A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Having realized that the vegetation–impervious surface–soil (V‐I‐S) model may be used as a method to define standardized urban landscape components, this chapter employs linear spectral mixture analysis (LSMA) as a remote sensing technique to estimate and map V‐I‐S components in order to analyze urban pattern and dynamics. Because of the significance of impervious surface as an urban land cover, land use, or material, the chapter examines data requirements for remote sensing of impervious surfaces, with a particular interest in the impacts of remotely sensed data characteristics (i.e. spectral, temporal, and spatial resolutions). It applies the V‐I‐S concept for a spatial‐temporal analysis of the urban morphology in Indianapolis with LSMA, and by doing so, the potentials and limitations of this model for characterizing and quantifying urban landscape components can further be examined.
Having realized that the vegetation–impervious surface–soil (V‐I‐S) model may be used as a method to define standardized urban landscape components, this chapter employs linear spectral mixture analysis (LSMA) as a remote sensing technique to estimate and map V‐I‐S components in order to analyze urban pattern and dynamics. Because of the significance of impervious surface as an urban land cover, land use, or material, the chapter examines data requirements for remote sensing of impervious surfaces, with a particular interest in the impacts of remotely sensed data characteristics (i.e. spectral, temporal, and spatial resolutions). It applies the V‐I‐S concept for a spatial‐temporal analysis of the urban morphology in Indianapolis with LSMA, and by doing so, the potentials and limitations of this model for characterizing and quantifying urban landscape components can further be examined.
Urban Mapping Requirements
Weng, Qihao (author)
2019-11-01
32 pages
Article/Chapter (Book)
Electronic Resource
English
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