DocumentCode
3071678
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
fYear
2013
fDate
21-26 July 2013
Firstpage
4253
Lastpage
4256
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location
Melbourne, VIC
ISSN
2153-6996
Print_ISBN
978-1-4799-1114-1
Type
conf
DOI
10.1109/IGARSS.2013.6723773
Filename
6723773
Link To Document