Evaluating free and simple remote sensing methods for mapping Chinese privet ( Ligustrum sinense ) invasions in hardwood
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Evaluating free and simple remote sensing methods for mapping Chinese privet (Ligustrum sinense) invasions in hardwood forests James S. Cash1 · Christopher J. Anderson1 · Luke Marzen2 Received: 24 January 2020 / Accepted: 24 March 2020 © Springer Nature Switzerland AG 2020
Abstract Chinese privet (Ligustrum sinense) is a common invasive shrub in hardwood forests of the southeastern US and has been shown to negatively affect native herbaceous and woody plants. The ability to map the distribution of L. sinense on a property could help land managers plan and budget for control operations. We evaluated whether freely available moderate resolution multispectral imageries (Landsat 8 and Sentinel 2) and open-source GIS software (QGIS with the Semi-Automatic Classification Plugin) could be effective tools for this application. These tools are widely used by remote sensing and mapping professionals; however their adoption by field-level land managers appears limited, and their utility for mapping L. sinense invasions is untested. We evaluated how satellite type, image acquisition date, classification algorithm, and L. sinense cover affected detection accuracy. We found that Sentinel 2 imagery from March tended to produce good results, especially when analyzed using the maximum likelihood algorithm. Our best classifier obtained an overall accuracy of 92.3% for areas with ≥ 40% L. sinense cover. We recommend that land managers interested in applying this tool use an adaptive process for developing training polygons and test multiple images and classification algorithms in order to achieve optimal results. Keywords Supervised classification · Invasive species · QGIS · Satellite imagery
1 Introduction Chinese privet (Ligustrum sinense) is an invasive shrub with a broad global range outside its native distribution [1]. It is particularly problematic in the southeastern US, where it and congeneric European privet (L. vulgare L.) were estimated in 2008 to cover over a million hectares [2, 3]. Ligustrum sinense can outcompete native plant species, potentially degrading wildlife habitat and limiting forest regeneration. Control costs are estimated around $216–$1820 per ha [4, 5], necessitating careful planning and budgeting on behalf of land managers who are interested in forest restoration. The objective of this study is to evaluate whether free satellite imagery and simple to use open-source software could be an effective tool for land
managers who need to map L. sinense invasions to help plan hardwood forest restoration projects. Ligustrum sinense was introduced to the southeastern US for landscaping in 1852 and has since spread throughout the region, primarily through endozoochory and hydrochory [6–8]. Individuals can have a single- or multistemmed growth form and may reach 10 m tall [6, 7]. The phenology of the plant is variable depending on the local climate and can range from evergreen to deciduous [7]. Negative correlations between L. sinense abundance and native plant abundance and diversity have been documented by ma
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