Influence of the Rainfall Anomaly Index on vegetation in the Pajeú river basin watershed Through Remote Sensing
DOI:
https://doi.org/10.51359/2238-6211.2024.258619Keywords:
precipitation, Google Earth Engine, CHIRPS, EVI-2Abstract
Precipitation is one of the main components of the hydrological cycle and has a strong influence on terrestrial features, such as vegetation. The analysis of the relationship between precipitation variability and vegetation vigor through remote sensing plays a fundamental role in understanding the impacts of climate change on ecosystem dynamics. Based on this, the present article aims to quantify the Rainfall Anomaly Index (RAI) for the Pajeú River Watershed using precipitation data from the CHIRPS group, as well as to examine the vegetation response to these anomalies through the Enhanced Vegetation Index (EVI-2), quantified using reflectance data from the MOD09Q1 (Terra satellite) and MYD09Q1 (Aqua satellite) products. The sample correlation between RAI and EVI-2 yielded a correlation coefficient of r = 0.77, indicating that an increase in RAI (precipitation growth) directly contributes to increased vegetative vigor. However, the simple regression analysis yielded an R2 = 0.58, indicating that the relationship between the variables is not linear and that vegetation is influenced by other factors such as temperature and relative humidity. Finally, this study provides evidence of the effectiveness of RAI in analyzing rainfall anomalies, as well as EVI-2 in exploring vegetation health variability and terrestrial dynamics.
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