A reference data framework for the application of satellite time series to monitor forest disturbance

Abstract

Comprehensive and robust estimations of forest disturbance over time are lacking in many parts of the world. In recent years, Landsat satellite data has been used extensively to retrospectively map forest disturbance across several decades. Human interpretation of Landsat time series, in association with ancillary data, has emerged as an effective and affordable way to collect reference data, which is often used to calibrate and validate disturbance models. If the reference data is collected using a robust probability sampling protocol, estimates of disturbance can be derived directly from the reference dataset using simple calculations. In this paper, we present the results of a reference data project in New South Wales, Australia, undertaken to characterise three decades of canopy disturbance across 13 Mha of predominantly native eucalypt forests. Our results indicate that disturbance is a frequent occurrence, with 70% of the forest disturbed during the last 33 years and around 35% experiencing two or more disturbances. The most common disturbance agent was wildfire, however, most wildfire disturbance occurred in few years, with over 4 Mha burnt in 2019–20 alone. The second most common disturbance agent was drought, which together with fire, was strongly influenced by low rainfall in the preceding years. Forest recovery was often quite rapid following disturbance, particularly in the event of increased rainfall. In this study, we demonstrate the value of collecting information in a systematic and comprehensive framework, which can be used to address numerous monitoring questions regarding forest canopy disturbance.

Keywords

• Forest disturbance
• Landsat time series
• Reference data
• Monitoring