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dc.contributor.authorGONÇALVES, T. G.pt_BR
dc.contributor.authorMACIEL, D. A.pt_BR
dc.contributor.authorALVES, H. M. R.pt_BR
dc.contributor.authorVOLPATO, M M. L.pt_BR
dc.contributor.authorVIEIRA, T. G. C.pt_BR
dc.contributor.authorDANTAS, M. F.pt_BR
dc.date.accessioned2016-03-17T11:11:11Zpt_BR
dc.date.available2016-03-17T11:11:11Zpt_BR
dc.date.created2016-03-17pt_BR
dc.date.issued2015pt_BR
dc.identifier.citationIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015. p. 1502-1507 , 2015pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1041257pt_BR
dc.descriptionLocated in the middle of the Rio Grande in Minas Gerais state, Furnas hydroelectric occupies an area of 1440 km², with an estimated volume of 17,217 km³ used to generate 1216 megawatts of power. Around the lake, other economic activities such as agriculture, pisciculture and tourism are also important. A shortage of rainfall in the region in 2014 heavily impacted these activities, causing also a decrease in the reservoir?s power generation capacity. The aim of this study was to assess the reduction of the volume of water in the reservoir using remote sensing and GIS. Landsat 8 26/04/2013 and 19/08/2014 satellite images were compared. The images were processed by eCognition Developer and Arcgis 10.2. It was observed that, in the 2013 image, the reservoir area was at 1134 km2 of water and 71.51% of its capacity. In the 2014 image, the area decreased to 807,42km2 and 27.55% capacity. This difference showed a reduction of 7,082km³ in volume in 16 months. These results show the applicability of satellite imagery and GIS to estimate reservoir areas over time, assisting various sectors in decision making processes and helping to mitigate the consequences of droughts.pt_BR
dc.language.isoporpt_BR
dc.rightsopenAccesspt_BR
dc.titleAvaliação do nível de água do reservatório de Furnas nos anos de 2013 e 2014, utilizando imagens Landsat-8.pt_BR
dc.typeArtigo em anais e proceedingspt_BR
dc.date.updated2016-03-18T11:11:11Zpt_BR
dc.subject.thesagroSensoriamento remotopt_BR
dc.subject.nalthesaurusRemote sensingpt_BR
dc.subject.nalthesaurusDroughtpt_BR
dc.subject.nalthesaurusGeographic information systemspt_BR
riaa.ainfo.id1041257pt_BR
riaa.ainfo.lastupdate2016-03-18pt_BR
dc.contributor.institutionTHAIS GABRIELA GONÇALVES, UFLA; DANIEL ANDRADE MACIEL, UFLA; HELENA MARIA RAMOS ALVES, SAPC; MARGARETE MARIN LORDELO VOLPATO, EPAMIG; TATIANA GROSSI CHQUILOFF VIEIRA, EPAMIG; MAYARA FONTES DANTAS, EPAMIG.pt_BR
Appears in Collections:Artigo em anais de congresso (SAPC)

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