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

IF 0.4 Q4 REMOTE SENSING Revista de Teledeteccion Pub Date : 2022-01-31 DOI:10.4995/raet.2022.15672
Wilmer Moncada, B. Willems, Alex Pereda, Cristhian Aldana, Jhony Gonzales
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引用次数: 1

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 anual 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.
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利用Landsat和Mod13q1图像,阿亚库乔地区阿帕切塔微流域,植被覆盖行为的年度趋势、异常和预测
阿帕契塔微盆地气候变率对植被行为有影响。目的是利用Landsat图像和MOD13Q1产品分析阿亚库乔地区阿帕切塔微盆地植被覆盖(CV)的年变化趋势、异常特征,并预测其变化规律。为此,用Kappa指数对CV进行分类和验证(p值= 0.032;0.05),获得了原位观测值与Landsat图像估计值之间的良好一致性。CV数据采用Lilliefors正态性检验(p值= 0.0014;0.05),表明它们不是来自正态分布。CV预测是用auto进行的。根据Box-Jenkins和arima方法,其两年的未来情景是可以接受的,但偏差较大。结果表明,到2020年底,Landsat影像的CV值为3378.96 ha, MOD13Q1产品的CV值为3451.95 ha, CV值呈年递增趋势。在过去的9年中,异常和CV预测也显示出显著的增加,在预测年份,2021年和2022年变得更高。
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来源期刊
Revista de Teledeteccion
Revista de Teledeteccion REMOTE SENSING-
CiteScore
1.80
自引率
14.30%
发文量
11
审稿时长
10 weeks
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