Understanding the radar backscattering from flooded and nonflooded Amazonian forests: Results from canopy backscatter modeling

Wang, Yong; Hess, Laura L.; Filoso, Solange; Mélack, John M.

doi:10.1016/0034-4257(95)00140-9

Cited by 166 publications

(89 citation statements)

References 19 publications

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“…In the case of flooded herbaceous vegetation with low emergent biomass, a vertical incidence angle may diminish the probability of a first bounce in vegetation and a second one in the water (or vice versa), increasing the probability of reaching water. This observation is in marked contrast to what happens in forest environments, where for a given polarization and frequency, double-bounce scattering is more important in steep than in shallow incidence angles scenes [12,25,67].…”

Section: Scenecontrasting

confidence: 68%

Mapping Plant Functional Types in Floodplain Wetlands: An Analysis of C-Band Polarimetric SAR Data from RADARSAT-2

et al. 2016

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Abstract:The inclusion of functional approaches on wetland characterizations and on biodiversity assessments improves our understanding of ecosystem functioning. In the Lower Paraná River floodplain, we assessed the ability of C-band polarimetric SAR data of contrasting incidence angles to discriminate wetland areas dominated by different plant functional types (PFTs). Unsupervised H/α and H/A/α Wishart classifications were implemented on two RADARSAT-2 images differing in their incidence angles (FQ24 and FQ08). Obtained classes were assigned to the information classes (open water, bare soil and PFTs) by a priori labeling criteria that involved the expected interaction mechanisms between SAR signal and PFTs as well as the relative values of H and α. The product obtained with the shallow incidence angle scene had a higher accuracy than the one obtained with the steep incidence angle product (61.5% vs. 46.2%). We show how a systematic analysis of the H/A/α space can be used to improve the knowledge about the radar polarimetric response of herbaceous vegetation. The map obtained provides novel ecologically relevant information about plant strategies dominating the floodplain. Since the obtained classes can be interpreted in terms of their functional features, the approach is a valuable tool for predicting vegetation response to floods, anthropic impacts and climate change.

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Section: Scenecontrasting

confidence: 68%

Mapping Plant Functional Types in Floodplain Wetlands: An Analysis of C-Band Polarimetric SAR Data from RADARSAT-2

et al. 2016

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“…Richards et al (1987) reported the bright return of flooded forest in L band by corner reflection between trunks and water surface beneath the canopy. Early results from Hess et al (1995) deal with the mapping of inundated areas of the central Amazon floodplain with the SIR-C SAR, and Wang et al (1995) compared C-and L-bands with respect to the detection of flooding in Amazonian forests. Smith et al (1995Smith et al ( , 1996 estimated discharge from braided glacial rivers with ERS-1 SAR images.…”

Section: Previous Studiesmentioning

confidence: 99%

Floodplain water storage in the Negro River basin estimated from microwave remote sensing of inundation area and water levels

Frappart

Seyler

Martinez

et al. 2005

Remote Sensing of Environment

201

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. Floodplain water storage in the Negro River basin estimated from microwave remote sensing of inundation area and water levels. Remote Sensing of Environment, Elsevier, 2005, 99, pp.387-399 Abstract : The objective of this study is to determine spatio-temporal variations of water volume over inundated areas located in large river basins using combined observations from the Synthetic Aperture Radar (SAR) onboard the Japanese Earth Resources Satellite (JERS-1), the Topex/Poseidon (T/P) altimetry satellite, and in-situ hydrographic stations. Ultimately, the goal is to quantify the role of floodplains for partitioning water and sediment fluxes over the great fluvial basins of the world. SAR images are used to identify the type of surface (open water, inundated areas, forest) and, hence, the areas covered with water. Both radar altimetry data and in-situ hydrographic measurements yield water level time series. The basin of the Negro river, the tributary which carries the largest discharge to the Amazon river, was selected as a test site. By combining area estimates derived from radar images classification with changes in water level, variations of water volume (focusing on a seasonal cycle) have been obtained. The absence of relationship between water volume and inundated area, reflecting the diverse and widely dispersed floodplains of the basin, is one of the main result of this study.

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“…Studies employing multi-polarized data indicate advantages of like-polarization (HH or VV) for the seperation of flooded and non-flooded forests [11,32]. According to [12,30], the backscatter ratio between flooded and non-flooded forest is higher at HH polarization than at VV polarization. Backscatter is generally lower for cross-polarization (HV or VH) as depolarization does not make for ideal corner reflectors [33].…”

Section: Introductionmentioning

confidence: 99%

Backscatter Analysis Using Multi-Temporal and Multi-Frequency SAR Data in the Context of Flood Mapping at River Saale, Germany

2015

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Abstract:In this study, an analysis of multi-temporal and multi-frequency Synthetic Aperture Radar data is performed to investigate the backscatter behavior of various semantic classes in the context of flood mapping in central Europe. The focus is mainly on partially submerged vegetation such as forests and agricultural fields. The test area is located at River Saale, Saxony-Anhalt, Germany, which is covered by a time series of 39 TerraSAR-X data acquired within the time interval December 2009 to June 2013. The data set is supplemented by ALOS PALSAR L-band and RADARSAT-2 C-band data. The time series covers two inundations in January 2011 and June 2013 which allows evaluating backscatter variations between flood periods and normal water level conditions using different radar wavelengths. According to the results, there is potential in detecting flooding beneath vegetation in all microwave wavelengths, even in X-band for sparse vegetation or leaf-off forests.

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Understanding the radar backscattering from flooded and nonflooded Amazonian forests: Results from canopy backscatter modeling

Cited by 166 publications

References 19 publications

Mapping Plant Functional Types in Floodplain Wetlands: An Analysis of C-Band Polarimetric SAR Data from RADARSAT-2

Mapping Plant Functional Types in Floodplain Wetlands: An Analysis of C-Band Polarimetric SAR Data from RADARSAT-2

Floodplain water storage in the Negro River basin estimated from microwave remote sensing of inundation area and water levels

Backscatter Analysis Using Multi-Temporal and Multi-Frequency SAR Data in the Context of Flood Mapping at River Saale, Germany

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