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.
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