Applying remote sensing methods to estimate alterations in land cover change and degradation in the desert regions of the Southeast Iberian Peninsula

Descripción del Articulo

Numerous drylands worldwide have experienced degradation of both soil and vegetation in proximity to watering areas. Degradation can be observed in satellite imagery as fading radial brightness belts extending away from the water sources. The main objective of this study was to examine the spatio-te...

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Detalles Bibliográficos
Autores: Leiva Piedra, Jorge Luis, Ramírez-Juidias, Emilio, Madueño-Luna, Antonio, Madueño-Luna, José Miguel, López-Gordillo, Miguel Calixto, Leiva-Piedra, Jorge Luis
Formato: artículo
Fecha de Publicación:2023
Institución:Universidad Tecnológica del Perú
Repositorio:UTP-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.utp.edu.pe:20.500.12867/7926
Enlace del recurso:https://hdl.handle.net/20.500.12867/7926
https://doi.org/10.3390/rs15163984
Nivel de acceso:acceso abierto
Materia:Remote sensing
Deserts
Geostatistical
Land cover
https://purl.org/pe-repo/ocde/ford#1.05.00
Descripción
Sumario:Numerous drylands worldwide have experienced degradation of both soil and vegetation in proximity to watering areas. Degradation can be observed in satellite imagery as fading radial brightness belts extending away from the water sources. The main objective of this study was to examine the spatio-temporal patterns of land degradation and rehabilitation in the drylands of the southeast Iberian Peninsula. The brightness index of tasseled cap was discovered to be the best form of spectral transformation for enhancing the contrast between the bright-degraded areas near the points and the darker surrounding areas far from and in between these areas. To comprehend the spatial structure present in spaceborne imagery of two desert sites and three key time periods, semi-variograms were created (mid-late 2000s, around 2015 and 2020). To assess spatio-temporal land-cover patterns, a kriging was used to smooth the brightness index values extracted from 30 m spatial resolution images. To assess the direction and intensity of changes between study periods, a change detection analysis based on kriging prediction maps was performed. These findings were linked to the socioeconomic situation prior to and following the EU economic crisis. The study discovered that degradation occurred in some areas as a result of the region’s agricultural activities being exploited.
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