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Título

Characterization of the main land processes occurring in Europe (2000-2018) through a MODIS NDVI seasonal parameter-based procedure

AutorRamírez-Cuesta, Juan Miguel CSIC ORCID; Minacapilli, M.; Motisi, A.; Consoli, Simona; Intrigliolo, Diego S. CSIC ORCID; Vanella, Daniela
Palabras claveTIMESAT
Normalized difference vegetation index
CORINE
Land use
Land cover
Fecha de publicación10-dic-2021
EditorElsevier
CitaciónScience of The Total Environment 799: 149346 (2021)
ResumenThe identification and recognition of the land processes are of vital importance for a proper management of the ecosystem functions and services. However, on-ground land uses/land covers (LULC) characterization is a time-consuming task, often limited to small land areas, which can be solved using remote sensing technologies. The objective of this work is to investigate how the different MODIS NDVI seasonal parameters responded to the main land processes observed in Europe in the 2000-2018 period; characterizing their temporal trend; and evaluating which one reflected better each specific land process. NDVI time-series were evaluated using TIMESAT software, which extracted eight seasonality parameters: amplitude, base value, length of season, maximum value, left and right derivative values and small and large integrated values. These parameters were correlated with the LULC changes derived from COoRdination of INformation on the Environment Land Cover (CLC) for assessing which parameter better characterized each land process. The temporal evolution of the maximum seasonal NDVI was the parameter that better characterized the occurrence of most of the land processes evaluated (afforestation, agriculturalization, degradation, land abandonment, land restoration, urbanization; R2 from 0.67-0.97). Large integrated value also presented significant relationships but they were restricted to two of the three evaluated periods. On the contrary, land processes involving CLC categories with similar NDVI patterns were not well captured with the proposed methodology. These results evidenced that this methodology could be combined with other classification methods for improving LULC identification accuracy or for identifying LULC processes in locations where no LULC maps are available. Such information can be used by policy-makers to draw LULC management actions associated with sustainable development goals. This is especially relevant for areas where food security is at stake and where terrestrial ecosystems are threatened by severe biodiversity loss.
DescripciónTrabajo desarrollado bajo la financiación del proyecto “Soil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping Systems” (773903), coordinado por José Alfonso Gómez Calero, investigador del Instituto de Agricultura Sostenible (IAS).
Versión del editorhttps://doi.org/10.1016/j.scitotenv.2021.149346
URIhttp://hdl.handle.net/10261/252978
DOI10.1016/j.scitotenv.2021.149346
ISSN0048-9697
E-ISSN1879-1026
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