Spatial Metrics and Image Texture for Mapping Urban Land Use

TLDR

The arrival of new‑generation, high‑spatial‑resolution satellite imagery (e.g., Ikonos) has opened up new opportunities for detailed mapping and analysis of urban land use. This study investigates an object‑oriented method to classify a large urban area into detailed land‑use categories, drawing on traditional aerial photointerpretation approaches. The object‑oriented classification employs spatial metrics and texture measures to describe the spatial characteristics of land‑cover objects within each land‑use region derived from interpreted aerial photographs. Spatial metrics proved most informative for distinguishing urban land uses, enabling the derivation of a nine‑category land‑use map for the Santa Barbara South Coast Region and suggesting that region‑based methods using spatial metrics and texture measurements offer a promising avenue for extracting detailed urban land‑use information from high‑resolution satellite imagery.

Abstract

The arrival of new-generation, high-spatial-resolution satellite imagery (e.g., Ikonos) has opened up new opportunities for detailed mapping and analysis of urban land use. Drawing on the traditional approach used in aerial photointerpretation, this study investigates an “object-oriented” method to classify a large urban area into detailed land-use categories. Spatial metrics and texture measures are used to describe the spatial characteristics of land-cover objects within each land-use region as derived from interpreted aerial photographs. In assessing how land-use categories vary in their spatial configuration, spatial metrics were found to provide the most important information for differentiating urban land uses. A detailed land-use map with nine categories was derived for the Santa Barbara South Coast Region area. Results from our work suggest that the region-based method exploiting spatial metrics and texture measurements is a potential new avenue to extract detailed urban land-use information from highresolution satellite imagery.