Detecting Annual Harvested Area Using Landsat Time Series Data on the Main Island of Kyushu

Abstract

The objective of this study was to investigate the utility of Landsat time series data for the detection of harvested area using annual data on the main island of Kyushu. We used a change detection algorithm to extract variables for the classification of harvesting, other disturbance, stable forest, and other land cover change. The estimated annual harvested area from 1985 to 2017 was 7426.5 ha, on average, with an increasing trend in the last decade. The overall, producer’s, and user’s accuracies were 95.2％ (±0.5％), 83.1％ (±2.9％), and 93.8％ (±0.9％), respectively, based on the accuracy assessment using satellite images. When the accuracy was assessed based on ground survey data, 87.6％ of the harvested area was detected by annual Landsat time series data. When the accuracy was assessed based on statistical data, the estimated harvested area was 2.6％ larger than the recorded clearcut area in national forests and 30.5％ larger than the recorded clearcut area in private conifer forests in Miyazaki Prefecture. This study demonstrated that using annual Landsat time series data is a viable approach for the detection of harvesting in a large area across several decades.