Mahlatse Kganyago

Phone+27 11 559 3645
Emailmahlatsekuj.acza
Websitehttps://www.uj.ac.za/members/mahlatse-kganyago

h-index

Research activity per year

Research Interests

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.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

Fingerprint

Dive into the research topics where Mahlatse Kganyago is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

34 Article
4 Conference contribution
2 Review article
1 Paper

A drought monitoring and early warning service for food security in South Africa
Pavlidis, V., Kganyago, M., Mukhawana, M., Alexandridis, T., Cherif, I., Laneve, G., Orsi, R., Kartsios, S., Karypidou, M. C., Sofiadis, I. & Katragkou, E., Apr 2024, In: Climate Services. 34, 100463.
Research output: Contribution to journal › Article › peer-review

Open Access
Effectiveness of South Africa's network of protected areas: Unassessed vascular plants predicted to be threatened using deep neural networks are all located in protected areas
Kandolo, B. S., Yessoufou, K. & Kganyago, M., Sept 2024, In: Ecology and Evolution. 14, 9, e70229.
Research output: Contribution to journal › Article › peer-review

Open Access
First-time calculation of the spatial distribution of concentration and air quality index over South Africa using TROPOMI data
Shikwambana, L., Kganyago, M., Mbatha, N. & Mhangara, P., 2024, In: Journal of the Air and Waste Management Association. 74, 8, p. 556-568 13 p.
Research output: Contribution to journal › Article › peer-review

Open Access
Monitoring the invasion of Campulocliniummacrocephalum (less) DC plants using a novel MaxEnt and machine learning ensemble in the Cradle Nature Reserve, South Africa
Makobe, B., Mhangara, P., Gidey, E. & Kganyago, M., Dec 2024, In: Environmental Systems Research. 13, 1, 24.
Research output: Contribution to journal › Article › peer-review

Open Access
Optical remote sensing of crop biophysical and biochemical parameters: An overview of advances in sensor technologies and machine learning algorithms for precision agriculture
Kganyago, M., Adjorlolo, C., Mhangara, P. & Tsoeleng, L., Mar 2024, In: Computers and Electronics in Agriculture. 218, 108730.
Research output: Contribution to journal › Review article › peer-review

Open Access
7 Citations (Scopus)

Study Results from University of the Witwatersrand Update Understanding of Machine Learning (Optical Remote Sensing of Crop Biophysical and Biochemical Parameters: an Overview of Advances In Sensor Technologies and Machine Learning Algorithms ...)
Kganyago, M.
24/04/24
1 item of Media coverage
Press/Media
Data on Climatology Described by Researchers at University of Johannesburg (A drought monitoring and early warning service for food security in South Africa)
Kganyago, M.
2/04/24
1 item of Media coverage
Press/Media
Study Data from University of Johannesburg Update Knowledge of Algorithms (Optimizing Sentinel-2 feature space for improved crop biophysical and biochemical variables retrieval using the novel spectral triad feature selection algorithm)
Kganyago, M.
22/02/24
1 item of Media coverage
Press/Media
Research from University of the Witwatersrand Yields New Findings on Agriculture (Mapping fruit tree dynamics using phenological metrics from optimal Sentinel-2 data and Deep Neural Network)
Kganyago, M.
11/12/23
1 item of Media coverage
Press/Media
Findings from University of the Witwatersrand Broaden Understanding of Remote Sensing (Evaluating the contribution of Sentinel-2 view and illumination geometry to the accuracy of retrieving essential crop parameters)
Kganyago, M.
8/12/23
1 item of Media coverage
Press/Media

Dr Mahlatse Kganyago

Personal profile

Research Interests

Expertise related to UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

A drought monitoring and early warning service for food security in South Africa

Effectiveness of South Africa's network of protected areas: Unassessed vascular plants predicted to be threatened using deep neural networks are all located in protected areas

First-time calculation of the spatial distribution of concentration and air quality index over South Africa using TROPOMI data

Monitoring the invasion of Campulocliniummacrocephalum (less) DC plants using a novel MaxEnt and machine learning ensemble in the Cradle Nature Reserve, South Africa

Optical remote sensing of crop biophysical and biochemical parameters: An overview of advances in sensor technologies and machine learning algorithms for precision agriculture

Study Results from University of the Witwatersrand Update Understanding of Machine Learning (Optical Remote Sensing of Crop Biophysical and Biochemical Parameters: an Overview of Advances In Sensor Technologies and Machine Learning Algorithms ...)

Data on Climatology Described by Researchers at University of Johannesburg (A drought monitoring and early warning service for food security in South Africa)

Study Data from University of Johannesburg Update Knowledge of Algorithms (Optimizing Sentinel-2 feature space for improved crop biophysical and biochemical variables retrieval using the novel spectral triad feature selection algorithm)

Research from University of the Witwatersrand Yields New Findings on Agriculture (Mapping fruit tree dynamics using phenological metrics from optimal Sentinel-2 data and Deep Neural Network)

Findings from University of the Witwatersrand Broaden Understanding of Remote Sensing (Evaluating the contribution of Sentinel-2 view and illumination geometry to the accuracy of retrieving essential crop parameters)

Dr Mahlatse Kganyago

Personal profile

Research Interests

Expertise related to UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Research output

Press/Media