Drought monitoring based on remote sensing in a grain-producing region in the Cerrado – Amazon Transition, Brazil.

dc.contributor.authorCarvalho, Mairon Ânderson Cordeiro Correa de
dc.contributor.authorUliana, Eduardo Morgan
dc.contributor.authorSilva, Demetrius David da
dc.contributor.authorAires, Uilson Ricardo Venâncio
dc.contributor.authorMartins, Camila Aparecida da Silva
dc.contributor.authorSousa Junior, Marionei Fomaca de
dc.contributor.authorCruz, Ibraim Fantin da
dc.contributor.authorMendes, Múcio André dos Santos Alves
dc.date.accessioned2022-09-28T19:54:13Z
dc.date.available2022-09-28T19:54:13Z
dc.date.issued2020pt_BR
dc.description.abstractDrought is a natural disaster that affects a country’s economy and food security. The monitoring of droughts assists in planning assertive actions to mitigate the resulting environmental and economic impacts. This work aimed to evaluate the performance of the standardized precipitation index (SPI) using rainfall data estimated by orbital remote sensing in the monitoring of meteorological drought in the Cerrado–Amazon transition region, Brazil. Historical series from 34 rain gauge stations, in addition to indirect measurements of monthly precipitation obtained by remote sensing using the products CHIRPS-2.0, PERSIANN-CDR, PERSIANN-CCS, PERSIANN, GPM-3IMERGMv6, and GPM-3IMERGDLv6, were used in this study. Drought events detected by SPI were related to a reduction in soybean production. The SPI calculated from the historical rain series estimated by remote sensing allowed monitoring droughts, enabling a high detailing of the spatial variability of droughts in the region, mainly during the soybean development cycle. Indirect precipitation measures associated with SPI that have adequate performance for detecting droughts in the study region were PERSIANN-CCS (January), CHIRPS-2.0 (February and November), and GPM-3IMERGMv6 (March, September, and December). The SPI and the use of precipitation data estimated by remote sensing are effective for characterizing and monitoring meteorological drought in the study region.pt_BR
dc.identifier.citationCARVALHO, M. A. C. C. de et al. Drought monitoring based on remote sensing in a grain-producing region in the Cerrado – Amazon Transition, Brazil. Water, v. 12, 2020. Disponível em: <https://www.mdpi.com/2073-4441/12/12/3366>. Acesso em: 29 abr. 2022.pt_BR
dc.identifier.doihttps://doi.org/10.3390/w12123366pt_BR
dc.identifier.issn2073-4441
dc.identifier.urihttp://www.repositorio.ufop.br/jspui/handle/123456789/15525
dc.language.isoen_USpt_BR
dc.rightsabertopt_BR
dc.rights.licenseThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Fonte: o PDF do artigo.pt_BR
dc.subjectAgricultural planningpt_BR
dc.subjectSoybeanpt_BR
dc.subjectClimate riskpt_BR
dc.subjectNatural disasterpt_BR
dc.subjectWater resource managementpt_BR
dc.titleDrought monitoring based on remote sensing in a grain-producing region in the Cerrado – Amazon Transition, Brazil.pt_BR
dc.typeArtigo publicado em periodicopt_BR

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