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A distributed spatial computing prototype system in grid environment

Science china(Technological Sciences) 2010年第S1期53卷 25-32页

作者： wu lun,yan menglong,gao yong,yang zhenzhen,zhao yong & chen bin institute of remote sensing and geographic information system,peking university,beijing 100871,china 1. institute of remote sensing and geographic information system Peking University Beijing 100871 China

Digital Earth has been a hot topic and research trend since it was proposed,and Digital china has drawn much attention in *** a key technique to implement Digital china,grid is an excellent and promising concept to construct a dynamic,inter-domain and distributed computing *** is appropriate to process geographic information across dispersed computing resources in networks effectively and cooperatively.A distributed spatial computing prototype system is designed and implemented with the Globus *** important aspects are discussed in *** architecture is proposed according to the characteristics of grid firstly,and then the spatial resource query and access interfaces are designed for heterogeneous data *** open-up hierarchical architecture for resource discovery and management is represented to detect spatial and computing resources in grid.A standard spatial job management mechanism is implemented by grid service for convenient *** addition,the control mechanism of spatial datasets access is developed based on *** prototype system utilizes the Globus Toolkit to implement a common distributed spatial computing framework,and it reveals the spatial computing ability of grid to support Digital china.

关键词： distributed geographic information processing grid computing Digital china GIS

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Artificial intelligence for geoscience:Progress,challenges,and perspectives

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The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie zhao Sheng Wang Chaojun Ouyang Min chen chenying Liu Jin Zhang Long Yu Fei Wang yong Xie Jun Li Fang Wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian yongjun Xu chengqing Yu Wei Han Tao Sun Zezhi Shao Tangwen Qian zhao chen Jiangyuan Zeng Huai Zhang Husi Letu bing Zhang Li Wang Lei Luo Chong Shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang Wei zhao Nan Li Chaolei Zheng yang Zhou Changping Huang Defeng Feng Qingsong Xu yan wu Danfeng Hong Zhenyu Wang Yinyi Lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng Shi Lizhe Wang Aerospace information Research institute Chinese Academy of SciencesBeijing 100094China School of Computer Science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China Data Science in Earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China institute of Computing Technology Chinese Academy of SciencesBeijing 100190China School of geographical Sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials Science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy University of CaliforniaCaliforniaRiversideCA 92521USA institute of remote sensing and geographical information system School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and remote sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing Earth science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

关键词： Earth utilizing landscape

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基于地理信息系统的色季拉山土地利用时空动态变化

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科学技术与工程 2021年第7期21卷 2602-2608页

作者：武辰爽郭永刚苏立彬西藏农牧学院水利土木工程学院林芝860000 西藏农牧学院高原生态研究所林芝860000

以西藏色季拉山为研究对象,对其1990—2018年土地利用类型时空变化及其影响因素进行了探究和分析。选取三期多时相遥感图像,基于遥感图像处理(the environment for visualizing images, ENVI)和地理信息系统(arc geographic information... 详细信息

以西藏色季拉山为研究对象,对其1990—2018年土地利用类型时空变化及其影响因素进行了探究和分析。选取三期多时相遥感图像,基于遥感图像处理(the environment for visualizing images, ENVI)和地理信息系统(arc geographic information of system, ArcGIS)软件,并结合该区域土地利用动态图和土地变更调查,得出土地利用分类图、转移矩阵土地利用动态度等结果。28年间,色季拉山主要土地利用类型是草地、林地和未利用地,三者整体上均表现出面积减少的现象;城乡、工矿及居民用地是2005年后出现的新增土地利用类型;空间上,东北方位变化最小,其余方位土地类型变化均匀;经调查,促使土地利用类型发生变化的原因主要有人口增多、城市基础建设和牧业发展。研究成果可为保护色季拉山生态经济和土地管理各级部门提供科学且可靠的理论支持。

关键词：土地利用时空动态变化地理信息系统色季拉山

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青藏高原植被结构变化反映环境变迁

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Science Bulletin 2023年第17期68卷 1928-1937页

作者：王艳芬薛凯胡容海丁柏阳曾弘李瑞津徐斌庞哲宋小宁李聪佳杜剑卿杨秀春张泽林郝彦宾崔骁勇郭柯高清竹张扬建朱军涛孙建李耀明姜丽丽周华坤罗彩云张振华高庆波陈世龙纪宝明徐兴良陈槐李奇赵亮徐世晓刘雅莉胡林勇武建双杨其恩董世魁贺金生赵新全汪诗平朴世龙于贵瑞傅伯杰 College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China beijing yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China State Key Laboratory of Tibetan Plateau Earth system Environment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXining 810016China Key Laboratory of Adaptation and Evolution of Plateau Biota Northwest Institute of Plateau BiologyChinese Academy of SciencesXining 810001China binzhou institute of Technology Weiqiao-UCAS Science and Technology ParkBinzhou 256606China College of Mining Engineering North China University of Science and TechnologyTangshan 063210China Key Laboratory of Agri-Informatics Ministry of Agriculture and Rural AffairsInstitute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China College of Life Sciences University of Chinese Academy of SciencesBeijing 100049China School of Grassland Science Beijing Forestry UniversityBeijing 100083China State Key Laboratory of Vegetation and Environmental Change Institute of BotanyChinese Academy of SciencesBeijing 100093China institute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural SciencesBeijing 100081China Key Laboratory for Agro-Environment&Climate Change Ministry of AgricultureBeijing 100081China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization&Ecological Restoration Biodiversity Conservation Key Laboratory of Sichuan Province Chengdu Institute of BiologyChinese Academy of SciencesChengdu 610041China Zoige Peatland and Global Change Research Station Chinese Academy of SciencesHongyuan 62

草地植被结构对于其生产和生态功能至关重要,但大尺度信息严重匮乏.本研究结合多源遥感数据和深度学习,在区域尺度上厘清了青藏高原高寒草地基于群系的植物群落结构空间格局,并比较了其历史变化.过去40年,高寒草甸在高寒草地中的比例从... 详细信息

草地植被结构对于其生产和生态功能至关重要,但大尺度信息严重匮乏.本研究结合多源遥感数据和深度学习,在区域尺度上厘清了青藏高原高寒草地基于群系的植物群落结构空间格局,并比较了其历史变化.过去40年,高寒草甸在高寒草地中的比例从50%上升到69%,反映了变暖变湿的环境变化.此外,高寒草甸和高寒草原中高山嵩草草甸和紫花针茅草原的优势度分别增强到76%和92%.其中,气候因子驱动了紫花针茅草原近些年的分布;高山嵩草草甸近些年的分布则并非完全由气候驱动,人类活动可能起重要作用.本研究首次探索了区域尺度植被结构特征与历史变化,为认识青藏高原草地变化的驱动力及其空间异质性提供了新视角.

关键词：高寒草地植被结构草地植被多源遥感数据深度学习植物群落结构区域尺度高寒草原

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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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