共查询到4条相似文献,搜索用时 0 毫秒
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Hongchao Fan Bisheng Yang Alexander Zipf Adam Rousell 《International journal of geographical information science》2016,30(4):748-764
Matching road networks is an essential step for data enrichment and data quality assessment, among other processes. Conventionally, road networks from two datasets are matched using a line-based approach that checks for the similarity of properties of line segments. In this article, a polygon-based approach is proposed to match the OpenStreetMap road network with authority data. The algorithm first extracts urban blocks that are central elements of urban planning and are represented by polygons surrounded by their surrounding streets, and it then assigns road lines to edges of urban blocks by checking their topologies. In the matching process, polygons of urban blocks are matched in the first step by checking for overlapping areas. In the second step, edges of a matched urban block pair are further matched with each other. Road lines that are assigned to the same matched pair of urban block edges are then matched with each other. The computational cost is substantially reduced because the proposed approach matches polygons instead of road lines, and thus, the process of matching is accelerated. Experiments on Heidelberg and Shanghai datasets show that the proposed approach achieves good and robust matching results, with a precision higher than 96% and a F1-score better than 90%. 相似文献
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Journal of Geographical Sciences - Based on the carrying capacity of the resources and the environment, this article defines the connotation of the land multifunctional space (LMFS) from three... 相似文献
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Mun-Hyun Jang 《International journal of geographical information science》2013,27(8):1393-1413
The objective of this study is the production and visualization of an emotional map to reveal the unique emotions inherent to the areas surrounding the Yeongsan River, which is often referred to as ‘the cradle of civilization’ in Korea. The sites selected for this study are the 11 cities and districts (5667.6 km2) that cut across the vast granary in the southeastern region of Korea, near the Yeongsan River. The emotional map was produced by extracting features of historical and cultural heritage distributed throughout this region and by using a geographic information systems program and its functions for spatial analysis. A database was constructed through interviews with locals and Global Positioning System to index 4318 pieces of cultural heritage to achieve the visualization of emotions. Among the 558 historical relics considered for representing the regional culture, 100 with the largest emotional impact were selected. It was determined that loyalty (), justice (), courtesy (), resentment (), and anger () should be the major emotional elements. Methodologically, a set of regional, periodic, historical, and emotional classification codes were first systematized. After subjecting this data to inverse distance weight interpolation and vertical exaggeration coefficients, the three-dimensional emotional map could be visualized. 相似文献