Relationship between macrophyte stand variables and radar backscatter at L and C band, Tucuruí reservoir, Brazil

Novo, Evlyn Márcia Leão de Moraes; Costa, Maycira; Mantovani, José Eduardo; Lima, I.B.T.

doi:10.1080/01431160110092885

Cited by 41 publications

(24 citation statements)

References 6 publications

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“…However, further research and development is needed to quantify not only the difference in vegetation versus no vegetation, but also how different resolutions, bands, and angles of radar reflect off different vegetation types, densities, and heights. It has been suggested that C-band imagery should be used when trying to map leaf shape and that L-band is more accurate for measuring aboveground biomass and stand height [98]. Other research has demonstrated that a multi-temporal and multi-incidence angle was the best approach, with steep incidence angles for mapping wetlands and large incidence angles for detecting open water from land [99][100][101].…”

Section: Resultsmentioning

confidence: 99%

A Collection of SAR Methodologies for Monitoring Wetlands

et al. 2015

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Abstract:Wetlands are an important natural resource that requires monitoring. A key step in environmental monitoring is to map the locations and characteristics of the resource to better enable assessment of change over time. Synthetic Aperture Radar (SAR) systems are helpful in this way for wetland resources because their data can be used to map and monitor changes in surface water extent, saturated soils, flooded vegetation, and changes in wetland vegetation cover. We review a few techniques to demonstrate SAR capabilities for wetland monitoring, including the commonly used method of grey-level thresholding for mapping surface water and highlighting changes in extent, and approaches for polarimetric decompositions to map flooded vegetation and changes from one class of land cover to another. We use the Curvelet-based change detection and the Wishart-Chernoff Distance approaches to show how they substantially improve mapping of flooded vegetation and flagging areas of change, respectively. We recommend that the increasing availability SAR data and the proven ability of these data to map various components of wetlands mean SAR should be considered as a critical component of a wetland monitoring system.

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Section: Resultsmentioning

confidence: 99%

A Collection of SAR Methodologies for Monitoring Wetlands

et al. 2015

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“…Results from this analysis suggest that, although an acceptable accuracy can be achieved with Landsat and a DEM alone, the SAR variables are important for improving the class accuracy of bog and fen. It may also be possible to achieve higher classification accuracies with only SAR variables and a DEM if multiple SAR images acquired across different dates [68][69][70][71], incidence angles [72][73][74], and moisture conditions [75] are combined as inputs to the classifier. In some cases, classification accuracy can increase significantly [75].…”

Section: Variable Importancementioning

confidence: 99%

Moving to the RADARSAT Constellation Mission: Comparing Synthesized Compact Polarimetry and Dual Polarimetry Data with Fully Polarimetric RADARSAT-2 Data for Image Classification of Peatlands

et al. 2017

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For this research, the Random Forest (RF) classifier was used to evaluate the potential of simulated RADARSAT Constellation Mission (RCM) data for mapping landcover within peatlands. Alfred Bog, a large peatland complex in Southern Ontario, was used as a test case. The goal of this research was to prepare for the launch of the upcoming RCM by evaluating three simulated RCM polarizations for mapping landcover within peatlands. We examined (1) if a lower RCM noise equivalent sigma zero (NESZ) affects classification accuracy, (2) which variables are most important for classification, and (3) whether classification accuracy is affected by the use of simulated RCM data in place of the fully polarimetric RADARSAT-2. Results showed that the two RCM NESZs (−25 dB and −19 dB) and three polarizations (compact polarimetry, HH+HV, and VV+VH) that were evaluated were all able to achieve acceptable classification accuracies when combined with optical data and a digital elevation model (DEM). Optical variables were consistently ranked to be the most important for mapping landcover within peatlands, but the inclusion of SAR variables did increase overall accuracy, indicating that a multi-sensor approach is preferred. There was no significant difference between the RF classifications which included RADARSAT-2 and simulated RCM data. Both medium-and high-resolution compact polarimetry and dual polarimetric RCM data appear to be suitable for mapping landcover within peatlands when combined with optical data and a DEM.

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“…This attribute of SAR was first noticed with Seasat data (MacDonald et al 1980) and is a wellknown capability of SAR (Hess et al 1990). The sensitivity to the target's moisture content and structural differences in the types of wetland vegetation also provide a capability for mapping wetlands (Pope et al 1994, Brisco and Pultz 1998, Novo et al 2002 especially when combined with optical data (Wang et al 1998, Toyra andPietroniro 2005). This is described in more detail in the next section.…”

Section: Flood and Flooded Vegetation Monitoringmentioning

confidence: 99%

“…SAR interferometry at C-band has also been successfully used for delineating flooded and non-flooded regions (Morley et al 1996). Research has shown that a multi-frequency combination is preferred, such as L and C-band, which can provide discrimination between a larger number of wetland vegetation types including flooded forest and aquatic macrophytes (Costa et al 2002, Novo et al 2002.…”

Section: Flood and Flooded Vegetation Monitoringmentioning

confidence: 99%

Water resource applications with RADARSAT-2 – a preview

Brisco¹,

Touzi²,

Sanden³

et al. 2008

International Journal of Digital Earth

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Fresh water is arguably the most vital resource for many aspects of a healthy and stable environment. Monitoring the extent of surface water enables resource managers to detect perturbations and long term trends in water availability, and set consumption guidelines accordingly. Potential end-users of water-related observations are numerous and reflect society as a whole. They encompass scientists and managers at all levels of government, aboriginal groups, water/ power utility managers, farmers, planners, engineers, hydrologists, medical researchers, climate scientists, recreation enthusiasts, public school to postgraduate students, many special interest groups and the general public. Water data and analyses generate information products that benefit water resources planning and management, engineering design, plant operations, navigation activities, health research, water quality assessments and ecosystem management. As well, they serve as inputs for flood and drought warnings and weather and climate prediction models. Radar data in general, and RADARSAT in particular, are very good for detecting open surface water and have been used operationally for flood monitoring in many countries. Significant radar data archives now exist to analyse seasonal, annual and decadal trends, in order to attain a better understanding of the freshwater cycle. Radar data are also useful for wetland classification and soil moisture estimation. With the increasing pressure on water resources, both from a quality as well as a quantity perspective, the need will continue to increase for reliable information.RADARSAT-2 has several innovations that will enhance the ability to provide useful information about water resources. This paper provides an overview of the use of radar in general, and RADARSAT-2 in particular, for the generation of information products useful to water resource managers.

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Relationship between macrophyte stand variables and radar backscatter at L and C band, Tucuruí reservoir, Brazil

Cited by 41 publications

References 6 publications

A Collection of SAR Methodologies for Monitoring Wetlands

A Collection of SAR Methodologies for Monitoring Wetlands

Moving to the RADARSAT Constellation Mission: Comparing Synthesized Compact Polarimetry and Dual Polarimetry Data with Fully Polarimetric RADARSAT-2 Data for Image Classification of Peatlands

Water resource applications with RADARSAT-2 – a preview

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