入侵物种
高光谱成像
草原
遥感
地理
植被(病理学)
引进物种
生态学
栖息地
空间分布
物种分布
生物多样性
多光谱图像
生态系统
环境科学
生物
病理
医学
作者
Phuong D. Dao,Alexander Axiotis,Yuhong He
出处
期刊:International Journal of Applied Earth Observation and Geoinformation
日期:2021-12-01
卷期号:104: 102542-102542
被引量:2
标识
DOI:10.1016/j.jag.2021.102542
摘要
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 coarse-resolution 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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