Cart (Loading....) | Create Account
Close category search window
 

Modeling Urban Heat Islands and Their Relationship With Impervious Surface and Vegetation Abundance by Using ASTER Images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Qihao Weng ; Indiana State Univ., Terre Haute, IN, USA ; Rajasekar, U. ; Xuefei Hu

An important issue in urban thermal remote sensing is how to use pixel-based measurements of land surface temperature (LST) to characterize and quantify the urban heat island (UHI) observed at the mesoscale and macroscale. Characterization and modeling of UHIs must consider the inherent spatial nonstationarity within land surface variables. This study extended a kernel convolution modeling method for 2-D LST imagery to characterize and model the UHI in Indianapolis, IN, as a Gaussian process. To understand the UHI pattern over space and time, four Advanced Spaceborne Thermal Emission and Reflection Radiometer images of different seasons/years were acquired and analyzed. Furthermore, we employed linear spectral mixture analysis to extract subpixel urban biophysical variables [i.e., green vegetation (GV) and impervious surface (IS)] and developed new indexes of greenness and imperviousness based on the convoluted images of GV and IS fractions. These indexes were proposed to show the contrast in the urban-rural biophysical environmental conditions. Results indicate that the UHI intensity possessed a stronger correlation with both greenness and imperviousness indexes than with GV and IS abundance. Because this study utilized a smoothing kernel to characterize the local variability of urban biophysical parameters, including LST, characterized UHIs can therefore be examined as a scale-dependent process. To this end, we categorized the smoothing parameters into three groups, corresponding to the three scales that are suitable to studying the urban thermal landscape at the microscale, mesoscale, and regional scale, respectively. The identified scales can then be matched with various applications in urban planning and environmental management.

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:49 ,  Issue: 10 )

Date of Publication:

Oct. 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.