Search

Your search keyword '"Magidi, James"' showing total 21 results
Start Over Author "Magidi, James"
21 results on '"Magidi, James"'

5. Geospatial Techniques to Quantify Urban Change

Author

Magidi, James, primary, Nhamo, Luxon, additional, Gumindoga, Webster, additional, Mhangara, Paidamwoyo, additional, Musakwa, Walter, additional, Mpandeli, Sylvester, additional, and Mabhaudhi, Tafadzwanashe, additional

Published
2022
Full Text
View/download PDF

19. Low-cost and scalable detection of sparse informal settlements using machine learning in Gcuwa, Eastern Cape, South Africa.

Author

Chamunorwa, Brighton, Shoko, Moreblessings, and Magidi, James

Subjects
*RANDOM forest algorithms, *SUPPORT vector machines, *DATA libraries, *BOOSTING algorithms, *K-nearest neighbor classification, *ENVIRONMENTAL degradation, *RADIOACTIVE waste repositories, *MACHINE learning
Abstract

Informative and scalable cartography plays a pivotal role in curbing urban pollution, waste management, and mitigating environmental damage in the development of informal settlements. The contemporary capabilities of cloud computing facilitate streamlined access to comprehensive data repositories, computational infrastructure, and proficient tools that have rapidly advanced the execution of sprawl mapping procedures. This study tests the performance of four machine-learning algorithms, namely: Gradient Boost, K Nearest Neighbor [KNN], Random Forest [RF], and Support Vector Machine [SVM] with data extracted from cloud computing repositories for delineating informal settlements in Gcuwa, Eastern Cape, South Africa, using low-cost datasets. A systematic approach comprising iterative phases, encompassing data acquisition, the development of a training dataset, modeling, and evaluation was employed. The delineation process involved the extraction of both spectral and textural features from Sentinel-2 imagery. The Random Forest algorithm emerged as the top performer, exhibiting the highest levels of accuracy and F1 score, followed by the gradient boosting, support vector machine, and then the K-nearest neighbor algorithms. Consequently, this innovative use of machine learning algorithms with low-cost datasets and the scalable, resilient approach for detecting informal settlements offers a promising avenue for enhancing urban planning and addressing sustainable development challenges. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

21. Mapping Irrigated Areas in the Limpopo Province, South Africa.

Author

Xueliang Cai, Magidi, James, Nhamo, Luxon, and van Koppen, Barbara

Subjects
IRRIGATION farming, IRRIGATION efficiency, INVESTMENTS, RURAL development, COMMUNITY development, ECONOMICS
Abstract

Recent studies reveal that there are many differences in reported numbers of irrigated areas, especially in developing countries, and that significant knowledge gaps and uncertainties remain to inform investment decisions and policy making. This is particularly relevant in South Africa, where the National Development Plan (NDP) envisages to increase irrigated areas; yet there are uncertainties in reported information on irrigated areas, especially on informal irrigation. This report summarizes the findings of a collaborative effort by the International Water Management Institute (IWMI), Department of Agriculture, Forestry and Fisheries (DAFF) and the Limpopo Department of Agriculture and Rural Development (LDARD) to map and assess irrigated areas in the Limpopo Province, South Africa. An assessment based on remote sensing was carried out to map agricultural areas in 2015 using a combination of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The mapping process was supported with data from previous irrigated area mapping exercises by DAFF and three field ground truthing (GT) surveys jointly conducted with the partners. A literature review and analysis of irrigated area statistics showed gaps and inconsistencies in different government reporting lines to comprehensively include irrigated areas. The mapping based on remote sensing estimated in total 1.6 million hectares (Mha) of cropland in the province, with only 262,000 ha actually irrigated in the 2015 winter season. The center-pivot irrigation systems, usually with high capital inputs, were underutilized with only 47,000 ha (29%) actually irrigated out of 164,000 ha equipped with center pivots. [ABSTRACT FROM AUTHOR]

Published
2017

Catalog

Books, media, physical & digital resources
See catalog results