Abstract
High-resolution maps of redwood distributions could enable strategic land management to satisfy diverse conservation goals, but the currently-available maps of redwood distributions are low in spatial resolution and biotic detail. Classification of airborne imaging spectroscopy data provides a potential avenue for mapping redwoods over large areas and with high confidence. We used airborne imaging spectroscopy data collected over three redwood forests by the Carnegie Airborne Observatory, in combination with field training data and application of a gradient boosted regression tree (GBRT) machine learning algorithm, to map the distribution of redwoods at 2-m spatial resolution. Training data collected from the three sites showed that redwoods have spectral signatures distinct from the other common tree species found in redwood forests. We optimized a gradient boosted regression model for high performance and computational efficiency, and the resulting model was demonstrably accurate (81–98% true positive rate and 90–98% overall accuracy) in mapping redwoods in each of the study sites. The resulting maps showed marked variation in redwood abundance (0–70%) within a 1 square kilometer aggregation block, which match the spatial resolution of currently-available redwood distribution maps. Our resulting high-resolution mapping approach will facilitate improved research, conservation, and management of redwood trees in California.
Highlights
Coastal redwoods (Sequoia sempervirens) are an exceptionally charismatic species
We used airborne imaging spectroscopy data collected over three redwood forests by the Carnegie Airborne Observatory, in combination with field training data and application of a gradient boosted regression tree (GBRT) machine learning algorithm, to map the distribution of redwoods at 2-m spatial resolution
We did not perform a direct comparison of the coarse-resolution redwood maps with our high-resolution maps, the large variation in redwood density we reported suggests that there is likely to be substantial variation in redwood density in locations that are currently listed as homogenous redwood habitat in the 1 km2 resolution redwood distribution map
Summary
Coastal redwoods (Sequoia sempervirens) are an exceptionally charismatic species. They are the tallest trees on earth, with some individuals taller than 100 m and older than 2000 years in age. Redwoods are endemic to the central coast of California and Southern Oregon, and redwood forests are locally- and globally-valued ecosystems [1]. Redwood forests are unique sites for recreation, and visitors to redwood-dominated state and national parks contribute $34 million dollars each year to local economies [1]. Redwoods have been the focus of recent research interest due to their unique potential for carbon storage [2], with some redwood forests estimated to store 2600 mg of aboveground carbon per unit hectare, the highest values recorded on earth [3]
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