Estimating impervious surfaces from medium spatial resolution imagery: a comparison between fuzzy classification and LSMA
Impervious surfaces are important environmental indicators and are related to many environmental issues, such as water quality, stream health and the urban heat island effect. Therefore, detailed impervious surface information is crucial for urban planning and environment management. To extract impervious surfaces from remote sensing imagery, many algorithms and techniques have been developed. However, there are still debates over the strengths and limitations of linear versus nonlinear algorithms in handling mixed pixels in the urban landscapes.