Z. Mitraka, F. Frate, N. Chrysoulakis, J. Gastellu-Etchegorry
{"title":"Exploiting Earth Observation data products for mapping Local Climate Zones","authors":"Z. Mitraka, F. Frate, N. Chrysoulakis, J. Gastellu-Etchegorry","doi":"10.1109/JURSE.2015.7120456","DOIUrl":null,"url":null,"abstract":"Earth Observation (EO) systems and the advances in remote sensing technology increase the opportunities for monitoring the thermal behaviour of cities. Several parameters related to the urban climate can be quantified from EO data products, providing valuable support for advanced urban studies and climate modelling. In this study, remote sensing techniques are applied to derive quantitative information necessary to identify the Local Climate Zones (LCZ). Parameters like the pervious and impervious surface fraction, the surface albedo, the building density, the mean building/tree height and the sky view factor are quantified and used to map possible zones with homogeneous thermal characteristics, considered as LCZ.","PeriodicalId":207233,"journal":{"name":"2015 Joint Urban Remote Sensing Event (JURSE)","volume":"361 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Joint Urban Remote Sensing Event (JURSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/JURSE.2015.7120456","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 28
Abstract
Earth Observation (EO) systems and the advances in remote sensing technology increase the opportunities for monitoring the thermal behaviour of cities. Several parameters related to the urban climate can be quantified from EO data products, providing valuable support for advanced urban studies and climate modelling. In this study, remote sensing techniques are applied to derive quantitative information necessary to identify the Local Climate Zones (LCZ). Parameters like the pervious and impervious surface fraction, the surface albedo, the building density, the mean building/tree height and the sky view factor are quantified and used to map possible zones with homogeneous thermal characteristics, considered as LCZ.