Wetland characterization using polarimetric RADARSAT-2 capability

Touzi, R.; Deschamps, A.; Rother, G.

doi:10.5589/m07-047

Cited by 113 publications

(33 citation statements)

References 25 publications

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“…As this effect seems to relate to complex factors (e.g., microwave incident angle, vegetation structure, density, and water levels), completely removing the effect is difficult when solely using the backscatter intensity. A potential solution is to use polarimetry decomposition [18,48] to distinguish the inundated vegetation, although it is not easy to obtain a substantial number of full polarimetry data, which is necessary for accurate polarimetry decomposition [18].…”

Section: Discussionmentioning

confidence: 99%

Monitoring of an Indonesian Tropical Wetland by Machine Learning-Based Data Fusion of Passive and Active Microwave Sensors

et al. 2018

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In this study, a novel data fusion approach was used to monitor the water-body extent in a tropical wetland (Lake Sentarum, Indonesia). Monitoring is required in the region to support the conservation of water resources and biodiversity. The developed approach, random forest database unmixing (RFDBUX), makes use of pixel-based random forest regression to overcome the limitations of the existing lookup-table-based approach (DBUX). The RFDBUX approach with passive microwave data (AMSR2) and active microwave data (PALSAR-2) was used from 2012 to 2017 in order to obtain PALSAR-2-like images with a 100 m spatial resolution and three-day temporal resolution. In addition, a thresholding approach for the obtained PALSAR-2-like backscatter coefficient images provided water body extent maps. The validation revealed that the spatial patterns of the images predicted by RFDBUX are consistent with the original PALSAR-2 backscatter coefficient images (r = 0.94, RMSE = 1.04 in average), and that the temporal pattern of the predicted water body extent can track the wetland dynamics. The PALSAR-2-like images should be a useful basis for further investigation of the hydrological/climatological features of the site, and the proposed approach appears to have the potential for application in other tropical regions worldwide. and growth of the neighboring countries of Indonesia. This development policy has resulted in rapid population growth and large changes in land use and land cover in the watershed, which may impact the water quality and dynamics of it [4].Geographical information is needed regarding the lake area to support the conservation of water resources and biodiversity. This is especially important for identifying the water-body dynamics, because during the dry season, the volume of water is very small and found only in the main river, soil basins, and oxbow lakes. During the rainy season, the water overflows inundated areas, lakes, puddles, and river courses. This annual inundation increases the variety of habitats available to the aquatic organisms [5]. In addition to local factors, the amount of lake water is strongly affected by global climate variability and events. For example, the lake becomes extremely dry in the El Niño years [6]. This means that the water-extent variability is controlled by both seasonal changes and the far less predictable annual changes. Even though long-term, frequent, and detailed mapping of the lake water extent is desirable and needed, few studies have attempted it.Satellite remote sensing is suitable for such a purpose. In fact, many techniques for monitoring wetlands have been proposed and developed [7]. In particular, microwave remote sensing is frequently used because it has two advantages, a high sensitivity to surface water instead of liquid water on the ground and observational capability, even under cloud cover or at night.One of the main microwave remote sensing approaches involves the use of synthetic aperture radar (SAR). The backscatter coefficient images derived from SAR can dis...

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Section: Discussionmentioning

confidence: 99%

Monitoring of an Indonesian Tropical Wetland by Machine Learning-Based Data Fusion of Passive and Active Microwave Sensors

et al. 2018

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“…We attribute the large increase in wetland detection to the use of a combination of high resolution multidate remote sensing ima- tease apart peatlands from seasonally drier, nonpeat accumulating wetlands or organic matter rich uplands, leading to an increase in accuracy. This agrees with SAR research conducted by others in mapping peatlands on flatter terrain (e.g., Bourgeau-Chavez et al, 2016;Grenier et al, 2007;Touzi, Deschamps, & Rother, 2007).…”

Section: Stocksmentioning

confidence: 99%

Multidate, multisensor remote sensing reveals high density of carbon‐rich mountain peatlands in the páramo of Ecuador

Hribljan

Suárez

Bourgeau-Chavez

et al. 2017

Global Change Biology

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Tropical peatlands store a significant portion of the global soil carbon (C) pool. However, tropical mountain peatlands contain extensive peat soils that have yet to be mapped or included in global C estimates. This lack of data hinders our ability to inform policy and apply sustainable management practices to these peatlands that are experiencing unprecedented high rates of land use and land cover change. Rapid large-scale mapping activities are urgently needed to quantify tropical wetland extent and rate of degradation. We tested a combination of multidate, multisensor radar and optical imagery (Landsat TM/PALSAR/RADARSAT-1/TPI image stack) for detecting peatlands in a 2715 km area in the high elevation mountains of the Ecuadorian páramo. The map was combined with an extensive soil coring data set to produce the first estimate of regional peatland soil C storage in the páramo. Our map displayed a high coverage of peatlands (614 km ) containing an estimated 128.2 ± 9.1 Tg of peatland belowground soil C within the mapping area. Scaling-up to the country level, páramo peatlands likely represent less than 1% of the total land area of Ecuador but could contain as much as ~23% of the above- and belowground vegetation C stocks in Ecuadorian forests. These mapping approaches provide an essential methodological improvement applicable to mountain peatlands across the globe, facilitating mapping efforts in support of effective policy and sustainable management, including national and global C accounting and C management efforts.

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“…Radar remote sensing, including synthetic aperture radar (SAR), has great potential to provide spatially-distributed information on permafrost ecosystem dynamics with its ability to penetrate cloud and independence from solar illumination. A number of studies using the space-borne radar measurements have been conducted to extract information regarding the freeze/thaw cycle [1][2][3][4][5][6][7], taiga forests [8][9][10][11][12][13][14], wetlands [15][16][17] and geological features [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…Kwok et al [11] demonstrated the usability of the co-and cross-polarization signature for characterizing changes in the relative scattering contributions in the radar signal between frozen and thawed conditions. Recently, several studies applied polarimetric processing techniques to characterize wetland classes in Canada [16] and to estimate the growing stock volume in Siberian forest [21,22].…”

Section: Introductionmentioning

confidence: 99%

Variations of Microwave Scattering Properties by Seasonal Freeze/Thaw Transition in the Permafrost Active Layer Observed by ALOS PALSAR Polarimetric Data

Park

2015

Remote Sensing

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Radar backscattering properties can be extremely sensitive to the freeze/thaw states of the ground surface. This study aims to evaluate the changes of L-band microwave scattering characteristics between thawed and frozen conditions by using polarimetric scattering mechanism indicators. ALOS PALSAR polarimetric mode data acquired in winter and spring seasons over Eastern Siberia are used in this study. Experimental results show that the actual scattering mechanisms and their seasonal variations over various forested and non-forested permafrost ecosystems can be successfully characterized by the polarimetric target decomposition parameters and the polarimetric coherences. In addition, fully polarimetric radar observations exhibit great potential for mapping land cover types and surficial features in the permafrost active layer. Particularly, the co-polarization coherences on the HV-polarization basis and circular-polarization basis were found to be very useful for discriminating different surficial geocryological characteristics in recently burnt forests and thermokarst regions.

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Wetland characterization using polarimetric RADARSAT-2 capability

Cited by 113 publications

References 25 publications

Monitoring of an Indonesian Tropical Wetland by Machine Learning-Based Data Fusion of Passive and Active Microwave Sensors

Monitoring of an Indonesian Tropical Wetland by Machine Learning-Based Data Fusion of Passive and Active Microwave Sensors

Multidate, multisensor remote sensing reveals high density of carbon‐rich mountain peatlands in the páramo of Ecuador

Variations of Microwave Scattering Properties by Seasonal Freeze/Thaw Transition in the Permafrost Active Layer Observed by ALOS PALSAR Polarimetric Data

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