Optimised remote sensing methodologies for mapping and monitoring seagrass in southeastern Australian estuaries

Abstract

Characterising the carbon sequestration capacity and economic value of seagrass is challenging due to the geographical heterogeneity and temporal variability of seagrass beds. The ability to produce spatially dynamic and high-quality maps that represent biophysical characteristics of seagrass meadows is critical to accurately assessing their carbon sequestration potential. Field surveys can provide detailed information on biophysical indicators but cannot accurately capture differences within highly heterogeneous seagrass habitats. Remote sensing enables synoptic mapping of seagrass at meadow to regional scale.

The overarching objective of this research was to develop and assess new approaches that utilise emerging remote sensing techniques and technologies to detect biophysical characteristics of seagrass, with a focus on capturing spatial heterogeneity and temporal variability relevant to assessing seagrass carbon stock. The specific aims were to identify seagrass biophysical characteristics related to carbon stock that can be mapped with remote sensing, evaluate methods for mapping these characteristics with UAVs, assess the role of additional spectral bands, and upscale the detection of these characteristics to Sentinel-2 time-series data. These aims were addressed through a systematic review synthesising research on drivers of carbon stock variation and remote sensing, two novel UAV remote sensing methods to characterise fine-scale temporal change and spatial heterogeneity, and a scaled-up application of the newly developed UAV methods to Sentinel-2 satellite data.

The methods demonstrated here contribute to more accurate and detailed mapping and monitoring of ecologically and economically valuable seagrass ecosystems. This has important implications for producing spatially explicit models of seagrass carbon stock and sequestration capacity, allowing blue carbon financing to account for heterogeneous and variable seagrass beds.