文章基于长江经济带非金属矿产数据,利用地理信息系统(geographic information system,GIS)空间分析方法和脱钩模型研究2007—2018年期间该地区非金属矿采矿权分布的时空变化特征。结果表明:非金属矿开采重心呈现出向西部地区移动的趋势...文章基于长江经济带非金属矿产数据,利用地理信息系统(geographic information system,GIS)空间分析方法和脱钩模型研究2007—2018年期间该地区非金属矿采矿权分布的时空变化特征。结果表明:非金属矿开采重心呈现出向西部地区移动的趋势;非金属矿采矿权分布呈现“西南—东北”的空间格局,且非金属矿高开采强度区呈现出收缩趋势;非金属矿采矿权分布具有显著的空间正相关特性,其中,高-高类型区域分布在贵州、江西等省份,低-低类型区域分布在浙江、江苏、安徽等省份;非金属矿采矿权面积与经济增长脱钩状态稳定,脱钩情况理想,经济发展对非金属矿产开发依赖性减小;建筑石料用灰岩采矿权分布的时空规律和非金属矿采矿权分布的时空规律相似,均呈现开采重心向西部偏移的态势。该研究结果反映了在2007—2018年中国经济高速发展期间,长江经济带非金属矿采矿权分布的时空特征变化及其影响因素,为今后非金属矿产资源开发空间布局优化提供空间决策参考。展开更多
Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-bas...Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-based) incremental updating (E-BIU) is proposed in this paper. At first, the relationship among the events, spatial changes and the database operations is analyzed, then a total architecture of E-BIU implementation is designed, which includes an event queue, three managers and two sets of rules, each component is presented in detail. The process of the E-BIU of master STDB is described successively. An example of building’s incremental updating is given to illustrate this approach at the end. The result shows that E-BIU is an efficient automatic updating approach for master STDB.展开更多
To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used....To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used. Drinking water samples from 29 wells in Zhenping County, China, were collected and analyzed. 35 parameters on water quality were selected, such as chloride concentration, sulphate concentration, total hardness, nitrate concentration, fluoride concentration, turbidity, pH, chromium concentration, COD, bacterium amount, total coliforms and color. The best spatial interpolation methods for the 35 parameters were found and selected from all types of interpolation methods in GIS environment according to the minimum cross-validation errors. The ACCA was improved through three strategies, namely mixed distance function, average similitude degree and probability conversion functions. Then, the ACCA was carried out to obtain different water quality grades in the GIS environment. In the end, the result from the ACCA was compared with those from the competitive Hopfield neural network(CHNN) to validate the feasibility and effectiveness of the ACCA according to three evaluation indexes, which are stochastic sampling method, pixel amount and convergence speed. It is shown that the spatial water quality grades obtained from the ACCA were more effective, accurate and intelligent than those obtained from the CHNN.展开更多
The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GI...The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.展开更多
文摘文章基于长江经济带非金属矿产数据,利用地理信息系统(geographic information system,GIS)空间分析方法和脱钩模型研究2007—2018年期间该地区非金属矿采矿权分布的时空变化特征。结果表明:非金属矿开采重心呈现出向西部地区移动的趋势;非金属矿采矿权分布呈现“西南—东北”的空间格局,且非金属矿高开采强度区呈现出收缩趋势;非金属矿采矿权分布具有显著的空间正相关特性,其中,高-高类型区域分布在贵州、江西等省份,低-低类型区域分布在浙江、江苏、安徽等省份;非金属矿采矿权面积与经济增长脱钩状态稳定,脱钩情况理想,经济发展对非金属矿产开发依赖性减小;建筑石料用灰岩采矿权分布的时空规律和非金属矿采矿权分布的时空规律相似,均呈现开采重心向西部偏移的态势。该研究结果反映了在2007—2018年中国经济高速发展期间,长江经济带非金属矿采矿权分布的时空特征变化及其影响因素,为今后非金属矿产资源开发空间布局优化提供空间决策参考。
文摘Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-based) incremental updating (E-BIU) is proposed in this paper. At first, the relationship among the events, spatial changes and the database operations is analyzed, then a total architecture of E-BIU implementation is designed, which includes an event queue, three managers and two sets of rules, each component is presented in detail. The process of the E-BIU of master STDB is described successively. An example of building’s incremental updating is given to illustrate this approach at the end. The result shows that E-BIU is an efficient automatic updating approach for master STDB.
基金Projects(41161020,41261026) supported by the National Natural Science Foundation of ChinaProject(BQD2012013) supported by the Research starting Funds for Imported Talents,Ningxia University,China+1 种基金Project(ZR1209) supported by the Natural Science Funds,Ningxia University,ChinaProject(NGY2013005) supported by the Key Science Project of Colleges and Universities in Ningxia,China
文摘To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used. Drinking water samples from 29 wells in Zhenping County, China, were collected and analyzed. 35 parameters on water quality were selected, such as chloride concentration, sulphate concentration, total hardness, nitrate concentration, fluoride concentration, turbidity, pH, chromium concentration, COD, bacterium amount, total coliforms and color. The best spatial interpolation methods for the 35 parameters were found and selected from all types of interpolation methods in GIS environment according to the minimum cross-validation errors. The ACCA was improved through three strategies, namely mixed distance function, average similitude degree and probability conversion functions. Then, the ACCA was carried out to obtain different water quality grades in the GIS environment. In the end, the result from the ACCA was compared with those from the competitive Hopfield neural network(CHNN) to validate the feasibility and effectiveness of the ACCA according to three evaluation indexes, which are stochastic sampling method, pixel amount and convergence speed. It is shown that the spatial water quality grades obtained from the ACCA were more effective, accurate and intelligent than those obtained from the CHNN.
文摘The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.
