of Atmospheric Physics(IAP)Chinese Academy of Sciences(CAS)BeijingChina Uni

The Pan-Eurasian Experiment Modelling Platform(PEEX-MP)is one of the key blocks of the PEEX Research *** PEEX MP has more than 30 models and is directed towards seamless envir-onmental *** main focus area is the Arctic-boreal regions and *** models used in PEEX-MP cover several main components of the Earth’s system,such as the atmosphere,hydrosphere,pedosphere and biosphere,and resolve the physicalchemicalbiological processes at different spatial and temporal scales and *** paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system,online integrated,forward/inverse,and socioeconomical modelling,and other approaches with a particular focus on applications in the PEEX geographical *** employed high-performance com-puting facilities,capabilities,and PEEX dataflow for modelling results are *** virtual research platforms(PEEXView,Virtual Research Environment,Web-based Atlas)for handling PEEX modelling and observational results are *** over-all approach allows us to understand better physical-chemicalbiological processes,Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks,impact,consequences,*** population,envir-onment and climate in the PEEX *** work was also one of the last projects of *** Zilitinkevich,who passed away on 15 February *** the finalization took time,the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.

关键词： Multi-scale and-processes modelling concept seamless coupling high-performance computing data infrastructure virtual research platforms

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Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

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Advances in Atmospheric sciences 2024年第8期41卷 1511-1526页

作者： Shengping HE Helge DRANGE Tore FUREVIK Huijun WANG Ke FAN Lise Seland GRAFF Yvan J.ORSOLINI Geophysical institute University of Bergen and Bjerknes Centre for Climate ResearchBergen 5020Norway Nansen Environmental and remote sensing Center Bergen 5007Norway key laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing 211544China Nansen-Zhu International Research Center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Southern Marine science and Engineering Guangdong laboratory(Zhuhai) Zhuhai 511458China School of Atmospheric science Sun Yat-Sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Norwegian Meteorological institute Oslo 0313Norway Norwegian institute for Air Research Kjeller 2007Norway

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

关键词： Arctic sea ice loss warm Arctic–cold East Asia atmospheric internal variability large-ensemble simulation NorESM2 PAMIP

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Modeling glacio-hydrological processes in the Himalayas:A review and future perspectives

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Geography and Sustainability 2024年第2期5卷 179-192页

作者： Lei Wang Hu Liu Ranjeet Bhlon Deliang Chen Junshui Long Tenzing C.Sherpa state key laboratory of Tibetan Plateau Earth System Environment and Resources(TPESER)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China university of chinese academy of sciences Beijing 100049China Regional Climate Group Department of Earth SciencesUniversity of GothenburgGothenburgS-40530(Box 460)Sweden International Centre for Integrated Mountain Development Lalitpur 44700Nepal

The Himalayas and their surrounding areas boast vast glaciers rivaling those in polar regions,supplying vital meltwater to the Indus,Ganges,and Brahmaputra rivers,supporting over a billion downstream inhabitants for drinking,power,and *** changing runoff patterns due to accelerated glacial melt,understanding and projecting glacio-hydrological processes in these basins is *** review assesses the evolution,applications,and key challenges in diverse glacio-hydrology models across the Himalayas,varying in complexities like ablation algorithms,glacier dynamics,ice avalanches,and *** findings indicate higher glacial melt contributions to annual runoff in the Indus compared to the Ganges and Brahmaputra,with anticipated peak melting in the latter basins—having less glacier cover—before the mid-21st century,contrasting with the delayed peak expected in the Indus Basin due to its larger glacier *** modeling studies still have large uncertainties in the simulated runoff components in the Himalayan basins;and the projections of future glacier melt peak time vary at different Himalaya sub-basins under different Coupled Model Intercomparison Project(CMIP)*** also find that the lack of reliable meteorological forcing data(particularly the precipitation errors)is a major source of uncertainty for glacio-hydrological modeling in the Himalayan ***,permafrost degradation compounds these challenges,complicating assessments of future freshwater *** measures include establishing comprehensive in situ observations,innovating remote-sensing technologies(especially for permafrost ice monitoring),and advancing glacio-hydrology models to integrate glacier,snow,and permafrost *** endeavors are crucial for informed policymaking and sustainable resource management in this pivotal,glacier-dependent ecosystem.

关键词： Glacio-hydrology Modeling Himalayas Glacier,snow,and permafrost Sustainable development

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Scale effects of leaf area index inversion based on environmental and disaster monitoring satellite data

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science china Earth sciences 2010年第S1期53卷 92-98页

作者： ZHANG Hao1,LI XiaoWen1,2,CAO ChunXiang1,YANG Hua2,GAO MengXu1,3,ZHENG Sheng1,3,XU Min1,3,XIE DongHui2,JIA HuiCong1,JI Wei1,ZHAO Jian1,3,CHEN Wei1,3 & NI XiLiang1,3 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,china 2 state key laboratory of remote sensing science,jointly sponsored by beijing normal university and institute of remote sensing applications of chinese academy of sciences,beijing 100875,china 3 Graduate university of chinese academy of sciences,beijing 100049,china 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. State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications of Chinese Academy of Sciences Beijing 100875 China3. Graduate University of Chinese Academy of Sciences Beijing 100049 China

The spatial distribution of sub-pixel components has an impact on retrieval accuracy,and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index(LAI).To investigate this effect,we constructed three realistic scenarios with the same LAI values and other properties,except that the simulated plants had different *** implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor(BRF) datasets based upon these simulated *** inversion was conducted using these data,which showed that spatial distribution affects retrieval *** inversion was also conducted for LAI based on charge-coupled device(CCD) data from the Environment and Disaster Monitor Satellite(HJ-1),which depicted both forest and drought-resistant crop land *** showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI *** spatial distribution of global fractal dimension index,which can be used to describe the area of sub-pixel components and their spatial distribution modes,shows good consistency with the coarse resolution LAI inversion error.

关键词： HJ-1 leaf area index scale effect spatial distribution

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Loose architecture of multi-level massive geospatial data based on virtual quadtree

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science china(Technological sciences) 2008年第S1期51卷 114-123页

作者： YANG ChongJun,WU Sheng,REN YingChao,FU Li,ZHANG FuQing,WANG Gang,TAN Jian,LIU DongLin,MA ChaoJi & LIANG Li 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 1. 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

This paper proposed a virtual quadtree (VQT) based loose architecture of multi-level massive geospatial data for integrating massive geospatial data dispersed in the departments of different hierarchies in the same sector into a unified GIS (Geographic Information System) platform. By virtualizing the nodes of the quad-tree,the VQT separates the structure of data organization from data storage,and screens the difference between the data storage in local computer and in the re-mote computers in network environment. And by mounting,VQT easily integrates the data from the remote computers into the local VQT so as to implement seam-less integration of distributed multi-level massive geospatial data. Based on that mode,the paper built an application system with geospatial data over 1200 GB distributed in 12 servers deployed in 12 cities. The experiment showed that all data can be seamlessly rapidly traveled and performed zooming in and zooming out smoothly.

关键词： massive geospatial data virtual quadtree loose architecture

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Human Settlement Evaluation in Mountain Areas Based on remote sensing,GIS and Ecological Niche Modeling

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Journal of Mountain science 2013年第3期10卷 378-387页

作者： ZHAO Jian XU Min LU Shi-lei CAO Chun-xiang 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 Graduate School of chinese academy of sciences

The Qinghai-Tibet Plateau is the word＇s highest and largest plateau. Due to increasing demands for environment exploration and tourism, a large transitional area is required for altitude adaptation. Hehuang valley, which locates in the transition zone between the Loess Plateau and the Qinghai-Tibet Plateau, has convenient transportation and relatively low elevation. Our question is whether the geographic conditions here are appropriate for adapted stay before going into the Qinghai-Tibet Plateau. Therefore, in this study, we examined the potential use of ecological niche modeling （ENM） for mapping current and potential distribution patterns of human settlements. We chose the Maximum Entropy Method （Maxent）, an ENM which integrates climate, remote sensing and geographical data, to model distributions and assess land suitability for transition areas. After preprocessing and selection, the correlation between variables and spatial auto- correlation input data were removed and 106 occurrence points and 9 environmental layers were determined as the model inputs. The threshold- independent model performance was reasonable according to lO times model running, with the area under the curve （AUC） values being 0.917± 0.01, and 0.923±0.002 for test data. Cohen＇s kappa coefficient of model performance was 0.848. Results showed that 82.22% of the study extent was not suitable for human settlement. Of the remaining areas, highly suitable areas aceounted for 1.19%, moderately for 5.3% and marginally for 11.28%. These suitable areas totaled 418.79 km2, and 86.25% of the sample data was identified in the different gradient of suitable *** decisive environmental factors were slope and two climate variables： mean diurnal temperature range and temperature seasonality. Our model showed a good performance in mapping and assessing human settlements. This study provides the first predicted potential habitat distribution map for human settlement in Ledu County, which could also help in

关键词： Human settlement remote sensing Suitability assessment Ecological niche modeling

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