Potential utility of SumbandilaSat imagery for monitoring indigenous forest health

Abstract

Indigenous forest degradation is regarded as one of the most important environmental issues facing sub-Saharan Africa and South Africa in particular. Indigenous forest degradation is characterised by habitat fragmentation stemming from logging of large parcels of forest, forest clearance for agriculture and settlements, species loss as a result of selective logging or harvesting, and changes in forest health resulting from unsustainable bark harvesting, disease or insect infestation or drought. Attempts to assess changes in vegetation condition with broadband sensors have failed. Subtle changes in vegetation condition require high- fidelity sensors with narrow contiguous bands (hyperspectral data). However, there is always a problem of data redundancy for specific applications. It is for this reason that a medium resolution sensor was developed by SunSpace in collaboration with Stellenbosch University, called the SumbandilaSat. SumbandilaSat has 6 strategically located bands designed to satisfy various applications. We investigated the potential of SumbandilaSat sensor for providing information on forest canopy stress for the Dukuduku indigenous forest (28o25’S, 32o17’E) situated in the northern part of KwaZulu-Natal, South Africa. Airborne hyperspectral imagery was acquired over the study area using the airborne sensor AISA (Airborne Imaging Spectroradiometer). The AISA data comprise 272 wavebands in the 393-994 nm spectral range and a spatial resolution of 2 m. Varying chlorophyll stress levels were simulated on the data and the resulting imagery resampled to the spectral configurations of SPOT 1 and SumbandilaSat. The results indicate a higher ability for SumbandilaSat data to detect chlorophyll stress when compared to SPOT 1 data. SumbandilaSat data would be relevant to monitor the impact of climate change and other anthropogenic factors on the health of indigenous forest.