Helmi Ayuradi Miharja
Department of Inter Religious Study, Hartford International University, Hartford

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Social Sensing and Urban Flooding: Socio-Spatial Insights from Citizen-Generated Data in Makassar City, Indonesia Rusdi Rusdi; Helmi Ayuradi Miharja
JAMBURA GEO EDUCATION JOURNAL Volume 7, Issue 1 (2026): Jambura Geo Education Journal (JGEJ)
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jgej.v7i1.35890

Abstract

Urban flooding in rapidly urbanizing coastal cities increasingly exceeds the capacity of conventional monitoring and response systems to capture its localized, time-sensitive, and socially differentiated impacts. This study examines the potential of social sensing as a complementary approach for understanding urban flooding as a socio-spatial process shaped by everyday experiences, digital participation, and governance practices, with an empirical focus on Makassar City, Indonesia. Drawing on citizen-generated Instagram content collected between January 2019 and March 2024  (retained posts: n = [N]; geotagged posts used for spatial analysis: [P%]), the research integrates spatial, temporal, and qualitative signals derived from geotagged locations, posting timestamps, and visual–narrative materials to analyze flood dynamics. Social sensing outputs are triangulated with institutional flood information (incident logs, response records, and hazard layers) to assess correspondence, gaps, and governance relevance. The findings indicate that social sensing captures impact-oriented flood information in locations where inundation disrupts everyday urban activities, provides early temporal signals associated with flood onset and escalation, and reveals qualitative dimensions of lived flood experience that are not represented in hydrological or administrative data alone. While spatial and temporal patterns broadly align with institutional records, citizen-generated reports can precede formal documentation and highlight highly localized effects (e.g., temporary road closures or neighborhood-scale ponding) that remain underreported in official datasets. Methodologically, the study advances a human-centered analytical framework that bridges digital geographic analysis with qualitative interpretation, prioritizing transparency, interpretability, and ethical handling of publicly available social media data (e.g., de-identification and quotation minimization). From a governance perspective, the results demonstrate the value of integrating social sensing into hybrid urban flood governance to support more adaptive, context-sensitive, and inclusive approaches to flood risk management.