Paper
7 November 2008 Extracting shelter forest in semi-arid sandy area based on Landsat ETM+ imagery
Xin Qi, Fang Huang, Yina Qi
Author Affiliations +
Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 71470Q (2008) https://doi.org/10.1117/12.813227
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China
Abstract
Taking a sub-area of semi-arid west Jilin Province as example, we mainly discuss the method of shelter forest extraction in sandy area from Landsat-7 ETM+ imagery in this study. After the comparison of the image fusion methods including HIS transforms, PCA transforms, Brovey transforms and Wavelet transforms, the method of Brovey transforms improved by wavelet analysis is presented for further processing. The details information in fused ETM+ image by this improved method is more considerable and fruitful. Using unsupervised classification in combination with supervised classification and threshold method based on NDVI, we extract the farmland shelterbelts from the fusion image finally. The accuracy of classification is more than 85%. From the experiment result, this method shows a better performance in the shelter forest extraction in a typical semi-arid sandy.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xin Qi, Fang Huang, and Yina Qi "Extracting shelter forest in semi-arid sandy area based on Landsat ETM+ imagery", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470Q (7 November 2008); https://doi.org/10.1117/12.813227
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KEYWORDS
Image fusion

Transform theory

Vegetation

Remote sensing

Image classification

Principal component analysis

Earth observing sensors

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