Modelización hidrológica distribuida de la Cuenca de la Rambla del Albujón mediante el uso de datos de teledetección

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.

Data and Resources

Metadata

Basic information
Resource type Text
Date of creation 2024-09-17
Date of last revision 2024-09-17
Show changelog
Metadata identifier 6ce32a1e-b2d3-5b03-b413-da64bd53d6ca
Metadata language Spanish
Themes (NTI-RISP)
High-value dataset category
ISO 19115 topic category
Other identifier
Keyword URIs
Character encoding UTF-8
Spatial information
INSPIRE identifier ESPMITECOIEPNBMMENOR691
INSPIRE Themes
Geographic identifier Murcia
Coordinate Reference System
Spatial representation Type
Bounding Box
"{\"type\": \"Polygon\", \"coordinates\": [[[-2.34, 37.38], [-0.69, 37.38], [-0.69, 38.76], [-2.34, 38.76], [-2.34, 37.38]]]}"
Spatial resolution of the dataset (m)
Provenance
Lineage statement
Metadata Standard
Conformity
Source dataset
Update frequency
Sources
Purpose
Process steps
Temporal extent (Start)
Temporal extent (End)
Version notes
Version
Dataset validity
Responsible Party
Name of the dataset creator Universidad Católica de Murcia
Name of the dataset maintainer
Identifier of the dataset creator
Email of the dataset creator
Website of the dataset creator
Identifier of the dataset maintainer
Email of the dataset maintainer
Website of the dataset maintainer