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Differences in precipitation and evapotranspiration between forested and deforested areas in the Amazon rainforest using remote sensing data

Abstract

With the constant deforestation observed in the Amazon region in recent decades, changes in local climates are unavoidable. Therefore, the aim of this study is to understand such climate changes by evaluating differences in precipitation (PRP), evapotranspiration (ET) and potential evapotranspiration (PET) between forested and deforested areas in the Brazilian Amazonia. Eight areas (four forested and four deforested) that maintained their land cover over a period of 15 years (2000–2014) were selected using PRODES (Legal Amazon Deforestation Monitoring Project) Digital’s remote sensing database. The PRP data were retrieved from the Tropical Rainfall Measurement Mission (TRMM, resolution of 0.25°), and the data of ET and PET were obtained from the moderate-resolution imaging spectroradiometer sensor (MODIS, resolution of 0.05°). The differences among PRP, ET and PET in each area were calculated using a regression model. The results show that ET was the only variable which presented a statistically significant difference between forested and deforested areas, mainly due to an intense decrease at the deforested sites during the dry season. Regarding PRP, a modest increase was observed on small areas, probably due to changes in local atmospheric dynamics, but on large areas decrease in PRP was noted. Nevertheless, in both cases there were no statistically significant differences between forested and deforested areas. PET presented a slightly increase value over deforested areas during the dry season, but not statistically significant as well.

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Acknowledgements

The authors would like to thank Instituto Tecnológico Vale (ITV) for providing financial and structural support in this study.

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Correspondence to Juarez Ventura de Oliveira.

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de Oliveira, J.V., Ferreira, D.B.d., Sahoo, P.K. et al. Differences in precipitation and evapotranspiration between forested and deforested areas in the Amazon rainforest using remote sensing data. Environ Earth Sci 77, 239 (2018). https://doi.org/10.1007/s12665-018-7411-9

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