In the first-tier cities,subway has become an important carrier and life focus of people’s daily travel activities.By studying the distribution of POIs of public service facilities around Metro Line 10,using GIS to q...In the first-tier cities,subway has become an important carrier and life focus of people’s daily travel activities.By studying the distribution of POIs of public service facilities around Metro Line 10,using GIS to quantitatively analyze the surrounding formats of subway stations,discussing the functional attributes of subway stations,and discussing the distribution of urban functions from a new perspective,this paper provided guidance and advice for the construction of service facilities.展开更多
Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and...Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and chemical parameters on a global scale.Earth observation data has the 4V features(volume,variety,veracity,and velocity) of big data that are suitable for climate change research.Moreover,the large amount of data available from scientific satellites plays an important role.This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research,such as synchronous satelliteeaerialeground observation experiments,which provide extremely large and abundant datasets; Earth observational sensitive factors(e.g.,glaciers,lakes,vegetation,radiation,and urbanization); and global environmental change information and simulation systems.With the era of global environment change dawning,Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking.Inevitably,Earth observation big data will encounter opportunities and challenges brought about by global climate change.展开更多
Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of ...Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of human-land interaction.In this paper,based on multi-source big data include 250 m×250 m resolution cell phone data,1.81×105 Points of Interest(POI)data and administrative boundary data,we built a UFA identification method and demonstrated empirically in Shenyang City,China.We argue that the method we built can effectively identify multi-scale multi-type UFAs based on human activity and further reveal the spatial correlation between urban facilities and human activity.The empirical study suggests that the employment functional zones in Shenyang City are more concentrated in central cities than other single functional zones.There are more mix functional areas in the central city areas,while the planned industrial new cities need to develop comprehensive functions in Shenyang.UFAs have scale effects and human-land interaction patterns.We suggest that city decision makers should apply multi-sources big data to measure urban functional service in a more refined manner from a supply-demand perspective.展开更多
The objective,connotations and research issues of big geodata mining were discussed to address its significance to geographical research in this paper.Big geodata may be categorized into two domains:big earth observat...The objective,connotations and research issues of big geodata mining were discussed to address its significance to geographical research in this paper.Big 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 precision.Based on this approach,the essence of mining big geodata includes four aspects.First,flow space,where flow replaces points in traditional space,will become the new presentation form for big human behavior data.Second,the objectives for mining big geodata are the spatial patterns and the spatial relationships.Third,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 scale.Fourth,data mining can be seen as a tool for discovery of geographic patterns and the patterns revealed may be attributed to human-land relationships.The big geodata mining methods may be categorized into two types in view of the mining objective,i.e.,classification mining and relationship mining.Future 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.展开更多
Paleogeographic analysis accounts for an essential part of geological research,making important contributions in the reconstruction of depositional environments and tectonic evolution histories(Ingalls et al.,2016;Mer...Paleogeographic analysis accounts for an essential part of geological research,making important contributions in the reconstruction of depositional environments and tectonic evolution histories(Ingalls et al.,2016;Merdith et al.,2017),the prediction of mineral resource distributions in continental sedimentary basins(Sun and Wang,2009),and the investigation of climate patterns and ecosystems(Cox,2016).展开更多
1 Introduction Information technology has been playing an ever-increasing role in geoscience.Sphisicated database platforms are essential for geological data storage,analysis and exchange of Big Data(Feblowitz,2013;Zh...1 Introduction Information technology has been playing an ever-increasing role in geoscience.Sphisicated database platforms are essential for geological data storage,analysis and exchange of Big Data(Feblowitz,2013;Zhang et al.,2016;Teng et al.,2016;Tian and Li,2018).The United States has built an information-sharing platform for state-owned scientific data as a national strategy.展开更多
Groundwater is an important water resource.The total amount of active groundwater in a hydrological cycle is about 3.5 times that of the total amount of surface water.The information in the deep groundwater records th...Groundwater is an important water resource.The total amount of active groundwater in a hydrological cycle is about 3.5 times that of the total amount of surface water.The information in the deep groundwater records the material exchange and dynamics in the earth’s evolution,which is an important aspect of the Deep-Time Digital Earth(DDE)plan.In recent years,scientists have discussed the distribution of transboundary aquifers and the environmental significance of groundwater resources through groundwater databases established by international organizations,such as the Global Groundwater Information System and the chronicles consortium,and national institutes,such as national geological surveys.The application of the groundwater database in the DDE plan,however,has been limited by the management,interactivity,and monitoring method of the groundwater data.The ability to further integrate data that are private and scattered across research institutions and individuals,while establishing an open,unified,and shared groundwater data platform,is essential to enhance our understanding of groundwater,ranging from shallow to deep water,which is a goal of the DDE plan.In this study,we introduced the current situation of groundwater database operations in domestic and international research and provided frontier research with groundwater big data.Considering the related objectives of the DDE plan and the limitations of existing groundwater databases,we proposed an improvement plan and new prospects for applying groundwater databases in the research of the deep earth.展开更多
【应用背景】地球大数据具有大规模、多样化、高复杂性和非结构化等特点,相关数据处理面临数据异构分散、计算复杂繁重、协同处理困难等挑战。【目的】提高海量异构地球大数据分析、处理、发布效率,加速大数据驱动科学创新。【方法】本...【应用背景】地球大数据具有大规模、多样化、高复杂性和非结构化等特点,相关数据处理面临数据异构分散、计算复杂繁重、协同处理困难等挑战。【目的】提高海量异构地球大数据分析、处理、发布效率,加速大数据驱动科学创新。【方法】本文设计并实现了一种新型超融合架构计算系统,研发了资源聚合与作业调度、HPC计算函数等服务,实现了超级计算、云计算等多元算力在单一计算系统中的集成融合与数据共享。【结果】建成了地球大数据云服务基础平台,形成了“云+超算”协同计算服务能力,满足了科研人员按需构建个性化计算环境、利用大数据与超级计算等方法协同处理科研数据需求。【结论】地球大数据云服务基础平台实现了多元算力融合,减少了跨算力数据搬运,提高了协同计算效率,更好的满足了专项与SDGs(Sustainable Development Goals)评估中复杂应用场景的快速计算需求,采用的方法对研制以数据为中心、一站式处理的新型融合架构计算系统具有积极借鉴意义。展开更多
In the context of urbanization,air pollution has emerged as a significant environmental challenge.A thorough understanding of their transport pathways,especially at a national scale,is essential for environmental prot...In the context of urbanization,air pollution has emerged as a significant environmental challenge.A thorough understanding of their transport pathways,especially at a national scale,is essential for environmental protection and policy-making.However,it remains partially elusive due to the constraints of available data and analytical methods.This study proposed a data-driven spatiotemporal correlation analysis method employing the Dynamic Time Warping(DTW).We represented the first comprehensive attempt to chart the long-term and nationwide transport pathways of PM_(2.5) utilizing an extensive dataset spanning from 2000 to 2021 across China,which is crucial for understanding long-term air pollution trends.Compared with traditional chemical transport models(CTMs),this data-driven method can generate transport pathways of PM_(2.5) without requiring extensive meteorological or emission data,and suggesting fundamentally consistent spatial distribution and trends.Our analysis reveals that China’s transport pathways are notably pronounced in the Northwest(34%of the total pathways in China),Southwest(22%),and North(21%)regions,with less significant pathways in the Northeast(10%)region and isolated occurrences elsewhere.Additionally,a notable decrease in the number of China’s PM_(2.5) transport pathways,similar to annual average concentrations,was observed after 2013,aligning with stricter environmental regulations.Furthermore,we have demonstrated the feasibility of applying our method to the transport pathways of other gaseous pollutants.The approach is effective in detecting and quantifying air pollutants’transport pathways,even in regions like the Northwest with limited monitoring infrastructure,which may aid in environmental decision-making.The study will notably improve the current understanding of air pollutants’transport process,providing a new perspective for studying the large-scale spatiotemporal correlations.展开更多
基金Beijing Municipal Social Science Foundation(22GLC062)Research on service function renewal of Beijing subway station living circle driven by multiple big data.Beijing Municipal Education Commission Social Science Project(KM202010009002)Young YuYou Talents Training Plan of North China University of Technology.
文摘In the first-tier cities,subway has become an important carrier and life focus of people’s daily travel activities.By studying the distribution of POIs of public service facilities around Metro Line 10,using GIS to quantitatively analyze the surrounding formats of subway stations,discussing the functional attributes of subway stations,and discussing the distribution of urban functions from a new perspective,this paper provided guidance and advice for the construction of service facilities.
基金funded by the International Cooperation and Exchanges National Natural Science Foundation of China (41120114001)
文摘Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and chemical parameters on a global scale.Earth observation data has the 4V features(volume,variety,veracity,and velocity) of big data that are suitable for climate change research.Moreover,the large amount of data available from scientific satellites plays an important role.This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research,such as synchronous satelliteeaerialeground observation experiments,which provide extremely large and abundant datasets; Earth observational sensitive factors(e.g.,glaciers,lakes,vegetation,radiation,and urbanization); and global environmental change information and simulation systems.With the era of global environment change dawning,Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking.Inevitably,Earth observation big data will encounter opportunities and challenges brought about by global climate change.
基金Under the auspices of Natural Science Foundation of China(No.41971166)。
文摘Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of human-land interaction.In this paper,based on multi-source big data include 250 m×250 m resolution cell phone data,1.81×105 Points of Interest(POI)data and administrative boundary data,we built a UFA identification method and demonstrated empirically in Shenyang City,China.We argue that the method we built can effectively identify multi-scale multi-type UFAs based on human activity and further reveal the spatial correlation between urban facilities and human activity.The empirical study suggests that the employment functional zones in Shenyang City are more concentrated in central cities than other single functional zones.There are more mix functional areas in the central city areas,while the planned industrial new cities need to develop comprehensive functions in Shenyang.UFAs have scale effects and human-land interaction patterns.We suggest that city decision makers should apply multi-sources big data to measure urban functional service in a more refined manner from a supply-demand perspective.
基金National Natural Science Foundation of China,No.41525004,No.41421001。
文摘The objective,connotations and research issues of big geodata mining were discussed to address its significance to geographical research in this paper.Big 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 precision.Based on this approach,the essence of mining big geodata includes four aspects.First,flow space,where flow replaces points in traditional space,will become the new presentation form for big human behavior data.Second,the objectives for mining big geodata are the spatial patterns and the spatial relationships.Third,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 scale.Fourth,data mining can be seen as a tool for discovery of geographic patterns and the patterns revealed may be attributed to human-land relationships.The big geodata mining methods may be categorized into two types in view of the mining objective,i.e.,classification mining and relationship mining.Future 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.
基金granted by the National Natural Science Foundation of China(Grant No.41802126)Open Fund of Key Laboratory of Sedimentary Mineralization and Sedimentary Minerals in Shandong Province(Grant No.DMSM2017006).
文摘Paleogeographic analysis accounts for an essential part of geological research,making important contributions in the reconstruction of depositional environments and tectonic evolution histories(Ingalls et al.,2016;Merdith et al.,2017),the prediction of mineral resource distributions in continental sedimentary basins(Sun and Wang,2009),and the investigation of climate patterns and ecosystems(Cox,2016).
基金granted by the National Science&Technology Major Projects of China(Grant No.2016ZX05033).
文摘1 Introduction Information technology has been playing an ever-increasing role in geoscience.Sphisicated database platforms are essential for geological data storage,analysis and exchange of Big Data(Feblowitz,2013;Zhang et al.,2016;Teng et al.,2016;Tian and Li,2018).The United States has built an information-sharing platform for state-owned scientific data as a national strategy.
基金supported by the National Natural Science Foundation of China No.41630318Deep-Time Digital Earth(DDE)Plan and Hydrology Team of DDE plan in China University of Geosciences,Wuhan。
文摘Groundwater is an important water resource.The total amount of active groundwater in a hydrological cycle is about 3.5 times that of the total amount of surface water.The information in the deep groundwater records the material exchange and dynamics in the earth’s evolution,which is an important aspect of the Deep-Time Digital Earth(DDE)plan.In recent years,scientists have discussed the distribution of transboundary aquifers and the environmental significance of groundwater resources through groundwater databases established by international organizations,such as the Global Groundwater Information System and the chronicles consortium,and national institutes,such as national geological surveys.The application of the groundwater database in the DDE plan,however,has been limited by the management,interactivity,and monitoring method of the groundwater data.The ability to further integrate data that are private and scattered across research institutions and individuals,while establishing an open,unified,and shared groundwater data platform,is essential to enhance our understanding of groundwater,ranging from shallow to deep water,which is a goal of the DDE plan.In this study,we introduced the current situation of groundwater database operations in domestic and international research and provided frontier research with groundwater big data.Considering the related objectives of the DDE plan and the limitations of existing groundwater databases,we proposed an improvement plan and new prospects for applying groundwater databases in the research of the deep earth.
文摘【应用背景】地球大数据具有大规模、多样化、高复杂性和非结构化等特点,相关数据处理面临数据异构分散、计算复杂繁重、协同处理困难等挑战。【目的】提高海量异构地球大数据分析、处理、发布效率,加速大数据驱动科学创新。【方法】本文设计并实现了一种新型超融合架构计算系统,研发了资源聚合与作业调度、HPC计算函数等服务,实现了超级计算、云计算等多元算力在单一计算系统中的集成融合与数据共享。【结果】建成了地球大数据云服务基础平台,形成了“云+超算”协同计算服务能力,满足了科研人员按需构建个性化计算环境、利用大数据与超级计算等方法协同处理科研数据需求。【结论】地球大数据云服务基础平台实现了多元算力融合,减少了跨算力数据搬运,提高了协同计算效率,更好的满足了专项与SDGs(Sustainable Development Goals)评估中复杂应用场景的快速计算需求,采用的方法对研制以数据为中心、一站式处理的新型融合架构计算系统具有积极借鉴意义。
基金funded by the National Natural Science Foundation of China(grant No.42376246)the Key Research and Development Project of Guangxi(grant No.GuikeAB24010046)the Joint Funds of the National Natural Science Foundation of China(grant No.U2268217).
文摘In the context of urbanization,air pollution has emerged as a significant environmental challenge.A thorough understanding of their transport pathways,especially at a national scale,is essential for environmental protection and policy-making.However,it remains partially elusive due to the constraints of available data and analytical methods.This study proposed a data-driven spatiotemporal correlation analysis method employing the Dynamic Time Warping(DTW).We represented the first comprehensive attempt to chart the long-term and nationwide transport pathways of PM_(2.5) utilizing an extensive dataset spanning from 2000 to 2021 across China,which is crucial for understanding long-term air pollution trends.Compared with traditional chemical transport models(CTMs),this data-driven method can generate transport pathways of PM_(2.5) without requiring extensive meteorological or emission data,and suggesting fundamentally consistent spatial distribution and trends.Our analysis reveals that China’s transport pathways are notably pronounced in the Northwest(34%of the total pathways in China),Southwest(22%),and North(21%)regions,with less significant pathways in the Northeast(10%)region and isolated occurrences elsewhere.Additionally,a notable decrease in the number of China’s PM_(2.5) transport pathways,similar to annual average concentrations,was observed after 2013,aligning with stricter environmental regulations.Furthermore,we have demonstrated the feasibility of applying our method to the transport pathways of other gaseous pollutants.The approach is effective in detecting and quantifying air pollutants’transport pathways,even in regions like the Northwest with limited monitoring infrastructure,which may aid in environmental decision-making.The study will notably improve the current understanding of air pollutants’transport process,providing a new perspective for studying the large-scale spatiotemporal correlations.
