Spectral resolution requirements for mapping urban areas

This study evaluated how spectral resolution of high-spatial resolution optical remote sensing data influences detailed mapping of urban land cover. A comprehensive regional spectral library and low altitude data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) were used to characterize the spectral properties of urban land cover. The Bhattacharyya distance was applied as a measure of spectral separability to determine a most suitable subset of 14 AVIRIS bands for urban mapping. We evaluated the performance of this spectral setting versus common multispectral sensors such as Ikonos by assessing classification accuracy for 26 urban land cover classes. Significant limitations for current multispectral sensors were identified, where the location and broadband character of the spectral bands only marginally resolved the complex spectral characteristics of the urban environment, especially for built surface types. However, the AVIRIS classification accuracy did not exceed 66.6% for 22 urban cover types, primarily due to spectral similarities of specific urban materials and high within-class variability.

I. Introduction

Urban environments represent one of the most challenging areas for remote sensing analysis due to high spatial and spectral diversity of surface materials. Typical urban surface types include a wide range of roofs, roads, sidewalks and parking lots of variable age, quality and composition. Further complicating the urban landscape are bare soil, vegetation, and other landscaping elements, creating a spectral diversity that far exceeds natural environments. This complexity, along with three-dimensional surface heterogeneity, creates a particularly challenging mapping environment for urban areas [1]–[4].