Monitoring the expansion of alien species along roads with remote sensing.

Sillero, N., Lourenço, P., Teodoro, A.C., Gonçalves, J.A., Honrado, J. y Cunha, M. Monitoring the expansion of alien species along roads with remote sensing. 2020 IENE International Conference. Abstract book. Évora: Infrastructure & Ecology Network Europe. 2021, Vol. 4.1.2, Num. 2, pags. 71-72. ISSN 978-972-778-182-9

Invasive species are one of the most important threats to biodiversity and ecosystems. Monitoring invasion status is necessary for the implementation of mitigation measures and conserving biodiversity. Remote Sensing (RS) is the best Earth Observation tool for monitoring biodiversity as it provides data at several spatial and temporal resolutions. We used RS data and techniques to monitor the expansion along roadsides of five invasive tree species and giant reed (Acacia dealbata, A. melanoxylon, Robinia pseudoacacia, Ailanthus altissima, and Arundo donax). We hypothesise that roadsides are the main path of expansion for invasive species in Mediterranean landscape, and that the expansion is human mediated, as lands along roads have a strong agricultural management. The study area was located in the intervention area of the project Life LINES, one of the main transport routes between Portugal and Spain. We used aerial photographs from three different periods: 1995, 2010, and 2016. The 2016 set had a spatial resolution of 0.1 m, and Red-Blue-Green (RGB) and infrared bands. The 2010 and 1995 sets had a spatial resolution respectively of 0.5 m and 1 m and RGB bands. We obtained training data for each invasive and native species with a real-time kinematic GPS receiver. The aerial photographies were segmented using the multi-resolution algorithm and an object-oriented classification (Nearest Neighbour classifier) in eCognition Developer software. The photographies were posteriorly classified through a sequential process. We did a first classification to exclude all the non-vegetation objects (e.g. roads). Then, we did a second classification to classify the five invasive species and other plant species. We assessed classification accuracy with the overall accuracy and Kappa index metrics. Invasive species expanded in the study area between 1995 and 2016 along the roads, mainly close to anthropic areas. In the last 6 years (2010-2016), A. donax expanded more than the other invasive species. In some cases, the invaded area duplicated between 1995 and 2016. During this period, human management hampered the expansion of invasive species by cutting down individuals. Remote Sensing proved to be an efficient tool to measure expansion of invasive species along roadsides with an easy and replicable method. Our results are essential to plan the management of roadsides.

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Fecha de creación 17-09-2024
Fecha de última modificación 17-09-2024
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Identificador de los metadatos 56228ee2-a0e6-5a7f-ba3e-62aed1f3e0be
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"{\"type\": \"Polygon\", \"coordinates\": [[[-18.16, 27.64], [4.32, 27.64], [4.32, 43.79], [-18.16, 43.79], [-18.16, 27.64]]]}"
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  1. 2020 IENE International Conference. Abstract book. Vol. 4.1.2
  2. Num. 2
  3. pags. 71-72
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Nombre del autor Sillero, N., Lourenço, P., Teodoro, A.C., Gonçalves, J.A., Honrado, J. y Cunha, M.
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