DocumentCode
3023454
Title
The characterization of digital surface model from stereo imagery over vegetated areas
Author
Wenjian Ni ; Zhiyu Zhang ; Zhifeng Guo ; Guoqing Sun
Author_Institution
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
fYear
2013
fDate
21-26 July 2013
Firstpage
504
Lastpage
507
Abstract
Some researches in the field of surveying and mapping showed that it held potentials to derive vegetation height from stereo imagery. However, most of current researches were conducted on aerial images or spaceborne images with very high resolutions (about 0.5 m). The resolution of stereo sensors with global coverage is always not so high. The characteristics of digital surface models (DSMs) should be affected by image resolutions because the DSM from stereo imagery was directly determined by the cloud of common points from the pair of stereo images while the automatic recognition of common points depended on the image textures. More stereo imagery has been and will be acquired by ALOS/PRISM and Chinese ZY03 with the resolution of about 2~4 m. Therefore, the characteristics of DSM from high stereo imagery at the resolution of 2-4 m over vegetated areas should be investigated. In this study, an automatic procedure for the extraction of DSM from stereo imagery and a method for the estimation of vegetation height from DSM were proposed. The experiments results showed that the method for the automatic extraction of DSM worked well and the estimation of vegetation height was valid at sparse forest.
Keywords
digital elevation models; geophysical image processing; image recognition; image resolution; surveying; vegetation mapping; ALOS PRISM data; Chinese ZY03 data; aerial images; automatic recognition; digital surface model; image resolution; mapping; spaceborne images; stereo imagery; surveying; vegetated areas; vegetation height; Correlation; Estimation; Image resolution; Laser radar; Remote sensing; Vegetation; Vegetation mapping; DSM; photogrammetry; stereo imagery; vegetation height;
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.2013.6721203
Filename
6721203
Link To Document