Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of...Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of existing data models and takinginto account the unique data structure and characteristic, methodology and key techniquesin the object-oriented spatial data modeling were proposed for the coalfield geological environment.The model building process was developed using object-oriented technologyand the Unified Modeling Language (UML) on the platform of ESRI geodatabase datamodels.A case study of spatial data modeling in UML was presented with successful implementationin the spatial database of the coalfield geological environment.The modelbuilding and implementation provided an effective way of representing the complexity andspecificity of coalfield geological environment spatial data and an integrated managementof spatial and property data.展开更多
To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm ...To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.展开更多
Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the ro...Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling,with the western stock of winter-spring cohort of neon flying squid （Ornmastrephes bartramii） in the northwest Pacific Ocean as an example.In this study,the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature （SST） from remote sensing during August to October of 2003-2008 were used.We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales （0.5°,1 ° and 2°）,four longitude scales （0.5°,1°,2° and 4°）,and three temporal scales （week,fortnight,and month）.The coefficients of variation （CV） of the weekly,biweekly and monthly suitability index （SI） were compared to determine which temporal and spatial scales of SI model are more precise.This study shows that the optimal temporal and spatial scales with the lowest CV are month,and 0.5° latitude and 0.5° longitude for O.bartramii in the northwest Pacific Ocean.This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts.We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.展开更多
Based on a newly proposed spatial data model Spatial Chromatic Model(SCM),we developed a spatial coding scheme,called the full-coded Ordinary Arranged Chromatic Diagram(full-OACD).As a type of spatial tessellation,ful...Based on a newly proposed spatial data model Spatial Chromatic Model(SCM),we developed a spatial coding scheme,called the full-coded Ordinary Arranged Chromatic Diagram(full-OACD).As a type of spatial tessellation,full-OACD partitions a geographic space into a number of subspaces,such as cells,edges,and vertices.These subspaces are called spatial particles and are assigned with unique codes chromatic codes.The generation,structure,computation,and properties of full-OACD are introduced.Relations between particulate chromatic codes and spatial topology are investigated.Full-OACD is a kind of new discrete spatial coordinate system where the information of real-world entities is embedded.Full-OACD provides an informative and meaningful spatial coding framework for spatial topological analysis and many other potential applications in geospatial information science.展开更多
Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon e...Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.展开更多
Digital elevation model(DEM)plays a fundamental role in the study of the earth system by expressing surface configuration,understanding surface process,and revealing surface mechanism.DEM is widely used in analysis an...Digital elevation model(DEM)plays a fundamental role in the study of the earth system by expressing surface configuration,understanding surface process,and revealing surface mechanism.DEM is widely used in analysis and modeling in the field of geoscience.However,traditional DEM has the defect of single attribute,which is difficult to support the research in earth system science oriented to geoscience process and mechanism mining.Hence,realizing the value-added data model on the basis of traditional DEM is necessary to serve digital elevation modeling and terrain analysis under the background of a new geomorphology research paradigm and earth observation technology.A theoretical framework for value-added DEM that mainly includes concept,connotation,content,and categories,is constructed in this study.The relationship between different types of value-added DEMs as well as the research significance and application category of this theoretical framework are also proposed.The following are different methods of value-added DEMs:(1)value-added methods of DEM space and time dimensions that emphasize the integration of the ground and underground as well as coupling of time and space,(2)attribute-based value-added methods composed of material(including underground,surface,and ground)and morphological properties,and(3)value-added methods of features and physical elements that consider geographical objects and landform features formed by natural processes and artificial effects.The digital terrace,slope,and watershed models are used as examples to illustrate application scenarios of the three kinds of value-added methods.This study aims to improve expression methods of DEMs under the background of new surveying and mapping technologies by adding value to the DEM at three levels of dimensions,attributes,and elements as well as support knowledge-driven digital geomorphological analysis in the era of big data.展开更多
In this paper a review on current research on 3DCM is presented, and an alternative approach by integrating the concepts and techniques of object\|oriented method and Computer Aided Design (CAD) is suggested. Through ...In this paper a review on current research on 3DCM is presented, and an alternative approach by integrating the concepts and techniques of object\|oriented method and Computer Aided Design (CAD) is suggested. Through the approach urban spatial entities as objects are extracted, which are represented with primary 3D elements (node, edge, face and body) and their combinations. In the light of the concept of object, the method supports the multiple representation of Level of Details (LOD). More importantly, topological relationships between objects are described so that 3D topological operations can be implemented.展开更多
This paper discusses the features and relevant theories of GIS spatial data model based on hypergraph,etc.The integrated concept model based on hypergraph and object_oriented model (HOOM) is proposed by the authors.Th...This paper discusses the features and relevant theories of GIS spatial data model based on hypergraph,etc.The integrated concept model based on hypergraph and object_oriented model (HOOM) is proposed by the authors.The principal contribution of this paper is that we study the K_section and other theories of hypergraph.An application example using HOOM is given at the end of the paper.展开更多
Interpolation methods in ArcGIS_ESRI Geostatistical Analyst tool allow obtaining unknown values at unsampled points from observed data and generating continuous surfaces. In this paper, forest data variables as tree h...Interpolation methods in ArcGIS_ESRI Geostatistical Analyst tool allow obtaining unknown values at unsampled points from observed data and generating continuous surfaces. In this paper, forest data variables as tree height and diameter measured in two plots in Central Mountains in Spain. These data were georeferenced to obtain maps that can visualize the spatial variability of these forest variables. In order to evaluate the best interpolation method that could adequately explain the spatial variability of those variables, two interpolation methods were studied： inverse results was made by means of statistical methods to analyze distance weighted （IDW） and Ordinary Kriging （OK）. A comparison of residuals. Results with the kriging method were slightly better.展开更多
This paper presents a new spatial data model based on trapezoidal-mesh for implementing spatial operations within geographical information systems(GIS).Based only on the solid foundation of spatial operations,diversif...This paper presents a new spatial data model based on trapezoidal-mesh for implementing spatial operations within geographical information systems(GIS).Based only on the solid foundation of spatial operations,diversified application models can be established to bridge the gap between Digital Earth models and the real world with its real-world problems(‘connecting through location’).In this paper,the involved polygon features are decomposed into a series of trapezoidalmeshes.Then,geo-processing operations are employed on these meshes rather than the original polygon features,resulting in a relatively simple spatial computation.As a kind of model designed by integrating raster with vector,the model presented here has advantages over other models when carrying out spatial operations insofar as providing a solid foundation for achieving the grand goal of Digital Earth.The concept of this data model and the two extensive examples of its application in spatial operations are elaborated upon in this article.As a result,this article and the research that supports it,proves that the adoption of the trapezoidal-mesh model greatly improves the efficiency of spatial operations in GIS.展开更多
Background:Tuberculosis(TB)is the notifiable infectious disease with the second highest incidence in the Qinghai province,a province with poor primary health care infrastructure.Understanding the spatial distribution ...Background:Tuberculosis(TB)is the notifiable infectious disease with the second highest incidence in the Qinghai province,a province with poor primary health care infrastructure.Understanding the spatial distribution of TB and related environmental factors is necessary for developing effective strategies to control and further eliminate TB.Methods:Our TB incidence data and meteorological data were extracted from the China Information System of Disease Control and Prevention and statistical yearbooks,respectively.We calculated the global and local Moran’s I by using spatial autocorrelation analysis to detect the spatial clustering of TB incidence each year.A spatial panel data model was applied to examine the associations of meteorological factors with TB incidence after adjustment of spatial individual effects and spatial autocorrelation.Results:The Local Moran’s I method detected 11 counties with a significantly high-high spatial clustering(average annual incidence:294/100000)and 17 counties with a significantly low-low spatial clustering(average annual incidence:68/100000)of TB annual incidence within the examined five-year period;the global Moran’s I values ranged from 0.40 to 0.58(all P-values<0.05).The TB incidence was positively associated with the temperature,precipitation,and wind speed(all P-values<0.05),which were confirmed by the spatial panel data model.Each 10°C,2 cm,and 1 m/s increase in temperature,precipitation,and wind speed associated with 9%and 3%decrements and a 7%increment in the TB incidence,respectively.Conclusions:High TB incidence areas were mainly concentrated in south-western Qinghai,while low TB incidence areas clustered in eastern and north-western Qinghai.Areas with low temperature and precipitation and with strong wind speeds tended to have higher TB incidences.展开更多
基金Supported by the Natural Science Foundation of Shanxi Province(2008011028-2)
文摘Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of existing data models and takinginto account the unique data structure and characteristic, methodology and key techniquesin the object-oriented spatial data modeling were proposed for the coalfield geological environment.The model building process was developed using object-oriented technologyand the Unified Modeling Language (UML) on the platform of ESRI geodatabase datamodels.A case study of spatial data modeling in UML was presented with successful implementationin the spatial database of the coalfield geological environment.The modelbuilding and implementation provided an effective way of representing the complexity andspecificity of coalfield geological environment spatial data and an integrated managementof spatial and property data.
文摘To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.
基金funded by National High Technology Research and Development Program of China (863 Program,2012AA092303)Project of Shanghai Science and Technology Innovation (12231203900)+2 种基金Industrialization Program of National Development and Reform Commission (2159999)National Science and Technology Support Program (2013BAD13B01)Shanghai Leading Academic Discipline Project
文摘Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling,with the western stock of winter-spring cohort of neon flying squid （Ornmastrephes bartramii） in the northwest Pacific Ocean as an example.In this study,the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature （SST） from remote sensing during August to October of 2003-2008 were used.We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales （0.5°,1 ° and 2°）,four longitude scales （0.5°,1°,2° and 4°）,and three temporal scales （week,fortnight,and month）.The coefficients of variation （CV） of the weekly,biweekly and monthly suitability index （SI） were compared to determine which temporal and spatial scales of SI model are more precise.This study shows that the optimal temporal and spatial scales with the lowest CV are month,and 0.5° latitude and 0.5° longitude for O.bartramii in the northwest Pacific Ocean.This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts.We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.
基金supported by National Natural Science Foundation of China(grant number:41971373)Natural Science Foundation of Zhejiang Province(grant number:LY17D10005).
文摘Based on a newly proposed spatial data model Spatial Chromatic Model(SCM),we developed a spatial coding scheme,called the full-coded Ordinary Arranged Chromatic Diagram(full-OACD).As a type of spatial tessellation,full-OACD partitions a geographic space into a number of subspaces,such as cells,edges,and vertices.These subspaces are called spatial particles and are assigned with unique codes chromatic codes.The generation,structure,computation,and properties of full-OACD are introduced.Relations between particulate chromatic codes and spatial topology are investigated.Full-OACD is a kind of new discrete spatial coordinate system where the information of real-world entities is embedded.Full-OACD provides an informative and meaningful spatial coding framework for spatial topological analysis and many other potential applications in geospatial information science.
基金National Natural Science Foundation of China,No.41601151Guangdong Natural Science Foundation,No.2016A030310149
文摘Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.
基金National Natural Science Foundation of China,No.41930102。
文摘Digital elevation model(DEM)plays a fundamental role in the study of the earth system by expressing surface configuration,understanding surface process,and revealing surface mechanism.DEM is widely used in analysis and modeling in the field of geoscience.However,traditional DEM has the defect of single attribute,which is difficult to support the research in earth system science oriented to geoscience process and mechanism mining.Hence,realizing the value-added data model on the basis of traditional DEM is necessary to serve digital elevation modeling and terrain analysis under the background of a new geomorphology research paradigm and earth observation technology.A theoretical framework for value-added DEM that mainly includes concept,connotation,content,and categories,is constructed in this study.The relationship between different types of value-added DEMs as well as the research significance and application category of this theoretical framework are also proposed.The following are different methods of value-added DEMs:(1)value-added methods of DEM space and time dimensions that emphasize the integration of the ground and underground as well as coupling of time and space,(2)attribute-based value-added methods composed of material(including underground,surface,and ground)and morphological properties,and(3)value-added methods of features and physical elements that consider geographical objects and landform features formed by natural processes and artificial effects.The digital terrace,slope,and watershed models are used as examples to illustrate application scenarios of the three kinds of value-added methods.This study aims to improve expression methods of DEMs under the background of new surveying and mapping technologies by adding value to the DEM at three levels of dimensions,attributes,and elements as well as support knowledge-driven digital geomorphological analysis in the era of big data.
文摘In this paper a review on current research on 3DCM is presented, and an alternative approach by integrating the concepts and techniques of object\|oriented method and Computer Aided Design (CAD) is suggested. Through the approach urban spatial entities as objects are extracted, which are represented with primary 3D elements (node, edge, face and body) and their combinations. In the light of the concept of object, the method supports the multiple representation of Level of Details (LOD). More importantly, topological relationships between objects are described so that 3D topological operations can be implemented.
文摘This paper discusses the features and relevant theories of GIS spatial data model based on hypergraph,etc.The integrated concept model based on hypergraph and object_oriented model (HOOM) is proposed by the authors.The principal contribution of this paper is that we study the K_section and other theories of hypergraph.An application example using HOOM is given at the end of the paper.
文摘Interpolation methods in ArcGIS_ESRI Geostatistical Analyst tool allow obtaining unknown values at unsampled points from observed data and generating continuous surfaces. In this paper, forest data variables as tree height and diameter measured in two plots in Central Mountains in Spain. These data were georeferenced to obtain maps that can visualize the spatial variability of these forest variables. In order to evaluate the best interpolation method that could adequately explain the spatial variability of those variables, two interpolation methods were studied： inverse results was made by means of statistical methods to analyze distance weighted （IDW） and Ordinary Kriging （OK）. A comparison of residuals. Results with the kriging method were slightly better.
文摘This paper presents a new spatial data model based on trapezoidal-mesh for implementing spatial operations within geographical information systems(GIS).Based only on the solid foundation of spatial operations,diversified application models can be established to bridge the gap between Digital Earth models and the real world with its real-world problems(‘connecting through location’).In this paper,the involved polygon features are decomposed into a series of trapezoidalmeshes.Then,geo-processing operations are employed on these meshes rather than the original polygon features,resulting in a relatively simple spatial computation.As a kind of model designed by integrating raster with vector,the model presented here has advantages over other models when carrying out spatial operations insofar as providing a solid foundation for achieving the grand goal of Digital Earth.The concept of this data model and the two extensive examples of its application in spatial operations are elaborated upon in this article.As a result,this article and the research that supports it,proves that the adoption of the trapezoidal-mesh model greatly improves the efficiency of spatial operations in GIS.
基金This study was supported by the Qinghai Center for Disease Control and Prevention(CDC).
文摘Background:Tuberculosis(TB)is the notifiable infectious disease with the second highest incidence in the Qinghai province,a province with poor primary health care infrastructure.Understanding the spatial distribution of TB and related environmental factors is necessary for developing effective strategies to control and further eliminate TB.Methods:Our TB incidence data and meteorological data were extracted from the China Information System of Disease Control and Prevention and statistical yearbooks,respectively.We calculated the global and local Moran’s I by using spatial autocorrelation analysis to detect the spatial clustering of TB incidence each year.A spatial panel data model was applied to examine the associations of meteorological factors with TB incidence after adjustment of spatial individual effects and spatial autocorrelation.Results:The Local Moran’s I method detected 11 counties with a significantly high-high spatial clustering(average annual incidence:294/100000)and 17 counties with a significantly low-low spatial clustering(average annual incidence:68/100000)of TB annual incidence within the examined five-year period;the global Moran’s I values ranged from 0.40 to 0.58(all P-values<0.05).The TB incidence was positively associated with the temperature,precipitation,and wind speed(all P-values<0.05),which were confirmed by the spatial panel data model.Each 10°C,2 cm,and 1 m/s increase in temperature,precipitation,and wind speed associated with 9%and 3%decrements and a 7%increment in the TB incidence,respectively.Conclusions:High TB incidence areas were mainly concentrated in south-western Qinghai,while low TB incidence areas clustered in eastern and north-western Qinghai.Areas with low temperature and precipitation and with strong wind speeds tended to have higher TB incidences.
