Assessment of Intra-Urban Heat Island in a Densely Populated City Using Remote Sensing: A Case Study for Manila City

Abstract

Changes in the environment occur in cities due to increased urbanization and population growth. Sustainable Development Goal (SDG) 11 is intrinsically linked to the environment, one facet of which is the need for universal access to secure, inclusive, and accessible green and public places. As urban heat islands (UHI) have the potential to negatively influence cities and their residents, existing resources and data must be used to identify and quantify these effects. To address this, we present the use of satellite-derived (2013–2022) and meteorological data (2014–2020) to assess intra-urban heat islands in Manila City, Philippines. The assessment includes (a) understanding the temporal variability of air temperature measurements and outdoor thermal comfort based on meteorological data, (b) comparative and correlative analysis between common Land-Use Land Cover indicators (Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Built-up Index (NDBI)) and Land Surface Temperature (LST), (c) spatial and temporal analysis of LST using spatial statistics techniques, and (d) generation of an intra-urban heat island (IUHI) map with a recommended class of action using a suitability analysis model. Finally, the areas that need intervention are compared to the affected population, and suggestions to enhance the thermal characteristics of the city and mitigate the effects of UHI are established.

Assessing Sustainability over Space and Time: The Emerging Roles of GIScience and Remote Sensing

“…Also focusing on SDG 11, a case study in Manila, Philippines, assessed the urban heat island phenomenon using RS data [10]. Consistent with findings from other studies around the world, the study revealed that residential areas, asphalted and concrete roads and walkways, and certain commercial establishments and buildings exhibited higher surface temperatures compared to areas with vegetation and near bodies of water.…”

Assessment of Urban Heat Island in the Northeastern State Capitals in Brazil Using Sentinel Satellite Data – 3 SLSTR

“…Therefore, considering that areas with vegetation and bodies of water mitigate the accumulated heat, while areas with exposed soil and certain construction materials increase the temperature [35][36][37][38][39][40][41], the hypotheses were raised to explain the results obtained in the Northeastern capitals, with the support of LULC images from MapBiomas [42], Figure 7. Analyzing the Fortaleza maximum SUHI, a high temperature may have occurred in the furthest region of the urban area, at PUa, with a value of 2.31, because the hottest pixel of this area had a very high temperature of approximately 30.96 °C.…”

Urban Heat Island Assessment in the Northeastern State Capitals in Brazil Using Sentinel-3 SLSTR Satellite Data

“…Therefore, it is clear that areas with vegetation and water bodies attenuate the accumulated heat. In contrast, areas with exposed soil and certain construction materials tend to increase the temperature [22,[37][38][39][40][41][42], so the hypotheses were developed to explain the results obtained in the northeastern capitals. In addition, Land Use Land Cover (LULC) images from MapBiomas [43] were used to get the percentages of each class present in each adjacent area (Table A1 and Figure 6).…”