A global analysis of urban reflectance

• Published in: International journal of remote sensing Vol. 26; no. 4; pp. 661 - 681
• Main Author: Small, C.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Abingdon Taylor & Francis Group 01-02-2005; Taylor and Francis
• Subjects: Applied geophysics; Earth sciences; Earth, ocean, space; Exact sciences and technology; Internal geophysics; physical properties; Thematic Mapper; reflectance; mixing; topology; Space remote sensing; Landsat; vegetation; urban areas; collections; false-color imagery; characterization; albedo
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431160310001654950

A comparative Spectral Mixture Analysis (SMA) of Landsat 7 Enhanced Thematic Mapper (ETM+) imagery for a collection of 28 urban areas worldwide provides a physical basis for a spectral characterization of urban reflectance properties. These urban areas have similar mixing space topologies and can be represented by three-component linear mixture models in both scene-specific and global composite mixing spaces. The results of the analysis indicate that the reflectance of these cities can be accurately described as linear combinations of High Albedo, Dark and Vegetation spectral endmembers within a two-dimensional mixing space containing over 90% of the variance in the observed reflectance. Only two of the 28 cities had greater than 10% median RMS misfit to the three-endmember linear model. The relative proportions of these endmembers vary considerably among different cities and within individual cities but in all cases the reflectance of the urban core lies near the dark end of a mixing line between the High Albedo and Dark endmembers. The most consistent spectral characteristic of the urban mosaic is spectral heterogeneity at scales of 10-20 m. In spite of their heterogeneity, built-up areas do occupy distinct regions of the spectral mixing space. This localization in mixing space allows spectrally mixed pixels in built-up areas to be discriminated from undeveloped land cover types. This provides a basis for mapping the spatial extent of human settlements using broadband optical satellite imagery collected over the past 30 years.