Assessment and Improvement of Urban Resilience to Flooding at a Subdistrict Level Using Multi-Source Geospatial Data: Jakarta as a Case Study

Abstract

Urban resilience to natural disasters (e.g., flooding), in the context of climate change, has been becoming increasingly important for the sustainable development of cities. This paper presents a method to assess the urban resilience to flooding in terms of the recovery rate of different subdistricts in a city using all-weather synthetic aperture radar imagery (i.e., Sentinel-1A imagery). The factors that influence resilience, and their relative importance, are then determined through principal component analysis. Jakarta, a flood-prone city in Indonesia, is selected as a case study. The resilience of 42 subdistricts in Jakarta, with their gross domestic product data super-resolved using nighttime-light satellite images, was assessed. The association between resilience levels and influencing factors, such as topology, mixtures of religion, and points-of-interest density, were subsequently derived. Topographic factors, such as elevation (coefficient = 0.3784) and slope (coefficient = 0.1079), were found to have the strongest positive influence on flood recovery, whereas population density (coefficient = −0.1774) a negative effect. These findings provide evidence for policymakers to make more pertinent strategies to improve flood resilience, especially in subdistricts with lower resilience levels.