Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Data and code underlying the PhD thesis: Deep Learning and Earth Observation for the Study of West African Rainfall

Domain:

climategeospatial

Record type:

dataset
Creator:
Est
Editor:
TU
Publisher:
4TU
Host:avatar
The PhD thesis "Deep Learning and Earth Observation for the Study of West African Rainfall" develops a Deep Learning-based satellite rainfall retrieval model for West Africa, called "RainRunner". RainRunner classifies 3-hour sequences of Meteosat Second Generation (MSG) WV and TIR images in rain/no-rain. After being trained in Northern Ghana, RainRunner is applied to a wider area in West Africa (the Sudanian Savana), to evaluate generalization capability and understand better the rainfall mechanisms in the wider area. This dataset allows to do a full performance evaluation of the model by downloading and processing MSG data to create the test dataset, applying the model and evaluating the results. More information about the exact goal of each script can be found the README.txt file.

Visit

doi.orgdata.4tu.nl

Tasks

computer visionimage classification

Tags

Artificial Intelligence and Image ProcessingFOS: Computer and information sciencesAtmospheric SciencesFOS: Earth and related environmental sciencesOther Earth SciencesEarth SciencesInformation and Computing SciencesDeep LearningEarth ObservationRainfall+6

Licenses

Creative Commons Attribution Non Commercial Share Alike 3.0 Unportedhttps://creativecommons.org/licenses/by-nc-sa/3.0/legalcode

Similar

Deep Learning and Earth Observation for the Study of West African RainfallDeep Learning and Earth Observation for the Study of West African Rainfall: Observing rainfall processes through the lens of AIData underlying PhD thesis: AI in the Sky - Advancing Wildlife Survey Methods in Africa with Deep Learning and Aerial ImageryRainRunner - Machine Learning and Earth observation for reliable rainfall information in West AfricaSoftware underlying PhD thesis: AI in the Sky - Advancing Wildlife Survey Methods in Africa with Deep Learning and Aerial Imagery.Data underlying the PhD thesis of Stefanie Steinbach: Sustainable Use of African Wetlands for Food Security: A Spatial Evaluation Approach

Deep Learning and Earth Observation for the Study of West African Rainfall

This repository contains all research data and code supporting the findings described in the dissert

Deep Learning and Earth Observation for the Study of West African Rainfall: Observing rainfall processes through the lens of AI

Data underlying PhD thesis: AI in the Sky - Advancing Wildlife Survey Methods in Africa with Deep Learning and Aerial Imagery

This dataset supports the PhD research titled “AI in the Sky: Advancing Wildlife Survey Methods

RainRunner - Machine Learning and Earth observation for reliable rainfall information in West Africa

<p>West Africa&#8217;s economy is mainly sustained on agriculture and over 70%

Software underlying PhD thesis: AI in the Sky - Advancing Wildlife Survey Methods in Africa with Deep Learning and Aerial Imagery.

ZyPro is a deep learning framework designed to support the PhD research project “AI in the Sky:

Data underlying the PhD thesis of Stefanie Steinbach: Sustainable Use of African Wetlands for Food Security: A Spatial Evaluation Approach

This dataset includes data and codes underlying the PhD thesis of Stefanie Steinbach: Sustainable Us