Abstract
Abstract. Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.
Highlights
Invasive species have large effect on landscape, nature and human society, and despite the worldwide efforts, their menace grows (Hulme et al, 2009)
Detection of herb species is only possible if the data provide enough spectral and/or spatial details, the species are distinct from their neighborhood, form dense and uniform stands, and/or are large enough to be detected (Maheu-Giroux and de Blois, 2004; Müllerová et al, 2005)
All mentioned species are considered invasive in a number of European
Summary
Invasive species have large effect on landscape, nature and human society (both economy and human health; Ehrenfeld, 2010), and despite the worldwide efforts, their menace grows (Hulme et al, 2009). Remote sensing (RS) can potentially provide detailed vegetation mapping over large areas, reducing costs of extensive field campaigns. Detection of herb species is only possible if the data provide enough spectral and/or spatial details, the species are distinct from their neighborhood, form dense and uniform stands, and/or are large enough to be detected (Maheu-Giroux and de Blois, 2004; Müllerová et al, 2005). The potential for invasive species monitoring using RS is still not fully exploited and for the majority of invasive species there are no detection algorithms described
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