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Spatio-Temporal Response of Vegetation Indices to Rainfall and Temperature in A Semiarid Region

Edith Olmos-Trujillo, Julián González-Trinidad, Hugo Enrique Júnez-Ferreira, Anuard Pacheco-Guerrero, Carlos Bautista-Capetillo, Claudia Ávila-Sandoval, Eric Galván-Tejada

2020Sustainability55 citationsDOIOpen Access PDF

Abstract

In this research, vegetation indices (VIs) were analyzed as indicators of the spatio-temporal variation of vegetation in a semi-arid region. For a better understanding of this dynamic, interactions between vegetation and climate should be studied more widely. To this end, the following methodology was proposed: (1) acquire the NDVI, EVI, SAVI, MSAVI, and NDMI by classification of vegetation and land cover categories in a monthly period from 2014 to 2018; (2) perform a geostatistical analysis of rainfall and temperature; and (3) assess the application of ordinary and uncertainty least squares linear regression models to experimental data from the response of vegetation indices to climatic variables through the BiDASys (bivariate data analysis system) program. The proposed methodology was tested in a semi-arid region of Zacatecas, Mexico. It was found that besides the high values in the indices that indicate good health, the climatic variables that have an impact on the study area should be considered given the close relationship with the vegetation. A better correlation of the NDMI and EVI with rainfall and temperature was found, and similarly, the relationship between VIs and climatic factors showed a general time lag effect. This methodology can be considered in management and conservation plans of natural ecosystems, in the context of climate change and sustainable development policies.

Topics & Concepts

Vegetation (pathology)Normalized Difference Vegetation IndexEnvironmental scienceBivariate analysisLagAridContext (archaeology)Enhanced vegetation indexClimate changeRegression analysisVegetation coverLinear regressionLand coverPhysical geographyVegetation IndexHydrology (agriculture)Land useGeographyEcologyStatisticsMathematicsGeologyComputer networkArchaeologyPathologyBiologyMedicineGeotechnical engineeringComputer scienceRemote Sensing in AgricultureLand Use and Ecosystem ServicesForest ecology and management