Journal
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
Volume 104, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.jag.2021.102542
Keywords
Invasive species; Species classification; Vegetation dynamic; Hyperspectral image; Topographic position index; Topographic wetness index
Categories
Funding
- Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN-386183]
- University of Toronto
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This study used airborne high-resolution narrow-band hyperspectral imagery to map invasive species in a heterogeneous grassland ecosystem in southern Ontario, Canada. The results showed high spectral and textural separability between invasive and native plants, with seasonality being the dominant factor for the distribution of invasive species at the landscape level, while small-scale topographic variations partially explain local patches of invasive species.
Characterizing the distribution, mechanism, and behaviour of invasive species is crucial to implementing an effective plan to protect and manage native grassland ecosystems. Hyperspectral remote sensing has been used to map and monitor invasive species at various spatial and temporal scales. However, most studies focus either on invasive tree species mapping or on the landscape level using coarse-spatial resolution imagery. These coarseresolution images are not fine enough to distinguish individual invasive grasses, especially in a heterogeneous environment where invasive species are small, fragmented, and co-existent with native plants with similar color and texture. To capture the small yet highly dynamic invasive plants at different stages of the growing season and under various topography and hydrological conditions, we use airborne high-resolution narrow-band hyperspectral imagery (HrHSI) to map invasive species in a heterogeneous grassland ecosystem in southern Ontario, Canada. The results show that there is high spectral and textural separability between two invasive species and between invasive and native plants, leading to an overall species classification accuracy of up to 89.6%. The combination of resultant species-level maps and the digital elevation model (DEM) showed that seasonality is the dominant factor that drives the distribution of invasive species at the landscape level, while small-scale topographic variations partially explain local patches of invasive species. This study provides insights into the feasibility of using HrHSI in mapping invasive species in a heterogeneous ecosystem and offers the means to understand the mechanism and behaviour of invasive species for a more effective grassland management strategy.
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