Abstract
The purpose of this study is to map shrub distributions and estimate shrub cover fractions based on the classification of high-spatial-resolution aerial orthoimagery and light detection and ranging (LiDAR) data for portions of the highly disturbed coastal sage scrub landscapes of San Clemente Island, California. We utilized nine multi-temporal aerial orthoimage sets for the 2010 to 2018 period to map shrub cover. Pixel-based and object-based image analysis (OBIA) approaches to image classification of growth forms were tested. Shrub fractional cover was estimated for 10, 20 and 40 m grid sizes and assessed for accuracy. The most accurate estimates of shrub cover were generated with the OBIA method with both multispectral brightness values and canopy height estimates from a normalized digital surface model (nDSM). Fractional cover products derived from 2015 and 2017 orthoimagery with nDSM data incorporated yielded the highest accuracies. Major factors that influenced the accuracy of shrub maps and fractional cover estimates include the time of year and spatial resolution of the imagery, the type of classifier, feature inputs to the classifier, and the grid size used for fractional cover estimation. While tracking actual changes in shrub cover over time was not the purpose, this study illustrates the importance of consistent mapping approaches and high-quality inputs, including very-high-spatial-resolution imagery and an nDSM.
Highlights
Non-native grasses cover a large extent of southern California that was once covered by extensive stands of native coastal sage scrub (CSS)
Aerial orthoimagery analyzed in this study was captured during different years and seasons, resulting in different vegetation conditions associated with vegetation phenology and available plant moisture
This study has shown that an object-based image analysis (OBIA) approach that incorporates high-spatial-resolution imagery and normalized digital surface model (nDSM) data yields higher accuracy shrub cover maps than pixel-based mapping
Summary
Non-native grasses cover a large extent of southern California that was once covered by extensive stands of native coastal sage scrub (CSS). CSS is a threatened habitat, where restoration efforts are often hindered by the dominance of exotic grasses. Native plant communities are slow to recover once exotic grasses have established [1,2]. CSS is a vegetation community type of high priority for conservation because of its high degree of biological diversity and marked reduction in areal extent. Management of CSS habitats is critical for the conservation of native vegetation, which supports several rare and threatened plant and animal species [3,4]. Mapping large regions of CSS habitat at the growth form level and tracking changes in shrub cover over time will create a baseline of CSS conditions and develop a trajectory for future recovery and restoration [5]
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