Abstract
This paper proposed a novel urban building extraction method to address the problems with shadow and spectral confusion using LiDAR data and very high resolution (VHR) imagery. The buildings were first extracted using height from LiDAR data and normalized difference vegetation index (NDVI) from VHR image. A refinement step was then adopted to reduce the errors caused by shadow and spectral similarity between the buildings with color roofs and vegetated roofs and the trees. A post processing step was finally conducted to further improve the result. The proposed method was quantitatively evaluated and compared with existing method using airborne LiDAR data and Quickbird image. The results indicated that the proposed method significantly outperformed the existing method. The proposed method is applicable for building extraction using VHR image and LiDAR data over complex urban areas with tall buildings and buildings with color roofs or vegetated roofs.
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