用高分卫星数据建3D城市模型,估算镇区人口。
Population estimation using 3D city modelling and Carto2S datasets -- A case study
- 结合多视角卫星影像生成高精度地形与建筑高度数据。
- 通过建筑高度和面积推算楼层数与户型数,估算人口规模。
- 融合开放街图信息,适合城市规划与基层决策者使用。
随着Carto2S系列卫星的发射,可获取0.6至1.0米分辨率的高清影像。利用C2S多时相、多视角数据,可生成高精度数字高程模型(DEM),进而导出数字地表模型(DTM),并提取地表建筑物与树木的准确高度。经地面控制点验证后,建筑高度可用于城市建模及资源估算,如人口、医疗、供水与交通规划。本研究基于高分辨率印度遥感卫星数据,采用Carto2S多视角数据生成某城区精确的DEM与DTM。利用这些数据提取建筑物高度,并与实地数据比对验证。结合高分辨率影像与建筑高度信息,构建精准的三维虚拟城市模型,推算住宅楼层数与建筑面积。进一步从开放街图(OSM)提取居民区周边医院与学校数量,结合上述信息进行人口估算。该方法为地方政府与决策者提供了一种高效的人口评估工具。
原文摘要 · Abstract (English)
With the launch of Carto2S series of satellites, high resolution images (0.6-1.0 meters) are acquired and available for use. High resolution Digital Elevation Model (DEM) with better accuracies can be generated using C2S multi-view and multi date datasets. DEMs are further used as an input to derive Digital terrain models (DTMs) and to extract accurate heights of the objects (building and tree) over the surface of the Earth. Extracted building heights are validated with ground control points and can be used for generation of city modelling and resource estimation like population estimation, health planning, water and transport resource estimations. In this study, an attempt is made to assess the population of a township using high-resolution Indian remote sensing satellite datasets. We used Carto 2S multi-view data and generated a precise DEM and DTM over a city area. Using DEM and DTM datasets, accurate heights of the buildings are extracted which are further validated with ground data. Accurate building heights and high resolution imagery are used for generating accurate virtual 3D city model and assessing the number of floor and carpet area of the houses/ flats/ apartments. Population estimation of the area is made using derived information of no of houses/ flats/ apartments from the satellite datasets. Further, information about number of hospital and schools around the residential area is extracted from open street maps (OSM). Population estimation using satellite data and derived information from OSM datasets can prove to be very good tool for local administrator and decision makers.
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