A modified approach for change detection using change vector analysis in posterior probability space
The multispectral and multitemporal data coming from satellites allow us to extract valuable spatiotemporal change. Consequently, Earth surface change detection analysis has been used in the past to monitor land cover changes caused by different reasons. Several techniques have been used for that pu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-04-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/593/2015/isprsarchives-XL-7-W3-593-2015.pdf |
| Summary: | The multispectral and multitemporal data coming from satellites allow us to extract valuable spatiotemporal change. Consequently,
Earth surface change detection analysis has been used in the past to monitor land cover changes caused by different reasons. Several
techniques have been used for that purpose and change vector analysis (CVA) has been frequently employed to carry out automatic
spatiotemporal information extraction. This work describes a modified methodology based on Supervised Change Vector Analysis
in Posterior probability Space (SCVAPS) with the final aim of obtaining a change detection map in Blida, Algeria. The proposed
technique is a Modified version of Supervised Change Vector Analysis Posterior probability Space (MSCVAPS) and it is applied at the
same region that the original technique studied in the literature. The classical Maximum Likelihood classifier is the selected method
for supervised classification since it provides good properties in the posterior probability map. An improved method for threshold
determination based on Double Flexible Pace Search (DFPS) is proposed in this work and it is employed to obtain the most adequate
threshold value. Then, the MSCVAPS approach is evaluated by two cases study of the land cover change detection in the region
of Blida, Algeria, and in the region of Shunyi District, Beijing, China, using a pair of Landsat Thematic Mapper images and pair
of Landsat Enhanced Thematic Mapper images, respectively. The final evaluation is given by the overall accuracy of changed and
unchanged pixels and the kappa coefficient. The results show that the modified approach gives excellent results using the same area of
study that was selected in the literature. |
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| ISSN: | 1682-1750 2194-9034 |