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Abstract
The advent of the new political dispensation in South Africa has seen an exponential growth in the
rate of land transformation and encroachment by other land uses into valuable agro-ecological
zones. Due to the socio-economic value of the often limited high-potential agricultural land in the
country, a reliable determination of encroachment and transformation is necessary for effective
monitoring and management of such agro-ecological resources. Using the robust support vector
machine classification algorithm, this study adopted multi-temporal, remotely sensed datasets to
assess the extent to which the physical development footprint in the uMngeni Local Municipality
affected the existing agro-ecological zones from 1993 to 2003 and from 2003 to 2013. The results
show a steady increase in built-up areas during the period under investigation. The study
demonstrates the value of multi-temporal, remotely sensed datasets and techniques in mapping the
vulnerability of existing agricultural land to urbanisation in the study area.