International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-4/W19
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W19, 361–367, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W19-361-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W19, 361–367, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W19-361-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  23 Dec 2019

23 Dec 2019

SPATIO-TEMPORAL ANALYSIS OF URBAN HEAT ISLAND IN MANDAUE CITY, PHILIPPINES

A. M. Rejuso1, A. C. Cortes2, A. C. Blanco1,3, C. A. Cruz1, and J. B. Babaan1 A. M. Rejuso et al.
  • 1UP Training Center for Applied Geodesy and Photogrammetry, College of Engineering, University of the Philippines, Diliman, Quezon City 1101, Philippines
  • 2Department of Biology and Environmental Science, College of Science University of the Philippines Cebu, Cebu City, Philippines
  • 3Department of Geodetic Engineering, University of the Philippines, Diliman, Quezon City, Philippines

Keywords: Climate Engine, land surface temperature, urban thermal environment, normalized built-up index, normalized vegetation index, normalized water index

Abstract. Extensive urbanization alters the natural landscape as vegetation were replaced with infrastructures composed of materials with low albedo and high heat capacity often resulting to increase in land surface temperatures (LST). The present study focused on the spatial and temporal variations of LST in Mandaue City, one of the metropolitan cities in the Philippines that had undergone a rapid rate of urbanization over the past years. Climate Engine (CE), a cloud computing tool that processes satellite images, was used in this study. Preprocessed LST, normalized difference water index (NDWI), normalized difference vegetation index (NDVI), shortwave infrared (SWIR 1) and near-infrared (NIR) layers were directly downloaded from CE while the normalized difference built-up index (NDBI) maps were calculated. Time-series dataset of these indices were analyzed to determine the impacts of reduced vegetation cover and increased built-up areas on surface temperature from years 2013 to 2019. The spatial distribution of LST were analyzed using Univariate Local Moran’s I in GeoDa to identify hotspots within the city. Analysis results showed that the hotspots are barangays Tipolo (100%), Bakilid (100%), Ibabao-Estancia (93.5%), Alang-Alang (87.2%), Guizo (84.4%), Subangdaku (84.1%), and Centro (79.4%). The results indicated that there is a linear relationship between LST and NDBI (r = 0.659, p < 0.01) while an inverse relationship was observed between LST with NDVI (r = −0.527, p < 0.1) and NDWI (r = −0.620, p < 0.01).