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Proceedings Paper

Saline-alkali land classification using MODIS data In Western Jilin Province, China
Author(s): Lingjia Gu; Ruizhi Ren; Junsheng Cao; Jian Sun
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Paper Abstract

Remote sensing technology can extract useful information from observation areas, meanwhile provide effective data for land monitoring, which is widely used in dynamic monitoring and resources research of saline alkali land. Through using MODIS spectral remote sensing data, a case study of Western Jilin Province of China mainly covered by typical saline alkali land was carried out in this paper. After using the proposed optimal band combination method, the main distribution positions of the observed saline alkali land were roughly determined based on the colors and shapes of MODIS images derived from deferent seasons. After analyzing the time series of NDVI observations, the decision tree classification of land cover was designed to determine the land cover types and the degree of salinity-alkalinity. Through obtaining and analyzing of the spectral characteristics of each saline alkali land type, the relationship between the spectral characteristics and saline alkali land type was deduced. The research results demonstrated that the saline alkali lands located in Western Jilin Province, China were effectively classified based on the spectral characteristics of MODIS data, which provided the moderate spatial resolution classification results for a wide range of saline alkali land monitoring.

Paper Details

Date Published: 24 September 2013
PDF: 10 pages
Proc. SPIE 8871, Satellite Data Compression, Communications, and Processing IX, 88710A (24 September 2013); doi: 10.1117/12.2022433
Show Author Affiliations
Lingjia Gu, Jilin Univ. (China)
Ruizhi Ren, Jilin Univ. (China)
Junsheng Cao, Changchun Institute of Optics, Fine Mechanics and Physics (China)
Jian Sun, Jilin Univ. (China)

Published in SPIE Proceedings Vol. 8871:
Satellite Data Compression, Communications, and Processing IX
Bormin Huang; Antonio J. Plaza; Chein-I Chang, Editor(s)

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