Abstract
Since their introduction in 2012, Local Climate Zones (LCZs) emerged as a new standard for characterizing urban landscapes, providing a holistic classification approach that takes into account micro-scale land-cover and associated physical properties. In 2015, as part of the community-based World Urban Database and Access Portal Tools (WUDAPT) project, a protocol was developed that enables the mapping of cities into LCZs, using freely available data and software packages, yet performed on local computing facilities. The LCZ Generator described here further simplifies this process, providing an online platform that maps a city of interest into LCZs, solely expecting a valid training area file and some metadata as input. The web application (available athttps://lcz-generator.rub.de) integrates the state-of-the-art of LCZ mapping, and simultaneously provides an automated accuracy assessment, training data derivatives, and a novel approach to identify suspicious training areas. As this contribution explains all front- and back-end procedures, databases, and underlying datasets in detail, it serves as the primary “User Guide” for this web application. We anticipate this development will significantly ease the workflow of researchers and practitioners interested in using the LCZ framework for a variety of urban-induced human and environmental impacts. In addition, this development will ease the accessibility and dissemination of maps and their metadata.
Highlights
Urbanization and climate change may be the two most important trends to shape global development in the decades ahead
The Local Climate Zones (LCZs) Generator web application described here further simplifies this process, as it provides an online platform that maps a city of interest into LCZs, solely expecting a valid TA file and some metadata as input
Since their introduction in 2012 (Stewart and Oke, 2012), Local Climate Zones (LCZs) emerged as a new standard for characterizing urban landscapes, providing a holistic classification approach that takes into account micro-scale landcover and associated physical properties (Demuzere et al, 2020a)
Summary
Urbanization and climate change may be the two most important trends to shape global development in the decades ahead. The TA dataset is used to extract spectral information from L8 images, which in turn is used in a supervised random forest classifier to categorize the entire region of interest into LCZ types This procedure was afterwards adopted by the World Urban Database and Access Portal Tools (WUDAPT) community project to create consistent LCZ maps of global cities (Ching et al, 2018). The second employs Google’s Earth Engine (EE)—a cloud-based platform for planetary-scale analysis (Gorelick et al, 2017)— to use its computational power, access to a range of geospatial datasets (Landsat, Sentinel, and others) and a large number of predefined algorithms Among others, this cloud-based approach resulted in high-resolution Local Climate Zone maps for global cities, Europe and the continental United States of America (Bechtel et al, 2019a,b; Demuzere et al, 2019a,b,c, 2020a,b; Brousse et al, 2020a). As this contribution explains all front- and back-end procedures, databases and underlying datasets in detail, it serves as the primary “User Guide” for this web application
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
