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Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities†
1K
Citations
24
References
1995
Year
EngineeringUrban ModellingLand UseUrban VegetationLand CoverSocial SciencesUrban Land UseVegetation-impervious Surface-soilUrban Ecosystem AnalysisVegetation-atmosphere InteractionsUrban EnvironmentGeographyUrban EcologyLand Cover MapUrban GeographyUrban MorphologyUrban Change DetectionGrowth ModellingRemote SensingUrban BiodiversityUrban Systems
Growing interest in urban systems as ecological entities calls for standards to parameterize their biophysical composition. The V‑I‑S model may serve as a foundation for universally characterizing urban/near‑urban environments, comparing urban morphology within and between cities, and enabling global urban ecosystem analysis driven by satellite data. The model is a vegetation‑impervious surface‑soil framework that can be driven by satellite digital data to standardize urban ecosystem analysis worldwide. The V‑I‑S model is useful for urban change detection, growth modelling, environmental impact analysis, energy and water investigations, and aspects of human ecosystem analysis.
Abstract Growing interest in urban systems as ecological entities calls for some standards in parameterizing biophysical composition of urban environments. A vegetation-impervious surface-soil ( V-I-S) model is presented as a possible basis for standardization. The V-I-S model may serve as a foundation for characterizing urban/near-urban environments universally, and for comparison of urban morphology within and between cities. Inasmuch as the model may be driven by satellite digital data, it may serve as a global model of urban ecosystem analysis and comparison world-wide. The V-I-S model may prove useful for urban change detection and growth modelling, for environmental impact analysis from urbanization, for energy- and water-related investigations, and for certain dimensions of human ecosystem analysis of the city as well.
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