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akeDataAnalyst/Ethiopia-Humanitarian-Flood-Assessment-Shabelle

Domaine:

geospatialclimate

Type de record:

software
Créateur:
ake
Hôte:
Automated Sentinel-1 SAR rapid flood mapping, demographic exposure, and network disruption analysis for the Shabelle River Basin, Ethiopia # Ethiopia Humanitarian Flood Assessment: Shabelle River Basin **Automated Sentinel-1 SAR Rapid Mapping, Demographic Exposure, and Network Disruption** --- ## Description This repository houses an end-to-end geospatial analytics and data pipeline platform designed to simulate, assess, and visualize rapid-onset flood emergencies in the Shabelle River Basin (Gode, Somali Region of Ethiopia). Modeled after standard operational frameworks utilized by the United Nations Satellite Centre (UNITAR-UNOSAT), the project combines active radar remote sensing, dasymetric population modeling, and transport graph theory into reproducible GIS reporting framework. --- ## The Problem Riverine flooding along the Shabelle River basin routinely threatens agrarian livelihoods, damages rural infrastructure, and severs vital regional supply arteries (such as the primary Gode-Kelafo corridor). Traditional emergency assessments face critical bottlenecks: * **Cloud Cover Delays:** Optical satellite imagery (e.g., Sentinel-2, Landsat) is often rendered ineffective during active storm and monsoon windows due to dense cloud cover. * **Logistical Blind Spots:** Humanitarian actors often lack near-real-time synchronization between flood boundaries, affected population clusters (WorldPop), and road network accessibility (OpenStreetMap). * **Manual Processing Delays:** Manual GIS digitization leads to response lag times during critical early-warning windows. --- ## The Solution This automated pipeline resolves these limitations by implementing: 1. **Cloud-Independent Radar Sensing:** Leverages Sentinel-1 Synthetic Aperture Radar (SAR) imagery, which penetrates heavy cloud cover and operates day or night via active backscatter differencing. 2. **Automated Geospatial Overlays:** Automatically correlates inundation polygons against high-resolution gridded population nodes and OpenStreetMap (OSM) transport routing topologies. --- ## Tech Stacks & Core Libraries * **Python:** Core orchestration …

Visit

github.com

Languages

SarSomali

Tags

ethiopiaflood-mappinggeospatialhumanitarian-gisnetworkxosmnxremote-sensingsarsentinel-1shabelle-river

Licenses

MIT

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