Abstract
Contemporary forest-health initiatives require technologies and workflows that can monitor forest degradation and recovery simply and efficiently over large areas. Spectral recovery analysis—the examination of spectral trajectories in satellite time series—can help democratize this process, particularly when performed with cloud computing and open-access satellite archives. We used the Landsat archive and Google Earth Engine (GEE) to track spectral recovery across more than 57,000 forest harvest areas in the Canadian province of Alberta. We analyzed changes in the normalized burn ratio (NBR) to document a variety of recovery metrics, including year of harvest, percent recovery after five years, number of years required to achieve 80% of pre-disturbance NBR, and % recovery the end of our monitoring window (2018). We found harvest areas in Alberta to recover an average of 59.9% of their pre-harvest NBR after five years. The mean number of years required to achieve 80% recovery in the province was 8.7 years. We observed significant variability in pre- and post-harvest spectral recovery both regionally and locally, demonstrating the importance of climate, elevation, and complex local factors on rates of spectral recovery. These findings are comparable to those reported in other studies and demonstrate the potential for our workflow to support broad-scale management and research objectives in a manner that is complimentary to existing information sources. Measures of spectral recovery for all 57,979 harvest areas in our analysis are freely available and browseable via a custom GEE visualization tool, further demonstrating the accessibility of this information to stakeholders and interested members of the public.
Highlights
Published: 23 November 2021Forests are a vital element of the Earth’s environment, supporting biodiversity [1], maintaining soil health and clean air [2,3,4], providing cultural and ecosystem services [5,6], and mitigating climate change [7,8]
As the above metrics were calculated at the per-pixel level, we summarized these for each harvest-area polygon in our dataset by extracting the mean and standard deviation of each from the relevant pixels corresponding to each polygon
We observed a high level of variability and range for the years to 80% spectral recovery metric (Y2R), with a mean of 8.70 years (s.d. = 3.56 years; range = 1.1 to 27.0 years; Table 2). These results suggested that rates of spectral recovery differ considerably across the forest harvest areas of Alberta, in the shorter term as well as the more medium to longer term
Summary
Forests are a vital element of the Earth’s environment, supporting biodiversity [1], maintaining soil health and clean air [2,3,4], providing cultural and ecosystem services [5,6], and mitigating climate change [7,8] These facts are well-established in the scientific literature and, increasingly, in the broader public consciousness. The Strategic Plan for Forests 2017–2030 adopted by the United Nations (UN) General Assembly in April of 2017 [11] provides a framework for global action on sustainable forest management and the halting of forest degradation and deforestation Achieving these global forest initiatives successfully will require effective mapping, monitoring, and assessment of forest cover and health. Forest ecosystems across the globe undergo continual change by both natural and anthropogenic forcing; a critical component for supporting programs such as the UN’s Strategic Plan is the mapping of forest disturbance and recovery
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