Fusion of remote sensing images and GIS data for land use/cover change detection

Hongyan Guo; Yaolin Liu; Gang Liu; Dan Chen; Zeying Lan; Dianfeng Liu

doi:10.1117/12.838401

13 October 2009 Fusion of remote sensing images and GIS data for land use/cover change detection

Hongyan Guo, Yaolin Liu, Gang Liu, Dan Chen, Zeying Lan, Dianfeng Liu

Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 749205 (2009) https://doi.org/10.1117/12.838401
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China

Abstract

Recently land use/cover change detection (LUCC) has become an important aspect in nature resource and environment monitoring and protection. A data fusion method for LUCC is presented concerning the situation that there are only the remote sensing (RS) images of updated period and the land use/cover maps of original period. Firstly, multi-spectral and panchromatic images of SPOT-5 are fused by using principle component analysis (PCA) algorithm on Erdas Imagine platform. Then, after the co-registration of the land use/cover map and RS image, the RS image of the updated period is classified by K-means algorithm and the precise classification chart of the land use/cover is obtained. The land use/cover map is transformed from vector to raster format and the land class code is used as each pixel's value of the transformed raster image. Finally, land use/cover changes are found by comparing the corresponding land class codes. The study area is located in Huangpi District of Wuhan City, and experiments demonstrate the proposed data fusion method for land use/cover change detection is a feasible resolution.

Citation Download Citation

Hongyan Guo, Yaolin Liu, Gang Liu, Dan Chen, Zeying Lan, and Dianfeng Liu "Fusion of remote sensing images and GIS data for land use/cover change detection", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 749205 (13 October 2009); https://doi.org/10.1117/12.838401

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