Groundwater-dependent invasive alien plants (GDIAPs) pose significant threats to biodiversity, ecosystems function and water resources by exploiting groundwater during dry periods. This study aims to detect and monitor GDIAPs, and analyse their effects on groundwater levels and groundwater-dependent ecosystems. By leveraging advanced technologies like Remote Sensing, GIS, MLA, and cloud computing, the study demonstrates the potential of Sentinel-2 and Landsat-8 data combined with algorithms such as Random Forest (RF) to achieve high accuracy in delineating GDIAPs, contributing to more effective environmental management and conservation strategies.
Flood events pose significant risks to urban areas, requiring effective flood modeling and risk assessment. This study presents an integrated approach for Cape Town Metro Region using remote sensing and hydrological models to enhance flood preparedness and response. The research aims to improve prediction accuracy, assess impacts, and support proactive flood management aligned with Sustainable Development Goals.
The South African Young Surveyors Network, initially established in 2012 and relaunched in June 2024, is part of the FIG Young Surveyors Network. We aim to reintroduce the network to the South African surveying community and encourage young surveyors to join their peers and engage in FIG activities at local, regional, and global levels.
This research seeks to investigate the locational potential of offshore wind renewable energy in the context of South Africa's coastal Special Economic Zones (SEZs). By spatially interrogating where offshore wind turbines (bottom-fixed and floating offshore wind turbines) can be placed and how much power output can be generated, the study aims to provide a framework for integrating offshore wind renewable energy into South Africa's developing energy mix. This work will contribute to energy security, industrial growth, and the achievement of the sustainable development goals (SDGs) by offering actionable insights for stakeholders involved in the renewable energy transition.
Spatial data and information have been integrated into the BCB curriculum for multiple years. QGIS and R are taught at the 3rd year level, but students are taught to draw on multiple tools and data repositories in creating spatial outputs associated with ecosystem services and conservation interventions. Student projects at the Hons and MSc, which apply approaches to tackling conservation challenges, are also noted.
This study investigated land cover changes in the Nandoni Dam region from 2001 to 2021. A significant decline in vegetation was observed, highlighting the impact of dam construction on ecosystems. The study also explored the use of data fusion to improve LULC classification in rural areas. While data fusion enhanced accuracy, statistical analysis did not reveal a significant difference between optical-only and optical-SAR+optical methods. The findings emphasize the importance of monitoring LULCC and utilizing data fusion techniques for effective land management.
