Urban Heat Risk Assessment Using Remote Sensing and Socioeconomic Data

Authors: Ronald C. Estoque*, National Institute for Environmental Studies, Japan, Makoto Ooba, National Institute for Environmental Studies, Japan, Takuya Togawa, National Institute for Environmental Studies, Japan, Yasuaki Hijioka, National Institute for Environmental Studies, Japan, Yuji Murayama, University of Tsukuba, Japan
Topics: Hazards, Risks, and Disasters, Hazards and Vulnerability, Remote Sensing
Keywords: urban heat risk, vulnerability, urban heat island, remote sensing, adaptation
Session Type: Paper
Day: 4/6/2019
Start / End Time: 5:00 PM / 6:40 PM
Room: Buchanan, Marriott, Mezzanine Level
Presentation File: No File Uploaded


Urban heat affects the livability of urban areas, but more importantly the lives of urban dwellers, their health and comfort. From the perspective of climate science and disaster risk management, risk is a function of hazard, exposure and vulnerability. However, the level of urban heat risk may not be uniform across space or cities. An urban heat risk index (UHRI) may help capture this pattern and identify those cities that are at risk. This study assesses urban heat risk in Philippine cities by deriving an UHRI using remote sensing and socioeconomic data. Its goal is to raise people’s awareness, including local planners and decision makers, of the state of Philippine cities in terms of urban heat risk, and eventually contribute to adaptation planning. To derive the UHRI, various social and ecological indicators were used. For hazard and exposure, satellite-derived land surface temperature and population density were used, respectively. The vulnerability of cities to urban heat was assessed as a function of sensitivity and adaptive capacity, following the conceptual definition of the Intergovernmental Panel on Climate Change (IPCC) in its Fifth Assessment Report (AR5). The sensitivity indicators included the ratio of young population, ratio of aged population, and poverty incidence. The adaptive capacity indicators included a vegetation (greenspace) index, city income, and per capita income. The indicators and components of risk were standardized and aggregated to derive the UHRI values of all the cities, which were later classified into five classes: very low, low, moderate, high, and very high.

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