Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1155228
Registro completo de metadados
Campo DCValorIdioma
dc.contributor.authorTEIXEIRA, A. H. DE C.
dc.contributor.authorLEIVAS, J. F.
dc.contributor.authorTAKEMURA, C. M.
dc.contributor.authorSILVA, G. B. S. da
dc.contributor.authorGARCON, E. A. M.
dc.contributor.authorSOUSA, I.
dc.contributor.authorCESAR SILVA
dc.date.accessioned2023-07-24T20:23:55Z-
dc.date.available2023-07-24T20:23:55Z-
dc.date.created2023-07-24
dc.date.issued2023
dc.identifier.citationEnvironmental Monitoring and Assessment, v. 195, n. 944, 2023.
dc.identifier.issn1573-2959
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1155228-
dc.descriptionAbstract: The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale remote sensing environmental indicators in Brazilian biomes. MODIS MOD13Q1 reflectance product and gridded weather data for the year 2016 were used to demonstrate the suitability of the algorithm to monitor the dynamics of environmental remote sensing indicators along a year in the Brazilian biomes, Amazon, Caatinga, Cerrado, Pantanal, Atlantic Forest, and Pampa. Significant spatial and temporal variations in precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P−ET) and water productivity (WP = ET/BIO). The highest WB and WP differences were detected in the wettest biomes, Amazon, Atlantic Forest, and Pampa, when compared with the driest biome, Caatinga. Rainfall distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e., the ET to reference evapotranspiration (ET0) ratio. However, there was a gap between ETf and WB, which may be related to the time needed for recovering good soil moisture conditions after rainfalls. For some biomes, BIO related most to the levels of absorbed photosynthetically active radiation (Amazon and Atlantic Forest), while for others, BIO followed most the soil moisture levels, depicted by ETf (Caatinga, Cerrado, Pantanal, and Pampa). The large-scale modeling showed suitability for monitoring the water and vegetation conditions, making way to detect anomalies for specific periods along the year by using historical images and weather data, with strong potential to support public policies for management and conservation of natural resources and with possibilities for replication of the methods in other countries.
dc.language.isopor
dc.rightsopenAccess
dc.subjectPrecipitation
dc.subjectWater productivity
dc.titleRemote sensing environmental indicators for monitoring spatial and temporal dynamics of weather and vegetation conditions: applications for Brazilian biomes.
dc.typeArtigo de periódico
dc.subject.nalthesaurusEvapotranspiration
dc.subject.nalthesaurusWater balance
dc.subject.nalthesaurusBiomass production
riaa.ainfo.id1155228
riaa.ainfo.lastupdate2023-07-24
dc.identifier.doidoi.org/10.1007/s10661-023-11560-8
dc.contributor.institutionANTONIO HERIBERTO DE CASTRO TEIXEIRA, UNIVERSIDADE FEDERAL DE SERGIPE; JANICE FREITAS LEIVAS, CNPM; CELINA MAKI TAKEMURA, CNPM; GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPMA; EDLENE APARECIDA MONTEIRO GARCON, CNPM; INAJÁ SOUSA, UNIVERSIDADE FEDERAL DE SERGIPE; SILVA, C., UNIVERSIDADE ESTADUAL DE CAMPINAS.
Aparece nas coleções:Artigo em periódico indexado (CNPM)

Arquivos associados a este item:
Arquivo TamanhoFormato 
6143.pdf7,3 MBAdobe PDFVisualizar/Abrir
Mostrar registro simples do item Visualizar estatísticas

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace