Using OpenStreetMap (OSM) to enhance the classification of local climate zones in the framework of WUDAPT

15834 10 87215 3 247783 document 87215 OSM2LCZ-For open access.pdf application/pdf 1f3772ebe69feb8bde5637dbaffc6b97 MD5 4663747 2019-04-11 06:02:10 https://pure.iiasa.ac.at/id/eprint/15834/1/OSM2LCZ-For%20open%20access.pdf 15834 1 1 application/pdf text en public cc_by_nc_4

OSM2LCZ-For open access.pdf

accepted 87216 2 247786 document 87216 lightbox.jpg image/png 5f2ac53c8cfd2c694c5b9148ee09c83f MD5 48193 2019-04-11 06:02:42 https://pure.iiasa.ac.at/id/eprint/15834/2/lightbox.jpg 15834 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en staffonly

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/87215 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/87215 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/87215 archive 353 disk0/00/01/58/34 2019-04-08 06:41:38 2021-08-27 17:31:37 2019-04-08 06:41:38 article show Fonte C.C. Lopes P. See L. 8571 0000-0002-2665-7065 Bechtel B. Using OpenStreetMap (OSM) to enhance the classification of local climate zones in the framework of WUDAPT pub prog_esm Local climate zones; Remote sensing; World urban database and access portal tools; (WUDAPT); Volunteered geographic information; OpenStreetMap The World Urban Database and Access Portal Tools (WUDAPT) project has adopted the LocalClimate Zone (LCZ) scheme as a basic and consistent description of form and function of cities atneighbourhood scale. LCZs are classified using crowdsourced training samples, open data andopen source software but the quality of the maps still needs improvement. The aim of this paperis to investigate the use of data from OpenStreetMap (OSM) to enhance the development of LCZs,complement the existing data sources, and improve the accuracy of the maps. Various featureswere derived from the OSM database and combined with seasonal LCZ maps. Therefore amethodology was developed and tested for Hamburg, Germany, using a fuzzy approach and thena weighted combination method was applied to combine the inputs from OSM with each of theseasonal LCZ maps. The results showed that improvements can be achieved for certain classes,either in terms of accuracy, e.g. rectifying the misclassification of agricultural areas as heavyindustry, or representation on the map, e.g. a more detailed water network. The approach developedis flexible and allows for knowledge about which data sources are more reliable as inputsto the combination and weighting process. 2019 published Elsevier 10.1016/j.uclim.2019.100456 276 public Urban Climate 28 e100456 TRUE 2212-0955 FALSE no info:eu-repo/semantics/article