Version 1
: Received: 21 August 2018 / Approved: 21 August 2018 / Online: 21 August 2018 (16:58:09 CEST)
How to cite:
Padmanaban, R.; Cabral, P.; Bhowmik, A.K. Satellite Image Fusion to Detect Changing Surface Permeability and Emerging Urban Heat Islands in a Fast-Growing City. Preprints2018, 2018080388. https://doi.org/10.20944/preprints201808.0388.v1
Padmanaban, R.; Cabral, P.; Bhowmik, A.K. Satellite Image Fusion to Detect Changing Surface Permeability and Emerging Urban Heat Islands in a Fast-Growing City. Preprints 2018, 2018080388. https://doi.org/10.20944/preprints201808.0388.v1
Padmanaban, R.; Cabral, P.; Bhowmik, A.K. Satellite Image Fusion to Detect Changing Surface Permeability and Emerging Urban Heat Islands in a Fast-Growing City. Preprints2018, 2018080388. https://doi.org/10.20944/preprints201808.0388.v1
APA Style
Padmanaban, R., Cabral, P., & Bhowmik, A.K. (2018). Satellite Image Fusion to Detect Changing Surface Permeability and Emerging Urban Heat Islands in a Fast-Growing City. Preprints. https://doi.org/10.20944/preprints201808.0388.v1
Chicago/Turabian Style
Padmanaban, R., Pedro Cabral and Avit K Bhowmik. 2018 "Satellite Image Fusion to Detect Changing Surface Permeability and Emerging Urban Heat Islands in a Fast-Growing City" Preprints. https://doi.org/10.20944/preprints201808.0388.v1
Abstract
Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of urban heat islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they have mostly involved time consuming and expensive field studies, and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and UHI emergence in Tirunelveli, Tamilnadu, India. Cartosat-2 and Landsat-7 ETM+ imageries from 2007 and 2017 were fused and classified using a Rotation Forest (RF), while surface permeability and temperature were quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Fused images exhibited higher classification accuracies than non-fused images, i.e. overall kappa coefficient values 0.83 and 0.75, respectively. We observed an overall increase of 20 km2 (45%) in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease of 27 km2 (37%) for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall (0.4) and also for almost all LULC zones. The LST values exhibited an associated overall increase (1.30C) of surface temperature in Tirunelveli with the highest increase (2.40C) for urban built-up areas between 2007 and 2017. The SAVI-LST combined metric depicted the Southeastern built-up areas in Tirunelveli as a potential UHI hotspot, while a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.
Keywords
Satellite Image Fusion, Land Surface Temperature, Surface Permeability, Landuse and Landcover, Soil Adjusted Vegetation Index, Urban Heat Island, Fast Growing City, Remote sensing
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Alex Martin
The commenter has declared there is no conflict of interests.
Commenter: Oraib Almegdady
The commenter has declared there is no conflict of interests.