Management Effects on Ground Cover Clumpiness: Scaling From Field to Sentinel-2 Cover Estimates

Abstract

ABSTRACT:Significant progress has been made in the development of cover data and derived products based on remotely sensed fractional cover information and field data across Australia, and these cover data sets are now used for quantifying and monitoring grazing land condition. The availability of a dense time-series of nearly 30 years of cover data to describe the spatial and temporal patterns in landscape changes over time can help with monitoring the effectiveness of grazing land management practice change. With the advent of higher spatial resolution data, such as that provided by the Copernicus Sentinel 2 series of satellites, we can look beyond reporting purely on cover amount and more closely at the operational monitoring and reporting on spatial arrangement of cover and its links with land condition. We collected high spatial resolution cover transects at 20 cm intervals over the Wambiana grazing trials in the Burdekin catchment in Queensland, Australia. Spatial variance analysis was used to determine the cover autocorrelation at various support intervals. Coincident Sentinel-2 imagery was collected and processed over all the sites providing imagery to link with the field data. We show that the spatial arrangement and temporal dynamics of cover are important indicators of grazing land condition for both productivity and water quality outcomes. The metrics and products derived from this research will assist land managers to prioritize investment and practice change strategies for long term sustainability and improved water quality, particularly in the Great Barrier Reef catchments.

Mesoscale Mapping of Sediment Source Hotspots for Dam Sediment Management in Data-Sparse Semi-Arid Catchments

“…have a great information quantity and quality, and undisputable spatial-temporal information distribution. However, ground truthing is necessary to fully utilize their potential for applications such as classification of land use, crop cover, and phenophases [122,123]. Similar to digital elevation models, remote sensing products (and derivate such as in this study) have a defined resolution that can lead to misrepresentation of processes occurring on sub-grid scale [17,124,125], which in turn can limit management at sub-grid scales.…”