The use of remote sensing to detect the consequences of erosion in gypsiferous soils
Entity
UAM. Departamento de Geología y GeoquímicaPublisher
Elsevier B.V.Date
2020-12Citation
10.1016/j.iswcr.2020.10.001
International Soil and Water Conservation Research 8.4 (2020): 383-392
ISSN
2095-6339 (print); 2589-059X (online)DOI
10.1016/j.iswcr.2020.10.001Funded by
This research was funded by the Project ACCION, and is part of the Operative Group Lenosot, supported by the Rural Development Programme 2014 e 2020 of the Comunidad de Madrid Government (Spain). We thank the cooperation of the Finca La Chimenea staff and the work of undergraduate students from the Autonomous University of MadridProject
Comunidad de Madrid. PDR-CM 2014/2020-ACCIONEditor's Version
https://doi.org/10.1016/j.iswcr.2020.10.001Subjects
Erosion; Gypsum; NDVI; Remote sensing; Soil color; Tillage; GeologíaRights
© 2020 Elsevier Ltd.Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.
Abstract
Tillage practices on sloping ground often result in unsustainable soil losses impairing soil functions such as crop productivity, water and nutrients storage, and soil organic carbon (SOC) sequestration. A sloping olive grove (10%) was planted in shallow gypsiferous soils in 2004. It was managed by minimum tillage; the most frequent management practice in central Spain. The consequences of erosion were studied in soil samples (at 0–10, 10–20, and 20–30 cm depths) by analyzing SOC, available water and gypsum content, and by detecting spectral signatures using an ASD FieldSpecPro® VIS/NIR-spectroradiometer. The Brightness index (BI), Shape index (FI), and Normalized Difference Vegetation Index (NDVI) were derived from the ASD spectral signatures and from remote sensing (Sentinel-2 image) data. The development of these young olive trees was estimated from the measured diameter of the trunks (17 ± 18 cm diameter). In 20–30 cm of the soil, the carbon stock (38 ± 18 Mg ha−1) as well as the available water content (12 ± 6%) was scarce, affecting the productivity of the olive grove. The above-mentioned indices obtained from the laboratory samples and the pixels of the Sentinel-2 image were significantly (p < 0.01) correlated, with a correlation coefficient of around 0.4. The BI was related to the gypsum content and the slope of the plot. The FI was related to the carbon and water contents. The NDVI derived from the satellite image identified the influence of soil degradation on the trees and the carbon content. The spatial-temporal changes of the indices might help in tracking soil changes over time
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Google Scholar:Sastre, Blanca
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Bienes, Ramón
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Marqués Pérez, María José
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Álvarez González, Ana María
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Carral González, Pilar
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Bienes, Ramón
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