Mahlatse Kganyago obtained BSc in Environmental Resource Studies and a BSc Honours in Geography from the University of Limpopo, Polokwane, South Africa, in 2009 and 2011, respectively. He further obtained an MSc degree in Applied Remote Sensing and GIS (Cum Laude) from the University of KwaZulu-Natal, Pietermaritzburg, South Africa, in 2016. In 2023, he obtained his PhD from the University of Witwatersrand.
He has an extensive experience in machine learning applications, image analysis (multispectral and hyperspectral), spectral analysis (NNIR-MIR range), land-cover/use mapping, retrieval of crop biophysical and biochemical variables, statistical and spatial modelling of landscapes, and both research and teaching of Remote Sensing/Earth observation/Geographical Information Systems for natural and agro-ecological resources management. His work in recent times focuses on enhancing the use, understanding, development, and implementation of novel remote-sensing technologies and robust machine-learning algorithms to aid agro-ecological systems research and application development for societal benefit.
Mr. Kganyago is a registered Professional Natural Scientist in Geospatial Sciences with the South African Council for Natural Scientific Professions (SACNASP). He is also a licensed RPAS (Remotely Piloted Aerial Systems) pilot in South Africa.
