2020
DOI: 10.3390/rs12030423
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Towards a Multi-Temporal Deep Learning Approach for Mapping Urban Fabric Using Sentinel 2 Images

Abstract: The major part of the population lives in urban areas, and this is expected to increase in the future. The main challenges faced by cities currently and towards the future are the rapid urbanization, the increase in urban temperature and the urban heat island. Mapping and monitoring urban fabric (UF) to analyze the environmental impact of these phenomena is more necessary than ever. This coupled with the increased availability of Earth observation data and their growing temporal capabilities leads us to consid… Show more

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Cited by 38 publications
(36 citation statements)
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“…Several machine learning methods have been used to perform land monitoring from satellite images, for instance: mapping of urban fabric [84][85][86], crop classification and field boundaries [87,88] and pest detection [89].…”
Section: Satellite Imagingmentioning
confidence: 99%
“…Several machine learning methods have been used to perform land monitoring from satellite images, for instance: mapping of urban fabric [84][85][86], crop classification and field boundaries [87,88] and pest detection [89].…”
Section: Satellite Imagingmentioning
confidence: 99%
“…Several modifications have been added to the original U-Net architecture. Among the most important of these modifications, especially in the field of satellite image processing, is the multi-class image classification on the one hand, and on the other hand, using different encoding branch architectures such as various version VGG Net [37], [38] and ResNet [39]. All these modifications and additions to the encoder-decoder model made it more robust and capable of classifying extremely complex images full of semantic details such as satellite images.…”
Section: Modified Multi-class U-net Architecturementioning
confidence: 99%
“…As the global trend of urbanization is expected to further increase the urban share of the world population from about 55 percent in 2018 to 68 percent by 2050 [3], understanding transformations of urban areas, and navigating those transformations towards more sustainable path-ways is of high societal relevance. Growing urbanization makes urban areas highly dynamic [4], thus, making the research on the detection of land-use patterns of great importance.…”
Section: Introductionmentioning
confidence: 99%
“…In Germany, in general, but also in the German federal state of North Rhine-Westphalia (NRW), parallel development has been observed, with a distinct growth of settlements and transportation infrastructure. In the national sustainability strategy, presented in 2002, the 30-ha goal was introduced by the German government aimed at reducing Germany's land consumption to a maximum of 30 ha per day until 2030 [4]. Although the daily land consumption has declined during the past years, it was still at 10 ha per day in NRW [40].…”
Section: Introductionmentioning
confidence: 99%