Calibration and Validation of Landsat Tree Cover in the Taiga−Tundra Ecotone

• Published in: Remote Sensing
• Main Authors: Paul Montesano, Christopher Neigh, Joseph Sexton, Min Feng, Saurabh Channan, Kenneth Ranson, John Townshend
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2016
• Subjects: Landsat; tree; canopy; cover; forest; structure; taiga; tundra; ecotone; uncertainty; Tundra
• Online Access: https://doi.org/10.3390/rs8070551

Monitoring current forest characteristics in the taiga−tundra ecotone (TTE) at multiple scales is critical for understanding its vulnerability to structural changes. A 30 m spatial resolution Landsat-based tree canopy cover map has been calibrated and validated in the TTE with reference tree cover data from airborne LiDAR and high resolution spaceborne images across the full range of boreal forest tree cover. This domain-specific calibration model used estimates of forest height to determine reference forest cover that best matched Landsat estimates. The model removed the systematic under-estimation of tree canopy cover >80% and indicated that Landsat estimates of tree canopy cover more closely matched canopies at least 2 m in height rather than 5 m. The validation improved estimates of uncertainty in tree canopy cover in discontinuous TTE forests for three temporal epochs (2000, 2005, and 2010) by reducing systematic errors, leading to increases in tree canopy cover uncertainty. Average pixel-level uncertainties in tree canopy cover were 29.0%, 27.1% and 31.1% for the 2000, 2005 and 2010 epochs, respectively. Maps from these calibrated data improve the uncertainty associated with Landsat tree canopy cover estimates in the discontinuous forests of the circumpolar TTE.