Monitoring forest disturbances in Southeast Oklahoma using Landsat and MODIS images

Monitoring forest disturbances using remote sensing data with high spatial and temporal resolution can reveal relationships between forest disturbances and forest ecological patterns and processes. In this study, we fused Landsat data at high spatial resolution (30 m) with 8-day MODIS data to produce high spatial and temporal resolution image time-series. The Spatial Temporal Adaptive Algorithm for mapping Reflectance Change (STAARCH) is a simple but effective fusion method. We adapted the STAARCH fusion method to successfully produce a time-series of disturbances with high overall accuracy (89-92%) in mixed forests in southeast Oklahoma. The results demonstrated that in southeast Oklahoma, forest area disturbed in 2011 was higher than it was in 2000. However, two remarkable drops were identified in 2001 and 2006. We speculated that the drops were related to the economic recessions causing reduction in the demand of woody products. The detected fluctuation of area disturbed calls for continuing monitoring of spatial and temporal changes in this and other forest landscapes using high spatial and temporal resolution imagery datasets to better recognize the economic and environmental factors, as well as the consequences of those changes. (C) 2015 Elsevier B.V. All rights reserved.