Authors: Bikalpa Adhikari*, Department of Geography, School of Liberal Arts, Indiana University - Purdue University Indianapolis, Indiana, Jeffrey Wilson, Department of Geography, School of Liberal Arts, Indiana University - Purdue University Indianapolis, Indiana, Dana Habeeb, Department of Informatics, Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, Indiana, Bhuwan Thapa, Department of Geography, School of Liberal Arts, Indiana University - Purdue University Indianapolis, Indiana, April Michelle Byrne, O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, Indiana, Conor Nolan, School of Global and International Studies,Indiana University, Bloomington,Indiana
Topics: Urban Geography, Geographic Information Science and Systems, Remote Sensing
Keywords: Urban Heat Island, Built Environment, Urban Land Use Classification
Session Type: Poster
Start / End Time: 3:20 PM / 4:35 PM
Room: Virtual Track 3
Presentation File: No File Uploaded
A better understanding of urban climate requires incorporation of information on natural and built environment characteristics at high spatial resolution. The Local Climate Zone (LCZ) classification system has been proposed as a global standard for urban land cover classification based on biophysical characteristics that affect urban climatology at fine spatial scales. The Local Climate Zones system was designed to enhance consistency in field studies of the urban heat island effect but can be extended to broader analyses of urban sustainability in the face of climate change. The goal of this project is to derive a Local Climate Zone classification map for the City of Indianapolis, Indiana using GIS-based methods that calculate Local Climate Zone variables including building morphology and impervious surface. We present preliminary findings of the classification using GIS-based methods. The study is conducted in Central Indianapolis which is characterized by diverse types of environments common to many cities. Plans for future works include comparison of the result with remote sensing-based classification (World Urban Database and Access Portal (WUDAPT) method), and the deployment of sensors to evaluate the reliability of GIS-based methods.