Characterizing variability of the urban physical environment for a suite of cities in Rondônia, Brazil

Abstract

Urban environments are characterized by high spectral and spatial heterogeneity and, as a consequence, most urban pixels in moderateresolution imagery contain multiple land-cover materials. Despite these complexities, virtually all urban land cover can be generalized as a combination of vegetation, impervious surfaces, and soil (V-I-S components), in addition to water. Previous work has demonstrated the potential of multiple endmember spectral mixture analysis (MESMA) to model the subpixel abundance of V-I-S components. Here, the authors test whether the technique is sufficiently robust to map V-I-S components for a diverse set of cities, selecting 10 urban centers in the state of Rondônia, Brazil, to represent a range of populations, development histories, and economic activities. For each urban sample, a 20 km × 20 km region centered over the built-up area was subset from Landsat Enhanced Thematic Mapper Plus (ETM+) imagery. MESMA was applied to all subscenes using the same spectral library, model constraints, and selection rules. Accu-racy of the modeled V-I-S fractions was assessed using high-resolution images mosaicked from digital aerial videography. Modeled fractions and reference fractions were highly correlated, with R2 values exceeding 0.75 for all materials in multiple cities across a region. Model complexity, or the number of endmembers required to accurately model each pixel, was correlated with the degree of human impact on the landscape. Built-up areas, as delineated by model complexity, exhibited a strong fit to the well-established relationship between the built-up area of a settlement and its population. Finally, this work demonstrates that the V-I-S components as modeled by MESMA can capture both inter- and intraurban variability, suggesting that these data products could contribute to comparative studies of urbanizing areas through time and across regions.