UAV data for multi-temporal Landsat analysis of historic reforestation: a case study in Costa Rica
Biology (CMC), WM Keck Science (CMC), Information Systems and Technology (CGU), Biology (Pitzer), WM Keck Science (Pitzer), Biology (Scripps), WM Keck Science (Scripps), WM Keck Science
The use of the Landsat constellation to quantify historic deforestation and reforestation over time is well established. This analysis, however, requires ground-referenced data that is often inaccessible in remote areas or expensive if no existing high-resolution satellite imagery exists. In response, we evaluate the capability of unmanned aerial vehicle (UAV) imagery to serve as ground-reference data for identifying land-cover classes in Landsat imagery. We then apply these classes to quantify 30 years of historical deforestation and reforestation of an ecological reserve in Costa Rica. While spatial and spectral disparities between the sensors limit the generalization of the approach, our results demonstrate the ability of UAV and Landsat data to inexpensively classify a reserve's historic land cover over time and suggest an 11 year period for land cover to transition from pasture to secondary forest in lowland tropical environments.
© 2017 Informa UK Limited
Marx, Andrew, McFarlane, Donald, Alzahrani, Ahmed. "UAV data for multi-temporal Landsat analysis of historic reforestation: a case study in Costa Rica." International Journal of Remote Sensing, (2017) 1-18.