Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data

Martinez, Jean‐Michel; Toan, Thuy Le

doi:10.1016/j.rse.2006.11.012

Cited by 314 publications

(212 citation statements)

References 46 publications

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“…atualmente, no ponto de coleta do testemunho Ta14, o nível médio das altas águas é de 550 cm enquanto o nível médio das águas baixas é de 50 cm durante um ciclo hidrológico , Martinez & Le Toan, 2007. Mas deve-se considerar que a unidade V vai de 270 a 199 cm da coluna sedimentar, ou seja, o topo da unidade está situado 250 cm abaixo do nível mínimo atual das águas.…”

Section: Discussionunclassified

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Reconstituição paleoambiental do Lago Santa Ninha, Várzea do Lago Grande de Curuai, Pará, Brasil

Moreira

Cordeiro

Turcq³

2009

Acta Amaz.

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RESUMOeste estudo teve por objetivo reconstituir as mudanças paleoambientais e paleohidrológicas no baixo amazonas. um testemunho de sedimento foi coletado no Lago Santa Ninha, na várzea do Lago Grande de curuai, localizada na margem direita do rio amazonas a aproximadamente 850 km da foz. o teor de água, a granulometria, as datações com carbono 14, os conteúdos de carbono orgânico e nitrogênio total e o isótopo estável do carbono (δ 13 c) foram utilizados para determinar os processos sedimentares a que o meio esteve submetido. o testemunho estudado possui 270 cm de comprimento que corresponde a um período de 5600 anos cal aP. este estudo colocou em evidência diferentes ambientes sedimentares: na base do testemunho até 4900 anos cal aP há uma vegetação inundada que foi gradualmente substituida por bancos de gramíneas e por uma planicie com secas sazonais em 4000 anos cal aP até alcançar, desde 600 anos aP as condições atuais deste lago. estas alterações podem ter ocorrido em decorrência de mudanças no ciclo hidrológico do rio amazonas que, por sua vez, também são reflexos de alterações climáticas.PALAVRAS-CHAVES: paleohidrologia, paleoambientes, amazônia, várzeas. Paleoenvironmental reconstruction of an Amazon floodplain lake, Lago Santa Ninha, Varzea do Lago Grande de Curuai, Pará, BrasilABSTRACT Physical, chemical and geochemical characteristics of lacustrine sediments were studied to reconstruct paleohydrologyical control on sedimentation in an amazonian floodplain. a core was collected at the Lago Grande de curuai floodplain, in the Santa Ninha Lake, located on the right margin of the amazon river at 850 km of the estuary. Water content, granulometry, radiocarbon dating, organic carbon, nitrogen content and δ 13 c were used to characterize the sedimentary processes. The core is 270 cm-long which corresponds to 5600 cal years BP. The core points out different sedimentary environments: flooded vegetation at the base of the core till 4900 cal years BP is substituted by grass banks changing to a floodplain encompassing prolonged annual dryness at 4000 cal years BP. Since 600 cal years BP, the present day Varzea Lake, permanently over flooded, has been installed.

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Section: Discussionunclassified

“…estas áreas inundadas são localmente conhecidas como várzeas e ocupam uma área que varia entre 140 000 km² e 500 000 km², dependendo da hidrologia do rio (Martinez & Le Toan, 2007).…”

Section: Introductionunclassified

Reconstituição paleoambiental do Lago Santa Ninha, Várzea do Lago Grande de Curuai, Pará, Brasil

Moreira

Cordeiro

Turcq³

2009

Acta Amaz.

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“…Unlike optical (visible/infrared) sensors, synthetic aperture radar (SAR) sensors, because of their capability to operate during daytime/night time and in almost all weather conditions, have emerged as one of the most important tools for providing reliable and near-real-time information on flood disasters. The potential of the SAR data for flood detection and mapping has been demonstrated by several previous investigations (Sugimura et al 2003;Martinez & Toan 2007). Mapping of water surface using SAR is possible because the SAR backscatter is very low due to the specular reflection when the water surface is smooth (Di Baldassarre et al, 2011).…”

Section: Introductionmentioning

confidence: 94%

An evaluation of flood inundation mapping from MODIS and ALOS satellites for Pakistan

Amarnath

Rajah

2015

Geomatics, Natural Hazards and Risk

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The paper presents a moderate resolution imaging spectroradiometer (MODIS) time-series imagery-based algorithm for detection and mapping of seasonal and annual changes in flood extent, and tests this using the flooding of the Indus River Basin in 2010 À one of the greatest recent disasters that affected more than 25 million people in Pakistan. The algorithm was applied to produce inundation maps for 10 annual flood seasons over the period from 2000 to 2011. The MODIS flood products were validated in comparison with advanced land observing system (ALOS) sensors, which have both advanced visible and near infrared radiometer and phased array type L-band synthetic images using the flood fraction comparison method. A simple threshold method is created to cluster the data to identify the flood pixels in the imagery. Calculations are then made to estimate a flood area for each resolution. A statistical study is performed to analyze false positive and false negative rates using the ALOS sensors as 'ground truth'. Comparison of two flood products at a grid size of 10 km resulted in the coefficient of determination range of 0.72À0.97. This research points to a relevant spatial resolution that could be effectively used to obtain accurate mapped products of the extent of the inundated area. The approach can be used to quantify the damage caused by floods.

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“…The mapping accuracy is assessed on one intermediate flood stage, showing a precision in excess of 90%. But to achieve this precision, the proposed classifier should be built on more than eight images (Martinez and Le Toan 2007).…”

Section: Existing Approaches To Flood Extent Extractionmentioning

confidence: 99%

Grid system for flood extent extraction from satellite images

2008

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Floods are among the most devastating natural hazards in the world, affecting more people and causing more property damage than any other natural phenomena. One of the important problems associated with flood monitoring is a flood extent extraction from satellite imagery, since it is impractical to acquire the flood area through field observations. This paper presents a new method to the flood extent extraction from synthetic-aperture radar (SAR) images that is based on intelligent computations. In particular, we apply artificial neural networks, selforganizing Kohonen's maps (SOMs), for SAR image segmentation and classification. We implemented our approach in a Grid system that was used to process data from three different satellite sensors: ERS-2/SAR during the flooding on the river Tisza, Ukraine and Hungary (2001), ENVISAT/ASAR WSM (Wide Swath Mode) and RADAR-SAT-1 during the flooding on the river Huaihe, China (2007).

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Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data

Cited by 314 publications

References 46 publications

Reconstituição paleoambiental do Lago Santa Ninha, Várzea do Lago Grande de Curuai, Pará, Brasil

Reconstituição paleoambiental do Lago Santa Ninha, Várzea do Lago Grande de Curuai, Pará, Brasil

An evaluation of flood inundation mapping from MODIS and ALOS satellites for Pakistan

Grid system for flood extent extraction from satellite images

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