Title :
Building extraction using lidar data and very high resolution image over complex urban area
Author :
Peijun Li ; Shasha Jiang ; Xue Wang ; Jun Zhang
Author_Institution :
Inst. of Remote Sensing & GIS, Peking Univ., Beijing, China
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.
Keywords :
feature extraction; geophysical image processing; image resolution; image segmentation; remote sensing by laser beam; vegetation mapping; LiDAR data; Quickbird image; complex urban areas; normalized difference vegetation index; post processing method; refinement method; shadow; spectral confusion; urban building extraction method; very high resolution imagery; Accuracy; Buildings; Data mining; Image segmentation; Laser radar; Urban areas; Vegetation; LiDAR; VHR image; building extraction; shadow;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6723773