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Automatic mapping of lunar landforms using DEM-derived geomorphometric parameters

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Journal of Geographical Sciences 2017年第11期27卷 1413-1427页

作者： WANG Jiao CHENG Weiming zhou chenghu ZHENG Xinqi School of Information Engineering China University of Geosciences Beijing 100083 China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China

Developing approaches to automate the analysis of the massive amounts of data sent back from the Moon will generate significant benefits for the field of lunar geomorphology. In this paper, we outline an automated method for mapping lunar landforms that is based on digital terrain analysis. An iterative self-organizing （ISO） cluster unsupervised classification enables the automatic mapping of landforms via a series of input raster bands that utilize six geomorphometric parameters. These parameters divide landforms into a number of spatially extended, topographically homogeneous segments that exhibit similar terrain attributes and neighborhood properties. To illustrate the applicability of our approach, we apply it to three representative test sites on the Moon, automatically presenting our results as a thematic landform map. We also quantitatively evaluated this approach using a series of confusion matrices, achieving overall accuracies as high as 83.34% and Kappa coefficients （K） as high as 0.77. An immediate version of our algorithm can also be applied for automatically mapping large-scale lunar landforms and for the quantitative comparison of lunar surface morphologies.

关键词： automatic classification geomorphometric parameters ISO cluster lunar iandforms DEM

A comparative analysis of changes in the phasing of temperature and satellite-derived greenness at northern latitudes

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Journal of Geographical Sciences 2013年第1期23卷 57-66页

作者： MA Ting zhou chenghu PEI Tao XIE Yichun State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS Seijing 100101 China Department of Geography and Geology Eastern Michigan University Ypsilanti MI 48917 USA

Plant growth at northern latitudes is highly responsive to the climatic changes that have occurred over recent decades. However, the sensitivity of the phasing of the seasonal cycle of terrestrial ecosystems to a changing environment remains less widely understood. We present an investigation and comparative study of large-scale changes in seasonal cy- cling of both land surface temperature and plant growth. Our results have shown trends in- dicating a marked increased towards overall plant productivity by -3% from 1982 to 2005, reduced trends in seasonal variation at low-mid latitudes by ~2%, increased trends in sea- sonal variations at mid-high latitudes by ~7%, and an earlier phase in northern terrestrial ecosystems （~1.1 days） in parallel with changes in the phasing of surface temperatures at northern latitudes over the 24 years in this study. These shifts in annual cycles of terrestrial vegetation appear to have a distinct geographical zonality and are dependent upon latitudinal changes in climatic variables. More conspicuous changes in overall vegetation productivity and the seasonal phase of ecosystems have been observed in Eurasia compared to North America, largely because of a more rapid rise in temperature. Our results state that changing climate boosts plant growth at northern latitudes, but also alters the phase and seasonal variations of the annual cycle of terrestrial ecosystems.

关键词： land surface temperature plant phenoiogy NDVI climate changes northern latitudes

Knowledge System,Ontology,and Knowledge Graph of the Deep-Time Digital Earth(DDE): Progress and Perspective

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Journal of Earth Science 2023年第5期34卷 1323-1327页

作者： Xiumian Hu Yiwei Xu Xiaogang Ma Yunqiang Zhu Chao Ma Chao Li Hairong Lü Xinbing Wang chenghu zhou Chengshan Wang School of Earth Sciences and Engineering Nanjing UniversityNanjing 210023China State Key Laboratory of Palaeobiology and Stratigraphy Nanjing Institute of Geology and Palaeontology and Center for Excellence in Life and PaleoenvironmentChinese Academy of SciencesNanjing 210008China Department of Computer Science University of IdahoMoscow ID 83844USA Institute of Geographical Science and Natural Resources Chinese Academy of SciencesBeijing 100101China State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation&Institute of Sedimentary Geology&College of Computer Science and Cyber Security Chengdu University of TechnologyChengdu 610059China IUGS Deep-Time Digital Earth Research Center of Excellence Suzhou 215101China Department of Automation Tsinghua UniversityBeijing 100084China School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesBeijing 100083China

THE USE OF KNOWLEDGE GRAPH IN NATURAL SCIENCE Knowledge graph is a field of Artificial Intelligence(AI)that aims to represent knowledge in the form of graphs,consisting of nodes and edges which represent entities and relationships between nodes respectively(Aidan et al.,2022).Although the knowledge graph was popularized recently due to use of this idea in Google’s search engine in 2012(Amit,2012),its root can be traced back to the emergence of the Semantic Web as well as earlier works in ontology(Aggarwal,2021).

关键词： DDE Google Web Semantic

Research and compilation of the Geomorphologic Atlas of the People＇s Republic of China （1：1,000,000）

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Journal of Geographical Sciences 2011年第1期21卷 89-100页

作者： CHENG Weiming zhou chenghu CHAI Huixia ZHAO Shangmin LIU Haijiang zhou Zengpo Institute of Geographic Sciences and Natural Resources Research CAS State Key Laboratory of Resources and Environmental Information Systems Beijing 100101 China Xinjiang Institute of Ecology and Geography CAS Urumqi 830011 China China National Environmental Monitoring Center Beijing 100012 China

Geomorphologic maps are one of the most fundamental materials of the natural environment. They have been widely used in scientific research,resource exploration and extraction,education and military affairs etc. An editorial committee was established in 2001 to collect materials for researching and compiling a set of new 1：1,000,000 geomorphologic atlas of China. A digital geomorphologic database was created with visual interpretation from Landsat TM/ETM imageries and SRTM-DEM etc. The atlas compiled from the database was finished. The main characteristics of the atlas are as follows：Firstly,Landsat TM/ETM imageries,published geomorphologic maps or sketches,geographical base maps,digital geological maps,and other thematic maps were collected,which were uniformly geometrically rectified,clipped into uniform sheets,and stored in the foundation database. Secondly,based on the legends of 15 sheets 1：1,000,000 maps published in the 1980s,a geomorphologic classification system was built by combining morphology and genesis types. The system comprised seven hierarchical layers：basic morphology,genesis,sub-genesis,morphology,micro-morphology,slope and aspect,material composition and lithology. These layers were stored in the database during visual image interpretation. About 2000 kinds of morpho-genesis and 300 kinds of morpho-structure were interpreted. Thirdly,the legend system was built,which included color,symbol bases and note bases etc.,compilation standards and procedures were developed,74 sheets of 1：1,000,000 covering all land and sea territories of China were compiled,the 1：1,000,000 geomorphologic atlas of the People＇s Republic of China was finished and published. The atlas will fill the blanks in national basic scale thematic maps,and the geomorphologic database could be applied widely in many fields in the future.

关键词： digital geomorphology geomorphologic map 1:1,000,000 geomorphologic database

Big geodata mining:Objective,connotations and research issues

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Journal of Geographical Sciences 2020年第2期30卷 251-266页

作者： PEI Tao SONG Ci GUO Sihui SHU Hua LIU Yaxi DU Yunyan MA Ting zhou chenghu State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China

The objective,connotations and research issues of big geodata mining were discussed to address its significance to geographical research in this *** geodata may be categorized into two domains:big earth observation data and big human behavior data.A description of big geodata includes,in addition to the“5Vs”(volume,velocity,value,variety and veracity),a further five features,that is,granularity,scope,density,skewness and *** on this approach,the essence of mining big geodata includes four ***,flow space,where flow replaces points in traditional space,will become the new presentation form for big human behavior ***,the objectives for mining big geodata are the spatial patterns and the spatial ***,the spatiotemporal distributions of big geodata can be viewed as overlays of multiple geographic patterns and the characteristics of the data,namely heterogeneity and homogeneity,may change with ***,data mining can be seen as a tool for discovery of geographic patterns and the patterns revealed may be attributed to human-land *** big geodata mining methods may be categorized into two types in view of the mining objective,i.e.,classification mining and relationship *** research will be faced by a number of issues,including the aggregation and connection of big geodata,the effective evaluation of the mining results and the challenge for mining to reveal“non-trivial”knowledge.

关键词： big earth observation data big human behavior data geographical spatiotemporal pattern spatiotemporal heterogeneity knowledge discovery

Geoscience knowledge graph in the big data era

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Science China Earth Sciences 2021年第7期64卷 1105-1114页

作者： chenghu zhou Hua WANG Chengshan WANG Zengqian HOU Zhiming ZHENG Shuzhong SHEN Qiuming CHENG Zhiqiang FENG Xinbing WANG Hairong LV Junxuan FAN Xiumian HU Mingcai HOU Yunqiang ZHU State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China School of Earth Sciences and Resources China University of Geosciences(Beijing)Beijing 100083China Key Laboratory of Deep-Earth Dynamics of Ministry of Natural Resources Institute of GeologyChinese Academy of Geological SciencesBeijing 100037China Institute of Artificial Intelligence Beihang UniversityBeijing 100191China State Key Laboratory for Mineral Deposits Research School of Earth Sciences and EngineeringNanjing UniversityNanjing 210023China Sinopec Petroleum Exploration&Production Research Institute Beijing 100083China School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Tsinghua UniversityBeijing 100084China Institute of Sedimentary Geology Chengdu University of TechnologyChengdu 610059China

Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the *** is a revolutionary leap in the research of geoscience knowledge discovery from the traditional encyclopedic discipline knowledge system to the computer-understandable and operable knowledge *** on adopting the graph pattern of general knowledge representation,the geoscience knowledge graph expands the unique spatiotemporal features to the Geoscience knowledge,and integrates geoscience knowledge elements,such as map,text,and number,to establish an all-domain geoscience knowledge representation model.A federated,crowd intelligence-based collaborative method of constructing the geoscience knowledge graph is developed here,which realizes the construction of high-quality professional knowledge graph in collaboration with global *** also develop a method for constructing a dynamic knowledge graph of multi-modal geoscience data based on in-depth text analysis,which extracts geoscience knowledge from massive geoscience literature to construct the latest and most complete dynamic geoscience knowledge graph.A comprehensive and systematic geoscience knowledge graph can not only deepen the existing geoscience big data analysis,but also advance the construction of the high-precision geological time scale driven by big data,the compilation of intelligent maps driven by rules and data,and the geoscience knowledge evolution and reasoning analysis,among *** will further expand the new directions of geoscience research driven by both data and knowledge,break new ground where geoscience,information science,and data science converge,realize the original innovation of the geoscience research and achieve major theoretical breakthroughs in the spatiotemporal big data research.

关键词： Geoscience knowledge graph All-domain geoscience knowledge representation model Federated crowd intelligence collaboration High-precision geological time scale

A proposal for the theoretical analysis of the interactive coupled effects between urbanization and the eco-environment in mega-urban agglomerations

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Journal of Geographical Sciences 2017年第12期27卷 1431-1449页

作者： FANG Chuanglin zhou chenghu GU Chaolin CHEN Liding LI Shuangcheng Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China School of Architecture Tsinghua University Beijing 100084 China Research Center for Eco-Environmental Sciences CAS Beijing 100875 China College of Urban and Environmental Sciences Peking University Beijing 100871 China

Mega-urban agglomerations are strategic core areas for national economic development and the main regions of new urbanization. They also have important roles in shifting the global economic center of gravity to China. However, the development of mega-urban agglomerations has triggered the interactive coercion between resources and the eco-envi- ronment. The interactive coupled effects between urbanization and the eco-environment in mega-urban agglomerations represent frontier and high-priority research topics in the field of Earth system science over the next decade. In this paper, we carried out systematic theo- retical analysis of the interactive coupling mechanisms and coercing effects between ur- banization and the eco-environment in mega-urban agglomerations. In detail, we analyzed the nonlinear-coupled relationships and the coupling characteristics between natural and human elements in mega-urban agglomerations. We also investigated the interactive coercion intensities between internal and external elements, and the mechanisms and patterns of local couplings and telecouplings in mega-urban agglomeration systems, which are affected by key internal and external control elements. In addition, we proposed the interactive coupling theory on urbanization and the eco-environment in mega-urban agglomerations. Furthermore we established a spatiotemporal dynamic coupling model with multi-element, multi-scale, multi-scenario, multi-module and multi-agent integrations, which can be used to develop an intelligent decision support system for sustainable development of mega-urban agglomera- tions. In general, our research may provide theoretical guidance and method support to solve problems related to mega-urban agglomerations and maintain their sustainable development.

关键词： mega-urban agglomeration urbanization eco-environment interactive coupled effects coupling theory process of theoretical analysis

Structure and contents of layered classification system of digital geomorphology for China

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Journal of Geographical Sciences 2011年第5期21卷 771-790页

作者： CHENG Weiming zhou chenghu LI Bingyuan SHEN Yuancun ZHANG Baiping State Key Laboratory of Resources and Environmental Information Systems Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China

This paper presents the structure and contents of a standardized layered classification system of digital geomorphology for *** digital classification method combines landforms characteristics of morphology with genesis.A total of 15 categories of exogenic and endogenic forces are divided into two broad categories：morpho-genetic and morpho-structural *** patches are used to manage the morpho-genetic types,and solitary points,lines and polygons are used to manage the morpho-structural *** classification method of digital morpho-genetic types can be divided into seven layers,*** morphology and altitude,genesis,sub-genesis,morphology,micro-morphology,slope and aspect,material and *** method proposes combinations of matrix forms based on layered *** attributes of every landform types are obtained from all or some of the seven *** the 15 forces categories,some classification indicators and calculation methods are presented for the basic morphology,the morphologic and sub-morphologic landforms of the morpho-genetic *** solitary polygon,linear and point types of morpho-structural landforms are presented *** layered classification method can meet the demands of scale-span geomorphologic mapping for the national primary scales from 1：500,000 to 1：1,000,*** layers serve as classification indicators,and therefore can be added and reduced according to mapping demands,providing flexible expandability.

关键词： digital geomorphology classification system morpho-genesis morpho-structure layered classification method

中国城市绿色发展效率时空演变特征及影响因素

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地理学报 2019年第10期74卷 2027-2044页

作者：周亮车磊周成虎兰州交通大学测绘与地理信息学院兰州730070 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室北京100101 西北师范大学地理与环境科学学院兰州730070

绿色发展作为化解自然环境约束、破解经济转型难题、支撑和实现全球可持续发展目标(SDGs)关键。正逐渐成为中国生态文明建设、美丽中国建设和全球经济转型与重构的重要指导理念。在梳理绿色发展概念与内涵基础上,采用SBM-Undesirable模... 详细信息

绿色发展作为化解自然环境约束、破解经济转型难题、支撑和实现全球可持续发展目标(SDGs)关键。正逐渐成为中国生态文明建设、美丽中国建设和全球经济转型与重构的重要指导理念。在梳理绿色发展概念与内涵基础上,采用SBM-Undesirable模型、泰尔指数和空间马尔科夫链等方法,对2005-2015年中国城市绿色发展效率时空分异特征及其演变过程进行了测度与刻画,并进一步耦合自然与人文因素定量探讨了人地关系地域系统下的影响机制。研究表明:① 2005-2015年中国城市绿色发展效率稳步提升,由0.475增加到0.523,总体提高了10%,时序上呈现“W”型波动增加的阶段性演变特征。②中国城市绿色发展效率呈现出“东中西”阶梯状递减的区域差异规律,不同类型城市群具有“国家级>区域性>地方性”倒金字塔式集群增长特征,形成了“超大城市>特大城市>大城市>中等城市>小城市”稳定等级规模结构。③中国城市绿色发展效率空间集聚特征显著,高效率城市存在正向溢出效应,低效率城市则负向溢出影响,“高高集聚、高带动低”的空间俱乐部趋同现象较为凸显,不同类型城市演化存在显著的路径依赖与时空惯性。④人地关系地域系统视角下,人文社会因素对城市绿色发展效率影响程度大于自然本底要素,其中经济实力、产业结构、开放程度和城市气温呈现积极促进作用。

关键词：绿色发展效率空间马尔科夫时空演变人地关系可持续发展目标