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- W1761030516 abstract "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 resol..." @default.
- W1761030516 created "2016-06-24" @default.
- W1761030516 creator A5015848806 @default.
- W1761030516 creator A5055794991 @default.
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- W1761030516 date "2015-07-29" @default.
- W1761030516 modified "2023-09-24" @default.
- W1761030516 title "Detecting fractional land-cover change in arid and semiarid urban landscapes with multitemporal Landsat Thematic mapper imagery" @default.
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- W1761030516 doi "https://doi.org/10.1080/15481603.2015.1071965" @default.
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