Tendencia anual, anomalías y predicción del comportamiento de cobertura de vegetación con imágenes Landsat y MOD13Q1, microcuenca Apacheta, Región Ayacucho

Translated title of the contribution: Annual trend, anomalies and prediction of vegetation cover behavior with Landsat and MOD13Q1 images, Apacheta micro-basin, Ayacucho Region

Wilmer Moncada, Bram Willems, Alex Pereda, Cristhian Aldana, Jhony Gonzales

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Climate variability in the Apacheta micro-basin has an impact on vegetation behavior. The objective is to analyze the annual trend, anomalies and predict the behavior of vegetation cover (CV) with Landsat images and the MOD13Q1 product in the Apacheta micro-basin of the Ayacucho Region. For this purpose, the CV was classified and validated with the Kappa index (p-value=0.032; <0.05), obtaining a good agreement between the values observed in situ and the estimated in the Landsat images. The CV data were subjected to the Lilliefors normality test (p-value=0.0014; <0.05) indicating that they do not come from a normal distribution. CV forecasting was performed with the auto.arima, forecast and prophet packages, in R, according to the Box-Jenkins and ARIMA approaches, whose two-year future scenario is acceptable, but with higher bias. The results show an annual increasing CV trend of 3,378.96 ha with Landsat imagery and 3,451.95 ha with the MOD13Q1 product, by the end of 2020. The anomalies and the CV forecast also show a significant increase in the last 9 years, becoming higher in the forecasted years, 2021 and 2022.

Translated title of the contributionAnnual trend, anomalies and prediction of vegetation cover behavior with Landsat and MOD13Q1 images, Apacheta micro-basin, Ayacucho Region
Original languageSpanish
Pages (from-to)73-86
Number of pages14
JournalRevista de Teledeteccion
Volume2022
Issue number59
DOIs
StatePublished - 2022

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© 2022, Universidad Politecnica de Valencia.. All rights reserved.

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