Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of indivi...Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.展开更多
Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application ...Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application of multi-source data becomes necessary.This paper presents an evidential reasoning (ER) approach to incorporate Landsat TM imagery,altitude and slope data.Results show that multi-source data contribute to the classification accuracy achieved by the ER method,whereas play a negative role to that derived by maximum likelihood classifier (MLC).In comparison to the results derived based on TM imagery alone,the overall accuracy rate of the ER method increases by 7.66% and that of the MLC method decreases by 8.35% when all data sources (TM plus altitude and slope) are accessible.The ER method is regarded as a better approach for multi-source image classification.In addition,the method produces not only an accurate classification result,but also the uncertainty which presents the inherent difficulty in classification decisions.The uncertainty associated to the ER classification image is evaluated and proved to be useful for improved classification accuracy.展开更多
This paper analyzes the status of existing resources through extensive research and international cooperation on the basis of four typical global monthly surface temperature datasets including the climate research dat...This paper analyzes the status of existing resources through extensive research and international cooperation on the basis of four typical global monthly surface temperature datasets including the climate research dataset of the University of East Anglia(CRUTEM3), the dataset of the U.S. National Climatic Data Center(GHCN-V3), the dataset of the U.S. National Aeronautics and Space Administration(GISSTMP), and the Berkeley Earth surface temperature dataset(Berkeley). China's first global monthly temperature dataset over land was developed by integrating the four aforementioned global temperature datasets and several regional datasets from major countries or regions. This dataset contains information from 9,519 stations worldwide of at least 20 years for monthly mean temperature, 7,073 for maximum temperature, and 6,587 for minimum temperature. Compared with CRUTEM3 and GHCN-V3, the station density is much higher particularly for South America, Africa,and Asia. Moreover, data from significantly more stations were available after the year 1990 which dramatically reduced the uncertainty of the estimated global temperature trend during 1990e2011. The integrated dataset can serve as a reliable data source for global climate change research.展开更多
Dynamic flood disaster simulation is an emerging and promising technology significantly useful in urban planning,risk assessment,and integrated decision support systems.It is still an important issue to integrate the ...Dynamic flood disaster simulation is an emerging and promising technology significantly useful in urban planning,risk assessment,and integrated decision support systems.It is still an important issue to integrate the large assets such as dynamic observational data,numerical flood simulation models,geographic information technologies,and computing resources into a unified framework.For the intended end user,it is also a holistic solution to create computer interpretable representations and gain insightful understanding of the dynamic disaster processes,the complex impacts,and interactions of disaster factors.In particular,it is still difficult to access and join harmonized data,processing algorithms,and models that are provided by different environmental information infrastructures.In this paper,we demonstrate a virtual geographic environments-based integrated environmental simulation framework for flood disaster management based on the notion of interlinked resources,which is capable of automated accumulating and manipulating of sensor data,creating dynamic geo-analysis and three-dimensional visualizations of ongoing geo-process,and updating the contents of simulation models representing the real environment.The prototype system is evaluated by applying it as a proof of concept to integrate in situ weather observations,numerical weather and flood disaster simulation models,visualization,and analysis of the real time flood event.Case applications indicate that the developed framework can be adopted for use by decision-makers for short-term planning and control since the resulting simulation and visualization are completely based on the latest status of environment.展开更多
Geographical studies of outdoor activities have increased in recent years with the rise in popularity of these activities worldwide,including in Japan.Volunteered geographic information(VGI)is a key tool for organizin...Geographical studies of outdoor activities have increased in recent years with the rise in popularity of these activities worldwide,including in Japan.Volunteered geographic information(VGI)is a key tool for organizing outdoor activities as it offers a means to determine the locational information and names of places.To evaluate the quality of VGI,geospatial data generated by land survey agencies and other VGI are often utilized as reference data.However,since these reference data may not be available,other methods are necessary to assure the quality of VGI.In this study,we examined five trust indicators based on the inherent characteristics of VGI through an empirical case study.We used mountain names extracted from OpenStreetMap in Japan as data because there were almost no other VGI in the vicinity.As a result,we isolated three trust indicators,namely versions,users,and tag corrections,to examine the thematic accuracy of VGI because these were the only statistically significant indicators.However,we found that the prediction rate of thematic accuracy was very low.To improve thematic accuracy,this study recommends using the most accurate versions,applying correctly given tags,and considering the motivations and characteristics of the VGI contributors.展开更多
To provide scientific management basis for the garden planning, project construction, maintenance, social service, this paper prompted that the urban gardening administration sectors need to construct gardening inform...To provide scientific management basis for the garden planning, project construction, maintenance, social service, this paper prompted that the urban gardening administration sectors need to construct gardening information management system. On the basis of fully requirements analysis of gardening sectors, this paper discussed the key technology for system construction. It also proposed to flexibly and smartly build up the system by using the secondary development design environment and running environment based on data center integration development platform. This system greatly helps the daily management and plays very important role in improving urban ecological environment and investment environment.展开更多
Many progresses have been made since the Digital Earth notion was envisioned thirteen years ago.However,the mechanism for integrating geographic informa-tion into the Digital Earth is still quite limited.In this conte...Many progresses have been made since the Digital Earth notion was envisioned thirteen years ago.However,the mechanism for integrating geographic informa-tion into the Digital Earth is still quite limited.In this context,we have developed a process to generate,integrate and publish geospatial Linked Data from several Spanish National data-sets.These data-sets are related to four Infrastructure for Spatial Information in the European Community(INSPIRE)themes,specifically with Administrative units,Hydrography,Statistical units,and Meteorology.Our main goal is to combine different sources(heterogeneous,multidisciplinary,multitemporal,multiresolution,and multilingual)using Linked Data principles.This goal allows the overcoming of current problems of information integration and driving geographical information toward the next decade scenario,that is,‘Linked Digital Earth’.展开更多
探究土地利用演变及其对碳储量的影响,对于减缓都市圈气候变化、促进绿色低碳发展具有重要意义。该研究在“双碳”目标背景下,结合兴趣点(point of interest,POI)数据并顾及斑块生成土地利用模拟模型(patch-generating land use simulat...探究土地利用演变及其对碳储量的影响,对于减缓都市圈气候变化、促进绿色低碳发展具有重要意义。该研究在“双碳”目标背景下,结合兴趣点(point of interest,POI)数据并顾及斑块生成土地利用模拟模型(patch-generating land use simulation model,PLUS)进行双约束转移矩阵优化,耦合生态系统服务与权衡的综合评估(integrated valuation of ecosystem services and trade-offs,InVEST)模型分析山东省济南都市圈2000—2020年土地利用演变规律及其对生态系统碳储量的影响,模拟预测了自然发展、城镇发展和生态保护3种情景下济南都市圈2030年和2060年土地利用变化并估算其生态系统碳储量,分析其碳储量重心迁移情况,并利用参数最优地理探测器探究碳储量空间分异驱动因素。结果表明:①2000—2020年,济南都市圈耕地、草地和未利用地面积持续减少,林地面积呈波动增加状态,水域、建设用地面积增长迅速;②2000—2020年,济南都市圈碳储量及土地利用空间格局相似,以黄河主脉为分界线,呈现“东南高,西北低”的分布特征,耕地类型碳储量为研究区碳储量的主要来源,占总碳储量的80%以上;③多情景模拟下的碳储量均有所降低,主要原因为高碳密度区域耕地转换为低碳密度区域建设用地,其中生态保护情景碳储量最高,2030年总碳储量为4226.86×10^(6) t,2060年总碳储量为3967.94×10^(6) t;④不同发展时期和情景下的济南都市圈碳储量重心均发生一定偏移,发展趋势受土地利用变化影响,重心地带一直处于山东大学历城区,说明济南都市圈发展较为全面均衡;⑤各驱动因子对济南都市圈碳储量空间分布具有明显影响,其中人口密度对碳储量空间分异解释力最大,交互作用下各因子均呈现对碳储量解释力增强的结果。展开更多
地理信息系统(Geographic Information System,GIS)在查询、分析地理信息方面具有效率高、功能强、使用便利等优点,已成为老旧供水管网整治管理的重要工具,以提高整治工作的效率和质量。文章以S市老旧供水管网整治中应用GIS技术的实例,...地理信息系统(Geographic Information System,GIS)在查询、分析地理信息方面具有效率高、功能强、使用便利等优点,已成为老旧供水管网整治管理的重要工具,以提高整治工作的效率和质量。文章以S市老旧供水管网整治中应用GIS技术的实例,介绍了数据集成规范化、电子地图可视化和整治管理长效化等具体功能的应用,并针对应用场景提出了优化对策,以适应供水行业精细化管理的发展需求。展开更多
基金supported by the National Key Research and Devel-opment Program of China (Grant No.2022YFC3005503)the National Natural Science Foundation of China (Grant Nos.52322907,52179141,U23B20149,U2340232)+1 种基金the Fundamental Research Funds for the Central Universities (Grant Nos.2042024kf1031,2042024kf0031)the Key Program of Science and Technology of Yunnan Province (Grant Nos.202202AF080004,202203AA080009).
文摘Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.
基金Under the auspices of National Natural Science Foundation of China (No.40871188)Knowledge Innovation Programs of Chinese Academy of Sciences (No.INFO-115-C01-SDB4-05)
文摘Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application of multi-source data becomes necessary.This paper presents an evidential reasoning (ER) approach to incorporate Landsat TM imagery,altitude and slope data.Results show that multi-source data contribute to the classification accuracy achieved by the ER method,whereas play a negative role to that derived by maximum likelihood classifier (MLC).In comparison to the results derived based on TM imagery alone,the overall accuracy rate of the ER method increases by 7.66% and that of the MLC method decreases by 8.35% when all data sources (TM plus altitude and slope) are accessible.The ER method is regarded as a better approach for multi-source image classification.In addition,the method produces not only an accurate classification result,but also the uncertainty which presents the inherent difficulty in classification decisions.The uncertainty associated to the ER classification image is evaluated and proved to be useful for improved classification accuracy.
基金supported by the China Meteorological Administration Special Public Welfare Research Fund (GYHY201206012, GYHY201406016)the Climate Change Foundation of the China Meteorological Administration (CCSF201338)
文摘This paper analyzes the status of existing resources through extensive research and international cooperation on the basis of four typical global monthly surface temperature datasets including the climate research dataset of the University of East Anglia(CRUTEM3), the dataset of the U.S. National Climatic Data Center(GHCN-V3), the dataset of the U.S. National Aeronautics and Space Administration(GISSTMP), and the Berkeley Earth surface temperature dataset(Berkeley). China's first global monthly temperature dataset over land was developed by integrating the four aforementioned global temperature datasets and several regional datasets from major countries or regions. This dataset contains information from 9,519 stations worldwide of at least 20 years for monthly mean temperature, 7,073 for maximum temperature, and 6,587 for minimum temperature. Compared with CRUTEM3 and GHCN-V3, the station density is much higher particularly for South America, Africa,and Asia. Moreover, data from significantly more stations were available after the year 1990 which dramatically reduced the uncertainty of the estimated global temperature trend during 1990e2011. The integrated dataset can serve as a reliable data source for global climate change research.
基金This study is supported by the National High Technology Research and Development Program of China(863 Program)(Nos.2012AA121305 and 2013AA120701)the National Natural Science Foundation of China(Nos.41471320 and 41201440).
文摘Dynamic flood disaster simulation is an emerging and promising technology significantly useful in urban planning,risk assessment,and integrated decision support systems.It is still an important issue to integrate the large assets such as dynamic observational data,numerical flood simulation models,geographic information technologies,and computing resources into a unified framework.For the intended end user,it is also a holistic solution to create computer interpretable representations and gain insightful understanding of the dynamic disaster processes,the complex impacts,and interactions of disaster factors.In particular,it is still difficult to access and join harmonized data,processing algorithms,and models that are provided by different environmental information infrastructures.In this paper,we demonstrate a virtual geographic environments-based integrated environmental simulation framework for flood disaster management based on the notion of interlinked resources,which is capable of automated accumulating and manipulating of sensor data,creating dynamic geo-analysis and three-dimensional visualizations of ongoing geo-process,and updating the contents of simulation models representing the real environment.The prototype system is evaluated by applying it as a proof of concept to integrate in situ weather observations,numerical weather and flood disaster simulation models,visualization,and analysis of the real time flood event.Case applications indicate that the developed framework can be adopted for use by decision-makers for short-term planning and control since the resulting simulation and visualization are completely based on the latest status of environment.
文摘Geographical studies of outdoor activities have increased in recent years with the rise in popularity of these activities worldwide,including in Japan.Volunteered geographic information(VGI)is a key tool for organizing outdoor activities as it offers a means to determine the locational information and names of places.To evaluate the quality of VGI,geospatial data generated by land survey agencies and other VGI are often utilized as reference data.However,since these reference data may not be available,other methods are necessary to assure the quality of VGI.In this study,we examined five trust indicators based on the inherent characteristics of VGI through an empirical case study.We used mountain names extracted from OpenStreetMap in Japan as data because there were almost no other VGI in the vicinity.As a result,we isolated three trust indicators,namely versions,users,and tag corrections,to examine the thematic accuracy of VGI because these were the only statistically significant indicators.However,we found that the prediction rate of thematic accuracy was very low.To improve thematic accuracy,this study recommends using the most accurate versions,applying correctly given tags,and considering the motivations and characteristics of the VGI contributors.
文摘To provide scientific management basis for the garden planning, project construction, maintenance, social service, this paper prompted that the urban gardening administration sectors need to construct gardening information management system. On the basis of fully requirements analysis of gardening sectors, this paper discussed the key technology for system construction. It also proposed to flexibly and smartly build up the system by using the secondary development design environment and running environment based on data center integration development platform. This system greatly helps the daily management and plays very important role in improving urban ecological environment and investment environment.
基金This work has been supported by the PlanetData(FP7-257641)myBigData(TIN2010-17060)projects.We would like to kindly thank all OEG members involved in the Linked Data initiatives.
文摘Many progresses have been made since the Digital Earth notion was envisioned thirteen years ago.However,the mechanism for integrating geographic informa-tion into the Digital Earth is still quite limited.In this context,we have developed a process to generate,integrate and publish geospatial Linked Data from several Spanish National data-sets.These data-sets are related to four Infrastructure for Spatial Information in the European Community(INSPIRE)themes,specifically with Administrative units,Hydrography,Statistical units,and Meteorology.Our main goal is to combine different sources(heterogeneous,multidisciplinary,multitemporal,multiresolution,and multilingual)using Linked Data principles.This goal allows the overcoming of current problems of information integration and driving geographical information toward the next decade scenario,that is,‘Linked Digital Earth’.
文摘探究土地利用演变及其对碳储量的影响,对于减缓都市圈气候变化、促进绿色低碳发展具有重要意义。该研究在“双碳”目标背景下,结合兴趣点(point of interest,POI)数据并顾及斑块生成土地利用模拟模型(patch-generating land use simulation model,PLUS)进行双约束转移矩阵优化,耦合生态系统服务与权衡的综合评估(integrated valuation of ecosystem services and trade-offs,InVEST)模型分析山东省济南都市圈2000—2020年土地利用演变规律及其对生态系统碳储量的影响,模拟预测了自然发展、城镇发展和生态保护3种情景下济南都市圈2030年和2060年土地利用变化并估算其生态系统碳储量,分析其碳储量重心迁移情况,并利用参数最优地理探测器探究碳储量空间分异驱动因素。结果表明:①2000—2020年,济南都市圈耕地、草地和未利用地面积持续减少,林地面积呈波动增加状态,水域、建设用地面积增长迅速;②2000—2020年,济南都市圈碳储量及土地利用空间格局相似,以黄河主脉为分界线,呈现“东南高,西北低”的分布特征,耕地类型碳储量为研究区碳储量的主要来源,占总碳储量的80%以上;③多情景模拟下的碳储量均有所降低,主要原因为高碳密度区域耕地转换为低碳密度区域建设用地,其中生态保护情景碳储量最高,2030年总碳储量为4226.86×10^(6) t,2060年总碳储量为3967.94×10^(6) t;④不同发展时期和情景下的济南都市圈碳储量重心均发生一定偏移,发展趋势受土地利用变化影响,重心地带一直处于山东大学历城区,说明济南都市圈发展较为全面均衡;⑤各驱动因子对济南都市圈碳储量空间分布具有明显影响,其中人口密度对碳储量空间分异解释力最大,交互作用下各因子均呈现对碳储量解释力增强的结果。
文摘地理信息系统(Geographic Information System,GIS)在查询、分析地理信息方面具有效率高、功能强、使用便利等优点,已成为老旧供水管网整治管理的重要工具,以提高整治工作的效率和质量。文章以S市老旧供水管网整治中应用GIS技术的实例,介绍了数据集成规范化、电子地图可视化和整治管理长效化等具体功能的应用,并针对应用场景提出了优化对策,以适应供水行业精细化管理的发展需求。
