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About
Lukumon is a Geospatial Data Scientist with a research interest in the application of Earth Observation to study ecosystems, water quality, and the nexus between disaster and food security in changing climate and rapidly increasing population.
He has a joint master's degree in Geospatial Technologies from three European universities (Universidade Nova de Lisboa, Universität Münster, and Universitat Jaume I). Additionally, he possesses a bachelor's degree in Surveying and Geoinformatics from the Federal University of Technology Akure, Nigeria.
He is skilled in several geospatial software and IT tools which include, but are not limited to, QGIS, Python, ArcGIS Pro, Google Earth Engine (GEE), ERDAS Imagine, AutoCAD, and Google Maps.
See some of his selected projects here.
Project Gallery
Crop Type Classification using Random Forest Machine Learning Classifier and Sentinel-2 using GEE and Python.
Above Ground Biomass Density (AGBD) Estimation using Satellite Data and Machine Learning
Land Cover Classification Using Machine Learning Algorithms and Multi-Source Satellite Images.
Flooded Crop Impact Assessment Using Integrated Method with GEE
Land Use Dynamics & Armed Conflicts Using EO
Time Series NDVI for Crop Growth Monitoring using GEE
Time Series NDVI for Crop Growth Monitoring using GEE
Geospatial Analysis of Agricultural Land Suitability using GIS-MCDA with AHP.
Flood Extent Mapping Using Sentinel-2 Satellite Images.
Flood Extent and Damage Assessment Using Multi-Source Data with GEE Python API.
Spatio-Temporal Analysis of Armed Clash Events and Fatalities in Nigeria Using Python and QGIS.
Water Quality Monitoring using Insitu, EO Data, & Machine Learning
Water Quality Monitoring using Insitu, EO Data, & Machine Learning
Population Density Map of Nigeria Using QGIS.
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