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Delineating urban, suburban and rural areas using Landsat and DMSP-OLS night-time images

机译:使用Landsat和DMSP-OLS夜间图像描绘城市,郊区和农村地区

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The number and size of urban settlements are increasing in all the continents of the world at a rapid pace. Urban sprawl is associated not only with changes in landcover and area, but also ecological, climate and social transformations. Mapping the growth and spread of urban areas is important. Remote sensing has long been used to map human settlements. Today the availability of a large number of satellites and sensors, determining the appropriate image to map urban area is a research area itself. This study compares two satellite images: Landsat Enhanced Thematic Mapper data and Defence Meteorological Satellite Program, Operational Linescan System image to map the urban footprint of the city of Hyderabad, India. Landsat ETM data is captured during the daytime and gives spectral reflectance values while the DMSP-OLS data captures artificial lights from human settlements at night and produces brightness information. The results show an accuracy of more than 90% in the classification and delineation of urban, suburban and rural landcover types. This study shows that in addition to spectral reflectance captured by satellites from different features on the earth surface during the daytime, differences in the degree of brightness of the lights emitted from urban areas at night is also an effective indicator in delineating landcover types.
机译:在世界所有大陆上,城市住区的数量和规模都在迅速增加。城市扩张不仅与土地覆被和面积的变化有关,而且还与生态,气候和社会转型有关。绘制城市地区的增长和扩散图很重要。长期以来,遥感一直被用来绘制人类住区的地图。如今,大量卫星和传感器的可用性,确定用于绘制市区图的适当图像,本身就是一个研究领域。这项研究比较了两个卫星图像:Landsat增强型专题制图仪数据和国防气象卫星计划,Operational Linescan System图像以绘制印度海得拉巴市的城市足迹。 Landsat ETM数据在白天被捕获并提供光谱反射率值,而DMSP-OLS数据在夜间捕获来自人类住区的人造光并产生亮度信息。结果表明,在城市,郊区和农村土地覆被类型的分类和划分中,准确性超过90%。这项研究表明,除了白天白天从地球表面不同特征的卫星捕获的光谱反射率之外,夜间从市区发出的光的亮度程度差异也是确定土地覆被类型的有效指标。

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