Remote sensing and GIS for urbanization and flood risk assessment in Phnom Penh, Cambodia

Abstract

This study performed flood risk assessment in urbanized areas using geospatial and remotely sensed data for 1990–2005–2020 periods using the linear unmixing model (LUM), random forests (RF), and support vector machines (SVM). The urban mapping results verified with reference data indicated close agreement, with the overall accuracies and Kappa coefficients higher than 88.9% and 0.78, respectively. A remarkable increase of 14.9% in urban area was observed for the period 2005–2020, compared to 7.2% during the period 1990–2005. The results of flood risk modeling revealed that RF produced slightly more accurate results than SVM. The flood risk areas aggregated with urban maps showed that the larger urban flood risk area was especially observed for the period 2005–2020. The urban areas of high/very high and medium flood risks calculated for 2020 were 19.7% and 20%, respectively. Such flood risk areas were also overlaid with the population density for urban planning and management.

Keywords:

• Urban sprawl
• flood risk
• random forests
• support vector machines
• Cambodia

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is financed by Ton Duc Thang University, Vietnam. The financial support is gratefully acknowledged.