| Technology and Methodology |
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Land Use Change Detection Based on Class Spectral Change Rule |
| WANG Yan1, SHU Ning1,2, GONG Yan1, LI Xue3 |
1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
3. Institute of Seismology, China Earthquake Administration, Wuhan 430071, China |
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Abstract This paper gives a proposal for land use change detection using high resolution remote sensing images based on class spectral change rules. Image segments and their class properties can be obtained by matching remote sensing images and land use map. Then the spectral distribution curve of each feature of the segments belonging to the same class is constructed for each image. Based on these curves, the spectral change rule of each class can be obtained by calculating fitting parameters of cubic polynomial. According to these parameters a change threshold is set and, through iteration, the image segments whose spectral change does not comply with the spectral change rule of their class are detected as the change segments. Two multispectral Quickbird images of part of Wuhan City obtained from 2002 and 2005 and a 1:10 000 land use map of 2002 in the same region were used as the study area. Exemplified by green land and urban areas, the results show the validity of this method.
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| Keywords
artificial neural network(ANN)
remote sensing reflectance
retrieve
absorption coefficient
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Issue Date: 20 August 2012
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2012,
Vol. 24
