Remote sensing of invasive alien woody species in Uruguayan native forests
he invasion of ecosystems by exotic species has been identified as the second cause of biodiversity loss worldwide, and is one of the most difficult threats to reverse. In Uruguay, the introduction and spread of invasive alien species (IAS) has been identified as a serious environmental problem, bec...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | Uruguay |
| Institución: | Universidad de la República |
| Repositorio: | COLIBRI |
| Idioma: | inglés |
| OAI Identifier: | oai:colibri.udelar.edu.uy:20.500.12008/30894 |
| Acceso en línea: | https://hdl.handle.net/20.500.12008/30894 |
| Access Level: | acceso abierto |
| Palabra clave: | Forest degradation Gleditsia triacanthos Biologic invasions Landsat Ligustrum lucidum Degradación de bosques Invasiones biológicas Degradação florestal Invasões biológicas |
| Sumario: | he invasion of ecosystems by exotic species has been identified as the second cause of biodiversity loss worldwide, and is one of the most difficult threats to reverse. In Uruguay, the introduction and spread of invasive alien species (IAS) has been identified as a serious environmental problem, becoming perhaps the greatest danger that native forests currently face. IAS often represents optical differences in the forest canopy and can therefore be detected remotely. The two most widespread and aggressive woody IAS in the country's forests are Ligustrum lucidum and Gleditsia triacanthos. The objective of this study was to spatially identify IAS within the native forest of Uruguay, mainly these two species, using remote sensing techniques. This work is based on multispectral data from medium-resolution satellite images (Landsat) and uses the normalized difference fraction index (NDFI) for classification. The NDFI is sensitive to canopy coverage and is calculated through a sub-pixel spectral mixture analysis (SMA), decomposing the reflectance information for each pixel into fractions. The results showed an area of 22,009 ha of native forest invaded by these IAS, with an overall accuracy of 87.6%, representing 2.63% of the total native forest area in the country. The results presented in this work will help to geographically analyze the invasion by IAS in the forest, linking it to possible drivers. Furthermore, this map can now be used as relevant information when designing IAS prevention, mitigation, restoration, and eventual eradication strategies in the country. |
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