Paper
9 October 2009 Hyperspectral remote sensing for land degradation mapping in China
Jing Wang, Ting He, Yuhuan Li, Yongqi Chen, Chunyan Lv
Author Affiliations +
Proceedings Volume 7471, Second International Conference on Earth Observation for Global Changes; 74710M (2009) https://doi.org/10.1117/12.836437
Event: Second International Conference on Earth Observation for Global Changes, 2009, Chengdu, China
Abstract
Land degradation is a major environmental problem internationally. Soil degradation is one of the key factors of land degradation, which is related to susceptibility to erosion, soil suitability, and soil characteristics especially at regional scale. It is important and meaningful to evaluate objectively land degradation at regional scale. The study is to present the classification approaches for land degradation by Degraded Soil Line Index (DSLI) and object-oriented method by determination of land degradation spectral response units (DSRU) compared to the spectral angle mapping (SAM) method using Hyperion image data for mapping land degradation. The method was tested in a study area located in Hengshan county in ShaanXi province, China, where is in the agriculture-pasture mixed area in Loess Plateau in China with complex physical geographical situation. The results showed that the three methods of SAM, DSLI and DSRU have the ability to map land degradation and degraded soil classes, and the performance of the methods of DSLI and SAM is different and DSLI is prior to SAM for land degradation mapping in the study area. Moreover, the results also showed that the object-oriented analysis method based on DSRU approach is valid for extraction of land degradation information and clearly shows the degraded land classes with an overall accuracy of 0.88 and Kappa coefficients of 0.86.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jing Wang, Ting He, Yuhuan Li, Yongqi Chen, and Chunyan Lv "Hyperspectral remote sensing for land degradation mapping in China", Proc. SPIE 7471, Second International Conference on Earth Observation for Global Changes, 74710M (9 October 2009); https://doi.org/10.1117/12.836437
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Remote sensing

Soil science

Associative arrays

Vegetation

Image segmentation

Image classification

Agriculture

Back to Top