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Characterizing the effect of small-scale topographic variability on co-existing native and invasive species in a heterogeneous grassland using airborne hyperspectral remote sensing

Dao, P. D.; Axiotis, A.; He, Y.

2021-04-11 ecology
10.1101/2021.04.11.439344 bioRxiv
Show abstract

O_LICharacterizing the distribution, mechanism, and behaviour of invasive species is crucial to implementing an effective plan for the protection and management of native grassland ecosystems. Hyperspectral remote sensing has been used for mapping and monitoring invasive species at various spatial and temporal scales. However, most studies focus either on invasive tree species mapping or on the landscape-level using low-spatial resolution remote sensing imagery. These low-resolution images are not fine enough to distinguish individual invasive grasses, especially in a heterogeneous environment where invasive species are small, fragmented, and co-existing with native plants with similar color and texture. C_LIO_LITo 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. C_LIO_LIThe results show that there is high spectral and textural separability between 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. C_LIO_LIThis 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. C_LI

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