Journal
GISCIENCE & REMOTE SENSING
Volume 52, Issue 6, Pages 700-722Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/15481603.2015.1071965
Keywords
arid and semiarid urban landscapes; fractional land cover; change detection; multitemporal Landsat imagery
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Funding
- Zhejiang A&F University's Research and Development Fund [2013FR052]
- National Science Foundation of China [31170347]
- 'Hundred Talents Program' of the Chinese Academy of Sciences
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Pixel-based approaches are commonly used for urban land-cover classification and change detection, but the results are often inaccurate in arid and semiarid urban landscapes due to the mixed-pixel problem and similar spectral signatures between impervious surface areas (ISAs) and bare soils. This research proposes a subpixel-based approach to examine land-cover change in Urumqi and Phoenix urban landscapes using multitemporal Landsat Thematic Mapper (TM) imagery. Linear spectral mixture analysis (SMA) was used to unmix TM multispectral imagery into four fractions -high-albedo object, low-albedo object, green vegetation (GV), and soil. ISA was determined from the sum of high-albedo and low-albedo fraction images after removal of non-ISA in both fraction images. The ISA, vegetation abundance, and soil images at different dates were used to examine their change over time. The results indicate that this subpixel-based approach can successfully detect small changes of urban land covers in medium spatial resolution images which pixel-based approaches cannot.
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