Title
Annual trend, anomalies and prediction of vegetation cover behavior with Landsat and MOD13Q1 images, Apacheta micro-basin, Ayacucho Region
Other title
Tendencia anual, anomalías y predicción del comportamiento de cobertura de vegetación con imÔgenes Landsat y MOD13Q1, microcuenca Apacheta, Región Ayacucho
Date Issued
01 January 2022
Access level
open access
Resource Type
journal article
Publisher(s)
Universidad Politecnica de Valencia
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.
Start page
73
End page
86
Volume
2022
Issue
59
Language
Spanish
OCDE Knowledge area
Investigación climÔtica Geociencias, Multidisciplinar Oceanografía, Hidrología, Recursos hídricos
Scopus EID
2-s2.0-85124581867
Source
Revista de Teledeteccion
ISSN of the container
11330953
Sponsor(s)
Este trabajo ha sido posible gracias a los pro-yectos ā€œStrengthening resilience of Andean river basin headwaters facing global changeā€ (PGA_084063), financiado por el Programa PEER de USAID y ā€œModelado de aguas subte-rrĆ”neas en los ecosistemas de humedales de la microcuenca Apachetaā€, financiado por FOCAM de la Universidad Nacional de San Cristóbal de Huamanga. Los autores tambiĆ©n agradecen a la Universidad Nacional de Frontera por su apoyo incondicional.
Sources of information: Directorio de Producción Científica Scopus