Analysis of environmental variables and deforestation in the amazon using logistical regression models.

In this study, we applied a multivariate logistic regression model to identify deforested areas and evaluate the current effects on environmental variables in the Brazilian state of Rondônia, located in the southwestern Amazon region using data from the MODIS/Terra sensor. The variables albedo, temperature, evapotranspiration, vegetation index, and gross primary productivity were analyzed from 2000 to 2022, with surface type data from the PRODES project as the dependent variable. The accuracy of the models was evaluated by the parameters area under the curve (AUC), pseudo R, and Akaike information criterion, in addition to statistical tests.

Hydrometeorological conditions in the semiarid and east coast regions of Northeast Brazil in the 2012-2017 period.

Various studies have identified that between 2012 and 2017, Brazil's semiarid region suffered severe drought. However, few studies have analyzed whether this drought also affected the eastern coastal region of Northeast Brazil (ENEB). Therefore, the objective of this work is to identify rainfall anomalies in these regions and verify the hydrometeorological impact on reservoirs in the 2012-2017 interval.