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Urban land cover thematic disaggregation,employing datasets from multiple sources and RandomForests modeling
Institution:1. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, CAS, No. 20 Nanxincun, Xiangshan, Beijing 100093, PR China;2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, 11A, Datun Road, Chaoyang District, Beijing 100101, PR China;3. State Key Laboratory of Atmospheric Boundary Layer, Institute of Atmospheric Physics and Atmospheric Chemistry, CAS, Chaoyang District, P.O. Box 9804, Beijing 100029, PR China;4. Department of Livestock Production, Ministry of Agriculture, No. 11 Nongzhanguan Nanli, Chaoyang District, Beijing 100125, PR China;1. National Water and Energy Center, UAE University, P.O. Box 15551, Al Ain, United Arab Emirates;2. Civil and Environmental Eng. Dept., College of Engineering, UAE University, P.O. Box 15551, Al Ain, United Arab Emirates
Abstract:Urban land cover mapping has lately attracted a vast amount of attention as it closely relates to a broad scope of scientific and management applications. Late methodological and technological advancements facilitate the development of datasets with improved accuracy. However, thematic resolution of urban land cover has received much less attention so far, a fact that hampers the produced datasets utility. This paper seeks to provide insights towards the improvement of thematic resolution of urban land cover classification. We integrate existing, readily available and with acceptable accuracies datasets from multiple sources, with remote sensing techniques. The study site is Greece and the urban land cover is classified nationwide into five classes, using the RandomForests algorithm. Results allowed us to quantify, for the first time with a good accuracy, the proportion that is occupied by each different urban land cover class. The total area covered by urban land cover is 2280 km2 (1.76% of total terrestrial area), the dominant class is discontinuous dense urban fabric (50.71% of urban land cover) and the least occurring class is discontinuous very low density urban fabric (2.06% of urban land cover).
Keywords:Urban land cover  Thematic disaggregation  Urban atlas  Landsat  RandomForests
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