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Active High-Locality Landslides in Mao County: Early Identification and Deformational Rules

Journal of Earth Science 2023年第5期34卷 1596-1615页

作者： Xianmin Wang Jing Yin Menghan Luo Haifeng Ren Jing Li Lizhe Wang Dongdong Li Guojun Li Hubei Subsurface Multi-Scale Imaging Key Laboratory School of Geophysics and GeomaticsChina University of GeosciencesWuhan 430074China Changsha Planning Information Service Center Changsha Municipal Bureau of Natual Resources and PlanningChangsha 410221China National Engineering Research Center for geoinformatics Aerospace Information Research InstituteChinese Academy of SciencesChinese Academy of SciencesBeijing 100101China College of Electronic Science and Engineering National University of Defense TechnologyChangsha 410073China Laboratory of Beyond LOS Reliable Information Transmission Chongqing University of Posts and TelecommunicationsChongqing 400065China

High-locality landslides are located on slopes at high elevations and are characterized by long sliding distances, large gravitational potential energy, high movement velocities, tremendous kinetic energy, and sudden onset. Thus, they often cause catastrophic damage to human lives and engineering facilities. It is of great significance to identify active high-locality landslides in their early deformational stages and to reveal their deformational rules for effective disaster mitigation. Due to alpinecanyon landforms, Mao County is a representative source of high-locality landslides. This work employs multisource data(geological, terrain, meteorological, ground sensor, and remote sensing data) and timeseries In SAR technology to recognize active high-locality landslides in Mao County and to reveal their laws of development. Some new viewpoints are suggested.(1) Nineteen active high-locality landslides are identified by the time-series In SAR technique, of which 7 are newly discovered in this work. All these high-locality landslides possessed good concealment during their early deformational stages. The newly discovered HL-16 landslide featured a large scale and a great slope height, posing a large threat to the surrounding buildings and residents.(2) The high-locality landslides in Mao County were mainly triggered by three factors: earthquakes, precipitation, and road construction.(3) Three typical high-locality landslides that were triggered by different factors are highlighted with their deformational rules under the functions of steep terrain, shattered rocks, fissure-water penetration, precipitation, and road construction. This work may provide clues to the prevention and control of high-locality landslides and can be applied to the determination of active high-locality landslides in other hard-hit areas.

关键词： high-locality landslide landslide identification deformational rule landslides engineering geology

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Spatial and Temporal Variation in Climate Trends in the Kyoga Plains of Uganda: Analysis of Meteorological Data and Farmers’ Perception

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Journal of Geoscience and Environment Protection 2020年第1期8卷 46-71页

作者： Oketcho Chombo Shuaib Lwasa Moses Tenywa Department of Geography Geoinformatics and Climate Sciences School of Forestry Environmental and Geographical Sciences Col-lege of Agriculture and Environmental Sciences Makerere University Kampala Uganda Department of Agricultural Production School of Agricultural Sciences College of Agriculture and Environmental Sciences Makerere University Kampala Uganda

With global warming now a certainty, it’s important to investigate climate change elements at the local level so as to enable stake holders adapt in order to sustain their livelihoods. This study investigated local climate changes, farmers’ perception of the changes and factors affecting perception to climate change in the Kyoga plains of Uganda. Monthly maximum temperature, minimum temperature and total rainfall from four meteorological stations within the study area for period 1984-2014 were obtained to analyse seasonal, annual and decadal trends in rainfall and temperature while a survey based on 384 randomly selected farmers was carried out to investigate the perception of variation in climate change trends among small holder farmers of different socioeconomic characteristics across the Kyoga plains. Multi stage random sampling was applied in the selection of the population sample. Non parametric analysis (Mann Kendall test) was used for analyzing trends and testing significance. In the survey, farmers were asked their observations about the local climate using structured questionnaires and these were analysed using descriptive statics. Logistics regression was then used to identify the factors that determined the perceptions of farmers on climate change. Overall, trends in monthly temperature are increasing over the years but not significantly while rainfall is decreasing but equally not significantly. Seasonal and decadal temperature had significant positive trends at different stations and sub zones over the years. 67% of the farmers realised a decrease in rainfall while 56.8% perceived an increase in temperature across the agroecological zone. 56.3% perceived declining rainfall and 52% realized increasing temperature in the southern sub zone while 42% realised a decrease in rainfall and 40.6%, an increase in temperature in the northern sub zone. Belonging to a group and age has significant positive effect on farmers’ perception of climate while farming exper

关键词： Climate Change Small Holder Farmers Spatial Differentiation Perception

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Towards an integrative approach to evaluate the environmental ecosystem services provided by urban forest

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Journal of Forestry Research 2019年第6期30卷 1981-1996页

作者： Samson Roeland Marco Moretti Jorge Humberto Amorim Cristina Branquinho Silvano Fares Federico Morelli Ulo Niinemets Elena Paoletti Pedro Pinho Gregorio Sgrigna Vladimir Stojanovski Abhishek Tiwary Pierre Sicard Carlo Calfapietra Department of Bioscience Engineering Research Group Environmental Ecology and Applied MicrobiologyLaboratory of Environmental and Urban EcologyUniversity of AntwerpAntwerpBelgium Institute of Research on Terrestrial Ecosystems(IRET) CNRHeadquartersVia Marconi 2PoranoItaly Forest Faculty in Skopje University SS Cyril and Methodius1000 SkopjeMacedonia Faculty of Engineering and the Environment University of SouthamptonHighfieldSouthampton SO17 1BJUK ARGANS 260 Route du Pin Montard06904 Sophia AntipolisFrance Department of Landscape Design and Sustainable Ecosystems Agrarian-technological InstituteRUDN UniversityMiklukho-Maklaya Str.6MoscowRussia 117198 Swiss Federal Research Institute WSL Biodiversity and Conservation BiologyZu¨rcherstrasse 1118903 BirmensdorfSwitzerland Swedish Meteorological and Hydrological Institute(SMHI) SE-60176 Norrko¨pingSweden Faculdade de Cieecias cE3c-Centre for EcologyEvolution and Environmental ChangesUniversidade de LisboaCampo GrandeLisbon 1749-016Portugal Council for Agricultural Research and Economics(CREA) Research Center for Forestry and WoodArezzoItaly Department of applied geoinformatics and Spatial Planning Faculty of Environmental SciencesCzech University of Life Sciences PragueKamy′cka′129165 00 Prague 6Czech Republic Institute of Agricultural and Environmental Sciences Estonian University of Life SciencesKreutzwaldi 1Tartu 51014Estonia Institute of Research on Terrestrial Ecosystems(IRET) CNRSection of FlorenceVia Madonna del Piano 10Sesto FiorentinoItaly Centre for Natural Resources and the Environment Instituto Superior Te′cnicoUniversity of LisbonLisbon 1749-016Portugal

As a Nature-Based Solution,urban forests deliver a number of environmental ecosystem services(EESs).To quantify these EESs,well-defined,reliable,quantifiable and stable indicators are *** literature analysis and expert knowledge gathered within COST Action FP1204 GreenInUrbs,we proposed a classification of urban forest EESs into three categories:(A)regulation of air,water,soil and climate;(B)provisioning of habitat quality;and(C)provisioning of other goods and *** category is divided into EES types:(a)amelioration of air quality;restoration of soil and water;amelioration of the microclimate;removal of CO2 from the air;(b)provision of habitat for biodiversity;support for resilient urban ecosystems;provision of genetic diversity;and(c)provision of energy and nutrients;provision of grey infrastructure *** EES type provides one or more *** each of these 12 benefits,we propose a set of indicators to be used when analyzing the impacts on the identified *** half of the 36 indicators are relevant to more than one single benefit,which highlights complex *** indicators of wider applicability are tree and stand characteristics,followed by leaf physical traits and tree species *** knowledge is needed for the optimization of the EESs delivered by urban forests,now and in the future.

关键词： Urban forests Environmental ecosystem services Indicators

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Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

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Geoscience Frontiers 2021年第2期12卷 505-519页

作者： Phuong Thao Thi Ngo Mahdi Panahi Khabat Khosravi Omid Ghorbanzadeh Narges Kariminejad Artemi Cerda Saro Lee Institute of Research and Development Duy Tan UniversityDa Nang550000Viet Nam Division of Science Education Kangwon National UniversityChuncheon-siGangwon-do24341Republic of Korea Geoscience Platform Division Korea Institute of Geoscience and Mineral Resources(KIGAM)124Gwahak-ro Yuseong-guDaejeon34132Republic of Korea Department of Watershed Management Engineering Sari Agricultural Science and Natural Resources UniversitySariIran Department of geoinformatics–Z_GIS University of SalzburgSalzburg5020Austria Department of Watershed and Arid Zone Management Gorgan University of Agricultural Sciences and Natural ResourcesGorgan49189-434Iran Soil Erosion and Desertification Research Group Department of GeographyUniversity of ValenciaValenciaSpain Department of Geophysical Exploration Korea University of Science and Technology217 Gajeong-ro Yuseong-guDaejeon34113Republic of Korea

The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related *** this study,we applied two novel deep learning algorithms,the recurrent neural network(RNN)and convolutional neural network(CNN),for national-scale landslide susceptibility mapping of *** prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors(altitude,slope degree,profile curvature,distance to river,aspect,plan curvature,distance to road,distance to fault,rainfall,geology and land-sue)to construct a geospatial database and divided the data into the training and the testing *** then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training *** calculated the receiver operating characteristic(ROC)curve and used the area under the curve(AUC)for the quantitative evaluation of the landslide susceptibility maps using the testing *** performance in both the training and testing phases was provided by the RNN algorithm(AUC=0.88)than by the CNN algorithm(AUC=0.85).Finally,we calculated areas of susceptibility for each province and found that 6%and 14%of the land area of Iran is very highly and highly susceptible to future landslide events,respectively,with the highest susceptibility in Chaharmahal and Bakhtiari Province(33.8%).About 31%of cities of Iran are located in areas with high and very high landslide *** results of the present study will be useful for the development of landslide hazard mitigation strategies.

关键词： CNN RNN Deep learning Landslide Iran

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Development of a sample preparation approach to measure the size of nanoparticle aggregates by electron microscopy

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Particuology 2019年第4期17卷 49-57页

作者： Agnieszka Dudkiewicz Angela Lehner Qasim Chaudhry Kristian Molhave Guenter Allmaier Karen Tiede Alistair B.A. Boxall Peter Hofmann John Lewis The Food and Environment Research Agency Sand Hutton York Y041 1LZ UK Department of Environment The University of York Heslington York YO10 5DD UK National Centre for Food Manufacturing The University of Lincoln Holbeach PE12 7AG UK Research Group Bio- and Polymer Analysis Institute of Chemical Technologies and Analytics TU Wien (Vienna University of Technology) Getreidemarkt 9 A-1060 Vienna Austria University of Chester Parkgate Road Chester CH1 4BJ UK Department of Micro and Nanotechnology Technical University of Denmark DTU Bldg 345b Lyngby 2800 Denmark Research Centre for Global Food Security and Ecosystems University of Hohenheim Wollgrasweg 43 70155 Stuttgart Germany Department of geoinformatics - Z.GIS University of Salzburg Schillerstr. 30 A-5020 Salzburg Austria

Electron microscopy (EM) is widely used for nanoparticle (NP) sizing. Following an initial assessment of two sample preparation protocols described in the current literature as"unperturbed", we found that neither could accurately measure the size of NPs featuring a broad size distribution, e.g., aggregates. Because many real-world NP samples consist of aggregates, this finding was of considerable concern. The data showed that the protocols introduced errors into the measurement by either inducing agglomeration artefacts or providing a skewed size distribution towards small particles (skewing artefact). The focus of this work was to develop and apply a mathematical refinement to correct the skewing artefact. This refinement provided a much improved agreement between EM and a reference methodology, when applied to the measurement of synthetic amorphous silica NPs. Further investigation, highlighted the influence of NP chemistry on the refinement. This study emphasised the urgent need for greater and more detailed consideration regarding the sample preparation of NP aggregates to routinely achieve accurate measurements by EM. This study also provided a novel refinement solution applicable to the size characterisation of silica and c让rate-coated gold NPs featuring broad size distributions. With further research, this approach could be extended to other NP types.

关键词： Nanoparticles Aggregates Measurement Electron microscopy Sample preparation Artefacts

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An Integrated Method for the Selection of Optimum Locations for Landfilling Utilizing GIS: A Case Study of the State of Kuwait

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Journal of Environmental Protection 2019年第2期10卷 260-275页

作者： Meshal Mohammad Abdullah Sabah Al-Jenaid Waleed Khalil Zubari Jasem Al-Ali Department of Ecosystem Science and Management Texas A&M University College Station TX USA Natural Environmental Systems and Technology (NEST) Research Group EcoLife Science Research and Consultation Hawally Kuwait geoinformatics Department College of Graduate Studies Arabian Gulf University Manama Bahrain Water Resources Management Program College of Graduate Studies Arabian Gulf University Manama Bahrain Geography Department College of Social Science Kuwait University Shuwaikh Kuwait

With the rise of urbanization, change in lifestyles, and food habits, the amount of Municipal Solid Waste (MSW) has been rapidly increasing with the composition constantly changing. Landfilling is the common approach for waste management in Kuwait, and around 90% of municipal wastes are disposed in landfill sites. Therefore, this study focused on the integration of different methods for the process of allocating optimum sites for MSW landfills, in four main stages. The first stage focused on utilizing the gap analysis method for the identification of effective criteria for landfill site selection, by comparing the criteria in Kuwait with the World Bank guidelines, US EPA, and Australia EPA, to suggest the best criteria for landfill site selection. These criteria were applied in the second and third stages to determine suitable locations for landfill sites using the Geographical Information System (GIS). In the last stage, the suitable areas were evaluated by studying the socioeconomic aspects such as distance to waste generation center, the proximity of existing roads, and lifespan to select optimum locations for landfilling. The results indicated that only one site with a total area of 12 km2 was considered optimum for MSW landfill sites in Kuwait. Therefore, moderate suitability areas were indicated to support and provide decision makers with more options. The moderately suitable sites are also suitable for landfilling, but they need to be designed carefully in order to avoid negative impacts on the environment and human health. Therefore, we conclude that there is an urgent need to apply the integrated waste management system in Kuwait, as well as to develop a long-term strategic plan.

关键词： Municipal Solid Waste ModelBuilder Gape Analysis Spatial Analysis Waste Management

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Geographic information science in the era of geospatial big data: A cyberspace perspective

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The Innovation 2022年第5期3卷 21-22页

作者： Xintao Liu Min Chen Christophe Claramunt Michael Batty Mei-Po Kwan Ahmad MSenousi Tao Cheng Josef Strobl Arzu Cöltekin John Wilson Temenoujka Bandrova Milan Konecny Paul MTorrens Fengyuan Zhang Li He Jinfeng Wang Carlo Ratti Olaf Kolditz Alexander Klippel Songnian Li Hui Lin Guonian Lu Department of Land Surveying and Geo-Informatics Hong Kong Polytechnic UniversityHong Kong SARKowloonChina Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China The French Naval Academy Research Institute 29240 Lanveoc-PoulmicFrance The Bartlett Centre for Advanced Spatial Analysis(CASA) University College London(UCL)WC1E 6BT LondonUK Institute of Space and Earth Information Science The Chinese University of Hong KongHong Kong SARShatin 999077China Department of Civil Engineering Cairo University12613 CairoEgypt SpaceTimeLab Department of CivilEnvironmental and Geomatic EngineeringUniversity College London(UCL)WC1E 6BT LondonUK Department of geoinformatics University of Salzburg5020 SalzburgAustria Institute of Interactive Technologies(IIT) University of Applied Sciences and Arts Northwestern Switzerland FHNW5210 WindischSwitzerland Spatial Sciences Institute University of Southern CaliforniaLos AngelesCA 90007USA Laboratory on Cartography Department of Photogrammetry and CartographyUniversity of ArchitectureCivil Engineering and Geodesy1164 SofiaBulgaria Laboratory on geoinformatics and Cartography Department of GeographyMasaryk University61137 BrnoCeskáRepublika Computer Science and Engineering Tandon School&Center for Urban Science+ProgressNew York UniversityNew YorkNY 10012USA School of Humanities and Social Science Xi’an Jiaotong UniversityXi’an 710049China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of SciencesBeijing 100101China Department of Urban Studies and Planning Massachusetts Institute of TechnologyCambridgeMA 02139USA Centre for Environmental Research Helmholtz Centre for Environmental Research-UFZ04318 LeipzigGermany Laboratory of Geo-information Science and Remote Sensing Wageningen University&ResearchWageningen 6708the Netherlands Department of Civil Engineering Toronto Metropolitan UniversityTorontoON M5B 2K3Canada School of Geography and Env

The advent of information and communication technology and the Internet of Things have led our society toward a digital *** proliferation of personal computers,smartphones,intelligent autonomous sensors,and pervasive network interactions with individuals have gradually shifted human activities from offline to online and from in person to *** transformation has brought a series of challenges in a variety of fields,such as the dilemma of placelessness,some aspects of timelessness(no time relevance),and the changing relevance of distance in the field of geographic information science(GIScience).In the last two decades,“cyber thinking”in GIScience has received significant attention from different *** instance,human activities in“cyberspace”need to be reconsidered when coupled with the geographic space to observe the first law of geography.

关键词： computer cyber instance

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Challenges and strategies for the visual exploration of complex environmental data

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International Journal of Digital Earth 2017年第10期10卷 1070-1076页

作者： Carolin Helbig Doris Dransch Michael Böttinger Colin Devey Antonie Haas Mario Hlawitschka Claudia Kuenzer Karsten Rink Christian Schäfer-Neth Gerik Scheuermann Tom Kwasnitschka Andrea Unger Helmholtz Centre for Environmental Research(UFZ) LeipzigGermany German Research Centre for Geosciences(GFZ) PotsdamGermany German Climate Computing Centre(DKRZ) HamburgGermany Helmholtz Centre for Ocean Research Kiel(GEOMAR) KielGermany Helmholtz Centre for Polar and Marine Research(AWI) BremerhavenGermany Faculty of Computer Science Mathematics and Natural SciencesLeipzig University of Applied Sciences(HTWK)LeipzigGermany German Aerospace Centre(DLR) OberpfaffenhofenGermany Institute of Computer Science Leipzig UniversityLeipzigGermany

In this opinion paper,we,a group of scientists from environmental-,geo-,ocean-and information science,argue visual data exploration should become a common analytics approach in Earth system science due to its potential for analysis and interpretation of large and complex spatio-temporal *** discuss the challenges that appear such as synthesis of heterogeneous data from various sources,reducing the amount of information and facilitating multidisciplinary,collaborative *** argue that to fully exploit the potential of visual data exploration,several bottlenecks and challenges have to be addressed:providing an efficient data management and an integrated modular workflow,developing and applying suitable visual exploration concepts and methods with the help of effective and tailored tools as well as generating and raising the awareness of visual data exploration and *** are convinced visual data exploration is worth the effort since it significantly facilitates insight into environmental data and derivation of knowledge from it.

关键词： Digital Earth geoinformatics geospatial data integration visualization

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可持续发展情景下丝绸之路沿线国家土地利用及其对陆地碳库影响

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Science Bulletin 2023年第7期68卷 740-749页

作者：曹敏田雅吴凯陈旻陈玉胡雪孙中昶左丽君林键骆磊朱瑞许振赐 Temenoujka Bandrova Milan Konecny 袁文平郭华东林珲闾国年 Key Laboratory of Virtual Geographic Environment Ministry of EducationNanjing Normal UniversityNanjing 210023China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China School of Geography and Environment Jiangxi Normal UniversityNanchang 330022China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China The Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034China Sierra Nevada Research Institute University of CaliforniaMerced CA 95348USA Institute of High Performance Computing Agency for ScienceTechnology and ResearchSingapore 138632Singapore Department of Geography the University of Hong KongHong Kong 999077China Laboratory on Cartography University of ArchitectureCivil Engineering and GeodesySofia 1164Bulgaria Laboratory on geoinformatics and Cartography Institute of GeographyMasaryk UniversityBrno 60177Czech Republic School of Atmospheric Sciences Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Sun Yat-sen UniversityZhuhai 519082China Key Laboratory of Poyang Lake Wetland and Watershed Research Ministry of EducationJiangxi Normal UniversityNanchang 330022China

可持续发展目标(SDGs)呼吁全世界共同采取行动,促进繁荣并保护地球.本研究面向SDGs构建了环境、粮食和经济等可持续发展情景,预测2020~2030年丝绸之路沿线国家的土地利用变化,并分析其对陆地碳库的影响。研究表明:未来土地利用变化及其... 详细信息

可持续发展目标(SDGs)呼吁全世界共同采取行动,促进繁荣并保护地球.本研究面向SDGs构建了环境、粮食和经济等可持续发展情景,预测2020~2030年丝绸之路沿线国家的土地利用变化,并分析其对陆地碳库的影响。研究表明:未来土地利用变化及其对陆地碳库的影响在不同情景下存在显著差异。在可持续环境情景下,林地得到了有效保护,相较于2020年中国林地碳储量增加了约0.60%;在可持续粮食情景下,耕地流失得到了缓解,尤其在南亚及东南亚地区的耕地面积呈现上升趋势:在可持续经济情景下,城市扩张速度加快,引起的碳损失量最多这项研究有助于推进丝绸之路沿线甚至全球可持续发展进程,为探寻可持续发展路径提供了科学依据。

关键词： Sustainable development goals(SDGs) Land-use projection Carbon pool Scenarios System dynamics model Cellular automata

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Mapping essential urban land use categories in China(EULUC-China):preliminary results for 2018

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Science Bulletin 2020年第3期65卷 182-187页

作者： Peng Gong Bin Chen Xuecao Li Han Liu Jie Wang Yuqi Bai Jingming Chen Xi Chen Lei Fang Shuailong Feng Yongjiu Feng Yali Gong Hao Gu Huabing Huang Xiaochun Huang Hongzan Jiao Yingdong Kang Guangbin Lei Ainong Li Xiaoting Li Xun Li Yuechen Li Zhilin Li Zhongde Li Chong Liu Chunxia Liu Maochou Liu Shuguang Liu Wanliu Mao Changhong Miao Hao Ni Qisheng Pan Shuhua Qi Zhehao Ren Zhuoran Shan Shaoqing Shen Minjun Shi Yimeng Song Mo Su Hoi Ping Suen Bo Sun Fangdi Sun Jian Sun Lin Sun Wenyao Sun Tian Tian Xiaohua Tong Yihsing Tseng Ying Tu Hong Wang Lan Wang Xi Wan Zongming Wang Tinghai Wu Yaowen Xie Jian Yang Jun Yang Man Yuan Wenze Yue Hongda Zeng Kuo Zhang Neng Zhang Tao Zhang Yu Zhang Feng Zhao Yichen Zheng Qiming Zhou Nicholas Clinton Zhiliang Zhu Bing Xu Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Tsinghua Urban Institute Tsinghua UniversityBeijing 100084China Center for Healthy Cities Institute for China Sustainable UrbanizationTsinghua UniversityBeijing 100084China Department of Land Air and Water ResourcesUniversity of CaliforniaDavisCA 95616-8627USA Department of Geological and Atmospheric Sciences Iowa State UniversityAmesIA 50011USA State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100101China AI for Earth Laboratory Cross-Strait InstituteTsinghua UniversityBeijing 100084China International Institute for Earth System Sciences Nanjing UniversityNanjing 210093China Research Center for Ecology and Environment of Central Asia Chinese Academy of SciencesUrumchi 830011China Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China National Engineering Laboratory for applied Technology in Forestry&Ecology in South China College of Life Science and TechnologyCentral South University of Forestry and TechnologyChangsha 410004China College of Surveying&Geo-Informatics Tongji UniversityShanghai 200092China Department of Urban Planning College of Architecture and Urban PlanningTongji UniversityShanghai 200092China Beijing Institute of Urban Planning Beijing 100045China Department of Urban Planning School of Urban DesignWuhan UniversityWuhan 430072China College of Earth Sciences Jilin UniversityChangchun 130061China Research Center for Digital Mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Institute of Remote Sensing and Geographic Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Department of Urban and Regional Planning School of Geography and PlanningSun Yat-sen Univ

Land use reflects human activities on *** land use is the highest level human alteration on Earth,and it is rapidly changing due to population increase and *** areas have widespread effects on local hydrology,climate,biodiversity,and food production[1,2].However,maps,that contain knowledge on the distribution,pattern and composition of various land use types in urban areas,are limited to city *** mapping standard on data sources,methods,land use classification schemes varies from city to city,due to differences in financial input and skills of mapping *** address various national and global environmental challenges caused by urbanization,it is important to have urban land uses at the national and global scales that are derived from the same or consistent data sources with the same or compatible classification systems and mapping *** is because,only with urban land use maps produced with similar criteria,consistent environmental policies can be made,and action efforts can be compared and assessed for large scale environmental ***,despite of the fact that a number of urban-extent maps exist at global scales[3,4],more detailed urban land use maps do not exist at the same *** at big country or regional levels such as for the United States,China and European Union,consistent land use mapping efforts are rare[5,6](e.g.,https://***/open_land_use/).

关键词： EULUC-China 土地利用类型

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