Assessing the Accuracy of Landsat Vegetation Fractional Cover for Monitoring Australian Drylands

Abstract

Satellite-derived vegetation fractional cover (VFC) has shown to be a promising tool for dryland ecosystem monitoring. This model, calibrated through biophysical field measurements, depicts the sub-pixel proportion of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (BS). The distinction between NPV and BS makes it particularly important for drylands, as these fractions often dominate. Two Landsat VFC products are available for the Australian continent: the original Joint Remote Sensing Research Program (JRSRP) product, and a newer Digital Earth Australia (DEA) product. Although similar validation statistics have been presented for each, an evaluation of their differences has not been undertaken. Moreover, spatial variability of VFC accuracy within drylands has not been comprehensively assessed. Here, a large field dataset (4207 sites) was employed to compare Landsat VFC accuracy across the Australian continent, with detailed spatial and temporal analysis conducted on four regions of interest. Furthermore, spatiotemporal features of VFC unmixing error (UE) were explored to characterize model uncertainty in large areas yet to be field sampled. Our results showed that the JRSRP and DEA VFC were very similar (RMSE = 4.00–6.59) and can be employed interchangeably. Drylands did not show a substantial difference in accuracy compared to the continental assessment; however contrasting variations were observed in dryland subtypes (e.g., semi-arid and arid zones). Moreover, VFC effectively tracked total ground cover change over time. UE increased with tree cover and height, indicating that model uncertainty was low in typical dryland landscapes. Together, these results provide guiding points to understanding the Australian ecosystems where VFC can be used with confidence.