Abstract
Spatial information about disturbance driven patterns of forest structure and ages across landscapes provide a valuable resource for all land management efforts including cross-ownership collaborative forest treatments and restoration. While disturbance events in general are known to impact stand characteristics, the agent of change may also influence recovery and the supply of ecosystem services. Our study utilizes the full extent of the Landsat archive to identify the timing, extent, magnitude, and agent, of the most recent fast disturbance event for all forested lands within Minnesota, USA. To account for the differences in the Landsat sensors through time, specifically the coarser spatial, spectral, and radiometric resolutions of the early MSS sensors, we employed a two-step approach, first harmonizing spectral indices across the Landsat sensors, then applying a segmentation algorithm to fit temporal trends to the time series to identify abrupt forest disturbance events. We further incorporated spectral, topographic, and land protection information in our classification of the agent of change for all disturbance patches. After allowing two years for the time series to stabilize, we were able to identify the most recent fast disturbance events across Minnesota from 1974–2018 with a change versus no-change validation accuracy of 97.2% ± 1.9%, and higher omission (14.9% ± 9.3%) than commission errors (1.6% ± 1.9%) for the identification of change patches. Our classification of the agent of change exhibited an overall accuracy of 96.5% ± 1.9% with classes including non-disturbed forest, land conversion, fire, flooding, harvest, wind/weather, and other rare natural events. Individual class errors varied, but all class user and producer accuracies were above 78%. The unmatched nature of the Landsat archive for providing comparable forest attribute and change information across more than four decades highlights the value of the totality of the Landsat program to the larger geospatial, ecological research, and forest management communities.
Highlights
Explicit information about stand-level forest attributes across land ownerships are valuable for regional forest assessments, coordinated forest management, and policy development.Landscape-level patterns of forest structure and stand age are largely driven by disturbance regimes [1].Characteristics of forest disturbance events, including the duration, severity, and causal agent, will affect the residual forest structure and potential recovery trajectories [2], both of which are vital to forest management planning and restoration actions
The unmatched nature of the Landsat archive for providing comparable forest attribute and change information across more than four decades highlights the value of the totality of the Landsat program to the larger geospatial, ecological research, and forest management communities
The Landsat time series methodology utilized in this study was successful in identifying the most recent fast disturbance events across Minnesota from 1974–2018 with a change vs. no-change validation accuracy of 97.2% ± 1.9% (Table 2)
Summary
Explicit information about stand-level forest attributes across land ownerships are valuable for regional forest assessments, coordinated forest management, and policy development.Landscape-level patterns of forest structure and stand age are largely driven by disturbance regimes [1].Characteristics of forest disturbance events, including the duration, severity, and causal agent, will affect the residual forest structure and potential recovery trajectories [2], both of which are vital to forest management planning and restoration actions. Forests 2020, 11, 362 and identifying the causal agents of disturbance events in a spatially explicit manner, may aid in forest management planning across multiple ownerships and large extents. This is especially true as management becomes increasingly focused on the “all lands approach” [7,8], requiring contiguous spatial information about forest structure, age, and disturbance histories to support planning for multi-ownership collaborations. While the underlying mechanisms for successful all lands management are collaborative projects and management prescriptions across ownership boundaries [7,8], contiguous spatial and temporal information about forest disturbance patterns at landscape scales provides support for the planning and execution of such collaborative efforts
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