Tracking landscape function with the capacity to identify degradation versus regeneration is fundamental to sustainable land management. Spatial changes in soil biophysical state could be monitored by identifying the parameters that contribute to resilience and functional integrity. Soil health is the foundation of landscape function and is paramount to the sustainable management of savannas and grasslands across Northern Australia that occupy approximately two million km2 (Williams et al., 2005). Climatic extremes are increasingly changing these landscapes which require adaptation in land management strategies to deal with more frequent droughts, floods, and fires. Hence, there is an incentive for accurate and rapid monitoring to quantify spatial changes from soil to pastures and higher vegetation.
This research will apply a range of sensing platforms to characterise ground cover dynamics, analysing signal variations before and after fire, drought, floods and the impacts of grazing. To enhance capabilities and provide detailed analysis, Unmanned Aerial Vehicle (UAV) and a hand-held field spectrophotometer will be used to study the landscape function and soil health. Potentially, the phototrophic fabric called biocrusts that inhabit the soil surfaces in the northern savannas could act as a soil health indicator, by means of its biodiversity and its microbial communities’ capacity to act as ecosystem engineers (Eldridge & Leys, 2003). Both UAV and handheld devices are adept to quantifying chlorophyll in biocrusts nondestructively by detecting specific wavelength bands across the entire electromagnetic hyperspectral range (Gitelson, Gritz, & Merzlyak, 2003). Such spectrophotometry would enable a clearer understanding of the nuances of ‘bare ground’ by mapping the distribution of chlorophyll at a field level and across landscapes both temporally and spatially to recognize the role of biocrusts as a surrogate measure for soil health.
Various studies have shown the utilisation of hyperspectral measurements accurately determine the chlorophyll concentration of plants and biocrusts at several scales (Román et al., 2019; Stephens, Louchard, Reid, & Maffione, 2003).
Furthermore, digital colour (RGB, red, green blue) image analysis is another non-destructive method that can accurately measure chlorophyll content (greenness), a plant health Third Party Project Agreement | SmartSat CRC | P3-32s Page 4
indicator, and nutrient levels. The advent of fixed camera and high-performance computing, over the past decade, has facilitated the use of high-resolution visible photos (Red, Green, Blue) and digital technologies (including machine learning) more readily.
In this research, I will work towards linking proximal and remote sensing to provide soil health management tools. The project will be based on 30-years of fire research at Victoria River Research Station (VRRS), Northern Territory, and the impacts of grazing management regimes (established 24 years) at Wambiana Station (WGT) in North Queensland. This research will enable the connection of soil health to management practices. In a progressively variable climate monitoring ecosystem interactions is critical to guiding land management. Furthermore, sensing technologies have the capacity to enhance insight and decision making to maintain resilience and ongoing landscape function.
Professor Susanne Schmidt, The University of Queensland
Than Myint Swe