GRSG Conference 2022: Orbit to Outcrop

Title:  Flood Analysis Study in South Omdurman, Khartoum & Jebel Awlia Localities Using RS & GIS Techniques

Author: Tarig Abuobida Ahmed Ali

Abstract:

Floods are one of the most frequent natural disasters that inflict human Suffering and misery in Sudan, out of all the natural hazards that might cause disasters. Sudan has had a series of high floods on the Nile and its tributaries, as well as flash floods in the Wadi system, over the last 50 years. Floods of this magnitude wreaked havoc on the agricultural industry, as well as buildings, other infrastructure, and animal and human lives. Floods have been recorded disrupting personal, economic, and social activity, as well as putting a country’s security and growth at risk by destroying roads, buildings, and other assets.

The goal of this study was to map flood extents and estimate damage to flooded area in order to determine the impact of floods on settlements and agriculture. This is made possible by doing a spatiotemporal analysis using high-resolution satellite imagery and modern Geographic Information Systems (GIS) tools.
Using multi temporal satellite imagery and GIS spatial analytic tools and methodologies, this study created Flood Hazard maps and estimates of flood damages for the study area (Khartoum, South Omdurman, and Jebel Awlia) to mitigate risks to property and life. As well as determining the impact of flooding on land cover.

This study used an integration of remote sensing as a data source and GIS as a processing toolkit to create flood maps using high resolution multi-temporal Sentinel-1 and Sentinel-2 imagery provided freely available by the European Space Agency (ESA). To create flood extents in corresponding rain months in the research area, two sets of remotely sensed data were acquired: images acquired before and after the flood.
Land cover classes were generated using high resolution optical Sentinel-2 imagery with a spatial resolution of 10m and advanced methodologies, and flood damage was assessed on each land cover type.

Hydrological Modelling techniques in addition to land cover classes were used to generate Flash Flood Hazard maps & then merged with River Flood Hazard maps to develop a final combined Flood Hazard Map.

Multi-seasonal Sentinel-2 images during and after flood were used to generate NDWI (Normalized Difference water Index) for the years (2018, 2019, 2020 & 2021). Then its results of 2020 flood extent have been compared to the results of Sentinel 1 SAR.

The outcomes of this study’s analysis were highly significant in terms of flood risk assessment. It detected and prioritized flood-affected locations based on previous flood mapping and the magnitude of the flood. This will help with modeling and forecasting future natural flooding disasters.