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América Latina y el Caribe
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https://biblioteca-repositorio.clacso.edu.ar/handle/CLACSO/74641Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.contributor | en-US | |
| dc.creator | De Almeida Pereira, Gabriel Henrique | - |
| dc.creator | Cechim Júnior, Clóvis | - |
| dc.creator | Fronza, Giovani | - |
| dc.creator | Deppe, Flávio André Cecchini | - |
| dc.date | 2019-08-28 | - |
| dc.date.accessioned | 2022-03-21T18:27:53Z | - |
| dc.date.available | 2022-03-21T18:27:53Z | - |
| dc.identifier | https://revistas.ufpr.br/raega/article/view/66988 | - |
| dc.identifier | 10.5380/raega.v46i3.66988 | - |
| dc.identifier.uri | http://biblioteca-repositorio.clacso.edu.ar/handle/CLACSO/74641 | - |
| dc.description | The Pantanal is one of the most important and preserved biomes in Brazil. This region is annually flooded due to episodes of precipitation along the Paraguay River and its tributaries. Understanding the dynamics of flooding is extreme important since it influences the entire Pantanal ecosystem. Remote Sensing data is an alternative to the identification of flooded areas and their changes in different periods. Among the possible sensors capable of mapping these flooded areas Radar sensor is one of the most attractive – mainly due to the low influence of cloud cover and atmospheric conditions, allowing imaging in dry or rainy seasons. For this work, Radar images from Sentinel 1 satellites for the years 2016, 2017, and 2018 were used. All available data from these years for the study area were used to generate images that represent the seasonality in the region for each year. In total, 1141 Sentinel 1 radar images were processed. The processing of such amount of data was possible through Google Earth Engine platform, which is capable of robust processing of a large amount of data, especially Remote Sensing data. At the end, it was possible to generate images that represent the seasonality of each year. It was also possible to compare the years, highlighting the differences between flooded areas indicating the periods of major precipitation. | en-US |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.language | por | - |
| dc.publisher | UFPR | pt-BR |
| dc.relation | https://revistas.ufpr.br/raega/article/view/66988/39346 | - |
| dc.relation | https://revistas.ufpr.br/raega/article/view/66988/39307 | - |
| dc.rights | Direitos autorais 2019 Raega - O Espaço Geográfico em Análise | pt-BR |
| dc.source | RA'E GA Journal - The Geographic Space in Analysis; v. 46, n. 3 (2019): 7º GeoPantanal - Simpósio de Geotecnologias no Pantanal; 88-100 | en-US |
| dc.source | Raega - O Espaço Geográfico em Análise; v. 46, n. 3 (2019): 7º GeoPantanal - Simpósio de Geotecnologias no Pantanal; 88-100 | pt-BR |
| dc.source | 2177-2738 | - |
| dc.source | 1516-4136 | - |
| dc.source | 10.5380/raega.v46i3 | - |
| dc.subject | Sensoriamento Remoto; Recursos Hídricos | en-US |
| dc.subject | Remote Sensing; image processing; time series images; seasonality; wetlands | en-US |
| dc.title | MULTITEMPORAL ANALYSIS OF SAR IMAGES FOR DETECTION OF FLOODED AREAS IN PANTANAL | en-US |
| dc.type | info:eu-repo/semantics/article | - |
| dc.type | info:eu-repo/semantics/publishedVersion | - |
| dc.type | pt-BR | |
| Aparece en las colecciones: | Programa de Pós-graduação em Geografía - PPGGeo/UFPR - Cosecha | |
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