Subpixel Change Detection and Identification Based on SpectralUnmixing: An Application to Change Detection of Landslide
碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 94 === Most of change detection algorithms for multi-temporal images are performed in unit of pixels. Due to the limit of spatial resolution, a pixel is, in many cases, a mixed pixel that consists of more than one ground cover types. We reviewed several spectral unmi...
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| Format: | Others |
| Language: | en_US |
| Published: |
2006
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| Online Access: | http://ndltd.ncl.edu.tw/handle/65839349056953372664 |
| Summary: | 碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 94 === Most of change detection algorithms for multi-temporal images are performed in unit of pixels. Due to the limit of spatial resolution, a pixel is, in many cases, a mixed pixel that consists of more than one ground cover types. We reviewed several spectral unmixing techniques such as independent component analysis (ICA), non-negative matrix factorization (NMF), unsupervised fully constrained least squares linear unmixing (UFCLSLU) and vertex component analysis (VCA). We employed the spectral unmixing techniques to explore subpixel information and to detect subpixel-scale changes. Furthermore, we demonstrated an application of subpixel change detection to detection of landslide expansions. The abundance feature extracted from multispectral images by spectral unmixing was incorporated with the slope feature into the process of landslide change identification based on the post-classification comparison procedure. Our result shows that the subpixel change detection method can provide more detailed information about landslide changes than pixel-based change detection algorithms.
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