Version 1
: Received: 9 June 2023 / Approved: 12 June 2023 / Online: 12 June 2023 (07:16:24 CEST)
How to cite:
Ramírez-Juidias, E.; Madueño-Luna, A.; Luna, J.M.M.; Gordillo, M.C.L.; Leiva-Piedra, J.L. Using Remote Sensing Techniques to Assess Land-Cover Change and Degradation in the Deserts of the Southeast Iberian Peninsula. Preprints2023, 2023060781. https://doi.org/10.20944/preprints202306.0781.v1
Ramírez-Juidias, E.; Madueño-Luna, A.; Luna, J.M.M.; Gordillo, M.C.L.; Leiva-Piedra, J.L. Using Remote Sensing Techniques to Assess Land-Cover Change and Degradation in the Deserts of the Southeast Iberian Peninsula. Preprints 2023, 2023060781. https://doi.org/10.20944/preprints202306.0781.v1
Ramírez-Juidias, E.; Madueño-Luna, A.; Luna, J.M.M.; Gordillo, M.C.L.; Leiva-Piedra, J.L. Using Remote Sensing Techniques to Assess Land-Cover Change and Degradation in the Deserts of the Southeast Iberian Peninsula. Preprints2023, 2023060781. https://doi.org/10.20944/preprints202306.0781.v1
APA Style
Ramírez-Juidias, E., Madueño-Luna, A., Luna, J.M.M., Gordillo, M.C.L., & Leiva-Piedra, J.L. (2023). Using Remote Sensing Techniques to Assess Land-Cover Change and Degradation in the Deserts of the Southeast Iberian Peninsula. Preprints. https://doi.org/10.20944/preprints202306.0781.v1
Chicago/Turabian Style
Ramírez-Juidias, E., Miguel Calixto López Gordillo and Jorge Luis Leiva-Piedra. 2023 "Using Remote Sensing Techniques to Assess Land-Cover Change and Degradation in the Deserts of the Southeast Iberian Peninsula" Preprints. https://doi.org/10.20944/preprints202306.0781.v1
Abstract
Many drylands around the world have seen both soil and vegetation degradation around watering points. It can be seen in spaceborne imagery as radial brightness belts that fade with distance from the water areas. The study's primary goal was to characterize spatio-temporal land degradation/rehabilitation in the drylands of the southeast Iberian Peninsula. The brightness index of Tasseled Cap was discovered to be the best 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). In order to assess spatio-temporal land-cover patterns, a geostatistical model (kriging) was used to smooth 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.
Keywords
Andalusia; remote sensing; desert of Tabernas; Sierra Alhamilla; Almería; mathematical models
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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