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Nyando Basin Flood Risk Prediction System: A Production-Grade, Explainable Machine Learning Framework for Ward-Level Flood Susceptibility Mapping in Kisumu County, Kenya

Domaine:

climategeospatial

Type de record:

datasetmodelsoftware
Créateur:
Koe
Éditeur:
Zenodo
Hôte:avatar

A production-grade machine learning flood susceptibility

system for the Nyando River Basin, Kisumu County, Kenya.

XGBoost classifier achieving AUC-ROC 0.94 trained on

open satellite data (CHIRPS, NASA DEM, Sentinel-1 SAR).

Includes modular Python source package, 19 pytest unit

tests, FastAPI prediction endpoint, and React web

dashboard. 100% open data — Kenya DPA 2019 and GDPR

compliant. Full codebase, training data, model weights,

and unit tests published under MIT and CC-BY-4.0 at

github.com.

Visit

doi.org

Languages

Kenyan Sign Language

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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Nyando Basin Flood Risk Prediction System: A Production-Grade, Explainable Machine Learning Framework for Ward-Level Flood Susceptibility Mapping in Kisumu County, Kenya — Revised Version 2.1

Nyando Basin Flood Risk Prediction System: A Production-Grade, Explainable Machine Learning Framework for Ward-Level Flood Susceptibility Mapping in Kisumu County, Kenya — Revised Version 2.1

Revised and corrected Version 2.1 of the Nyando Basin Flood Risk Prediction System. Corrections in t