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Land-Use/Land-Cover Change Detection Using Improved Change-Vector Analysis
Open accessAbstract
Change-vector analysis (CVA) is a valuable technique for land-use/land-cover change detection. However, how to reasonably determine thresholds of change magnitude and change direction is a bottleneck to its proper application. In this paper, a new method is proposed to improve CVA. The method (the improved CVA) consists of two stages, Double-Window Flexible Pace Search (DFPS), which aims at determining the threshold of change magnitude, and direction cosines of change vectors for determining change direction (category) that combines single-date image classification with a minimum-distance categorizing technique. When the improved CVA was applied to the detection of the land-use/land-cover changes in the Haidian District, Beijing, China, Kappa coefficients of “change/no-change” detection and “from-to” types of change detection were 0.87 and greater than 0.7, respectively, for all kinds of land-use changes. The experimental results indicate that the improved CVA has good potential in land-use/land-cover change detection.
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Cited by
He, C., Shi, P., Xie, D., & Zhao, Y. (2010) · Remote Sensing Letters · doi:10.1080/01431161.2010.481681 · Cited by 373
Self-citationVegetation Dynamics in Yellowstone’s Northern Range: 1985 to 1999
Savage, S. L., & Lawrence, R. L. (2010) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.76.5.547 · Cited by 16
Metadata
- Authors
- Chen, J., Gong, P., He, C., Pu, R., & Shi, P.
- Venue
- Photogrammetric Engineering & Remote Sensing
- Published
- 2003-04-01
- Volume
- 69
- Issue
- 4
- Pages
- 369-379
- ISSN
- 0099-1112 (ISSN-L)
- OpenAlex
- W2167093797
- Cited by
- 383
- References
- 0
- FWCI
- 15.07
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Chen, J., Gong, P., He, C., Pu, R., & Shi, P. (2003). Land-Use/Land-Cover Change Detection Using Improved Change-Vector Analysis. Photogrammetric Engineering & Remote Sensing. https://doi.org/10.14358/pers.69.4.369
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