ISPF aims to foster prosperity by solving shared global research and innovation challenges. This will be done through working closely with international partners to: support research excellence and build the knowledge and technology of tomorrow strengthen ties with international partners that share our values; enable researchers and innovators to cultivate connections, follow their curiosity and pioneer transformations internationally, for the good of the planet. Activities under ISPF ODA aim to deliver research and innovation partnerships with low- and middle-income countries.

South Africa is a water-scarce country, which experiences highly variable rainfall as well as high evaporative rates resulting in an average of only 9% of rainfall being translated into streamflow. These characteristics have led to a system where water resources are strongly intertwined with the land cover and land use, and thereby the energy and carbon fluxes. The proposed study area is part of the Northern Drakensberg Strategic Water Source Area (SWSA) in the upper uThukela catchment. The study area, includes a vast tract of the protected, near pristine UNESCO World Heritage Ukhahlamba Drakensberg Park which falls under the management of Ezemvelo KZN Wildlife (EKZNW), contrasted with the heavily engineered Thukela-Vaal Pump storage scheme and impoverished communities with no access to water. The complex terrain and high levels of biodiversity endemism make the landscape sensitive to global change. There is a heavy dependence on the ecosystem services this landscape provides at national, regional and local scales with the livelihoods of the local population closely linked to the natural resources and ecosystem integrity. High soil-carbon stocks and the catchments' substantive contribution to the country's water resources, coupled with trends in land transformation impacting on these ecosystem functions provide a development context of national significance in which to understand global change impacts on ecosystem functioning along a river course from point and plot scale to cumulative downstream impacts. To optimally manage the landscape, as well as identify intervention and restoration activities, fine-scale observations over the relatively large area are required. Being in a developing country, as well as a rural area with complex topography means that fine-scale, field-based observation data are scarce, and is limited to a small research area in the headwater catchments in the protected grassland area (approximately 8 km2 out of a larger area of approx 5000 km2) and a new established site lower in the landscape in a conservation area. Land cover outside the protected areas varies from commercial agricultural cropping and rangelands, to heavily degraded rural village areas. Remotely sensed satellite based information is often inaccurate in areas of rugged, mountainous terrain such as this. The overarching objective of this project, would be to develop and validate fine scale datasets for the selected areas in the Northern Drakensberg for use in land and water management and modelling applications. These datasets are critical for upscaling ongoing in-situ observations across the broader landscape, in order to reduce spatio-temporal uncertainty around the influence of global change on ecosystem biodiversity and functional assets.  This would be achieved through the joint expertise of STFC RAL Space in earth observation and SAEON in field based monitoring in combination with their local knowledge The aims and objectives are Design and build a drone-based HyperSpectral Imager (HSI) platform for use in the field in the Northern Drakensberg, South Africa.  Perform fine-scale vegetation, land, evapotranspiration and soil water content mapping using drone technology and hyperspectral, thermal and LIDAR at a seasonal temporal resolution.  Complement in-situ monitoring with land-based sensors and satellite imagery for tracking  seasonal and longer-term shifts in vegetation phenology. Validate the fine-scale data products from the drone and satellite imagery using existing field-based data.  Build capacity through knowledge exchange and sharing of procedures and best practice.