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Article

Multiscaling NDVI Series Analysis of Rainfed Cereal in Central Spain

1
CEIGRAM, Research Centre for the Management of Agricultural and Environmental Risk, Universidad Politécnica de Madrid, 28040 Madrid, Spain
2
Department of Agricultural Production, Universidad Politécnica de Madrid, 28040 Madrid, Spain
3
Dpto de Matemática Aplicada a las TIC, Universidad Politécnica de Madrid, 28040 Madrid, Spain
4
Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Nicolas R. Dalezios
Remote Sens. 2021, 13(4), 568; https://doi.org/10.3390/rs13040568
Received: 4 January 2021 / Revised: 24 January 2021 / Accepted: 1 February 2021 / Published: 5 February 2021
(This article belongs to the Special Issue Remote Sensing for Agrometeorology)
Vegetation indices time series analysis is increasingly improved for characterizing agricultural land processes. However, this is challenging because of the multeity of factors affecting vegetation growth. In semiarid regions the rainfall, the soil properties and climate are strongly correlated with crop growth. These relationships are commonly analyzed using the normalized difference vegetation index (NDVI). NDVI series from two sites, belonging to different agroclimatic zones, were examined, decomposing them into the overall average pattern, residuals, and anomalies series. All of them were studied by applying the concept of the generalized Hurst exponent. This is derived from the generalized structure function, which characterizes the series’ scaling properties. The cycle pattern of NDVI series from both zones presented differences that could be explained by the differences in the climatic precipitation pattern and soil characteristics. The significant differences found in the soil reflectance bands confirm the differences in both sites. The scaling properties of NDVI original series were confirmed with Hurst exponents higher than 0.5 showing a persistent structure. The opposite was found when analyzing the residual and the anomaly series with a stronger anti-persistent character. These findings reveal the influences of soil–climate interactions in the dynamic of NDVI series of rainfed cereals in the semiarid. View Full-Text
Keywords: generalized structure function; generalized Hurst exponent; NDVI anomalies; rainfed crops; climate-soil interaction generalized structure function; generalized Hurst exponent; NDVI anomalies; rainfed crops; climate-soil interaction
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MDPI and ACS Style

Rivas-Tabares, D.A.; Saa-Requejo, A.; Martín-Sotoca, J.J.; Tarquis, A.M. Multiscaling NDVI Series Analysis of Rainfed Cereal in Central Spain. Remote Sens. 2021, 13, 568. https://doi.org/10.3390/rs13040568

AMA Style

Rivas-Tabares DA, Saa-Requejo A, Martín-Sotoca JJ, Tarquis AM. Multiscaling NDVI Series Analysis of Rainfed Cereal in Central Spain. Remote Sensing. 2021; 13(4):568. https://doi.org/10.3390/rs13040568

Chicago/Turabian Style

Rivas-Tabares, David Andrés, Antonio Saa-Requejo, Juan José Martín-Sotoca, and Ana María Tarquis. 2021. "Multiscaling NDVI Series Analysis of Rainfed Cereal in Central Spain" Remote Sensing 13, no. 4: 568. https://doi.org/10.3390/rs13040568

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