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Open AccessArticle

Using Satellite-Borne Remote Sensing Data in Generating Local Warming Maps with Enhanced Resolution

Department of Geomatics Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
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ISPRS Int. J. Geo-Inf. 2018, 7(10), 398; https://doi.org/10.3390/ijgi7100398
Received: 13 September 2018 / Revised: 27 September 2018 / Accepted: 4 October 2018 / Published: 6 October 2018
Warming, i.e., increments of temperature, is evident at the global, regional, and local level. However, understanding the dynamics of local warming at high spatial resolution remains challenging. In fact, it is very common to see extremely variable land cover/land use within built-up environments that create micro-climatic conditions. To address this issue, our overall goal was to generate a local warming map for the period 1961–2010 at 15 m spatial resolution over the southern part of the Canadian province of Alberta. Our proposed methods consisted of three distinct steps. These were the: (i) construction of high spatial resolution enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) maps; (ii) conversion of air temperature (Ta) normal (i.e., 30 years average) at higher spatial resolution using vegetation indices (VI); and (iii) generation of a local warming map at 15m spatial resolution. In order to execute this study, we employed MODIS-driven air temperature data, EVI and NDVI data, and Landsat-driven vegetation indices. The study uncovered that around 58% (up to positive 1 °C) of areas in the considered study region were experiencing increased temperature; whereas only about 4% of areas underwent a cooling trend (more than negative 0.25 °C). The remaining 38% did not exhibit significant change in temperature. We concluded that remote sensing technology could be useful to enhance the spatial resolution of local warming maps, which would be useful for decision-makers considering efficient decisions in the face of increments in local temperature. View Full-Text
Keywords: air temperature normal; enhanced vegetation index; Landsat-8; landscape dynamics; MODIS; normalized difference vegetation index air temperature normal; enhanced vegetation index; Landsat-8; landscape dynamics; MODIS; normalized difference vegetation index
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Rahaman, K.R.; Ahmed, M.R.; Hassan, Q.K. Using Satellite-Borne Remote Sensing Data in Generating Local Warming Maps with Enhanced Resolution. ISPRS Int. J. Geo-Inf. 2018, 7, 398.

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