Seasonal Change in Wetland Coherence as an Aid to Wetland Monitoring

Water is an essential natural resource, and information about surface water conditions can support a wide variety of applications, including urban planning, agronomy, hydrology, electrical power generation, disaster relief, ecology and preservation of natural areas. Synthetic Aperture Radar (SAR) is recognized as an important source of data for monitoring surface water, especially under inclement weather conditions, and is used operationally for flood mapping applications. The canopy penetration capability of the microwaves also allows for mapping of flooded vegetation as a result of enhanced backscatter from what is generally believed to be a double-bounce scattering mechanism between the water and emergent vegetation. Recent investigations have shown that, under certain conditions, the SAR response signal from flooded vegetation may remain coherent during repeat satellite over-passes, which can be exploited for interferometric SAR (InSAR) measurements to estimate changes in water levels and water topography. InSAR results also suggest that coherence change detection (CCD) might be applied to wetland monitoring applications. This study examines wetland vegetation characteristics that lead to coherence in RADARSAT-2 InSAR data of an area in eastern Canada with many small wetlands, and determines the annual variation in the coherence of these wetlands using multi-temporal radar data. The results for a three-year period demonstrate that most swamps and marshes maintain coherence throughout the ice-/snow-free time period for the 24-day repeat cycle of RADARSAT-2. However, open water areas without emergent aquatic vegetation generally do not have suitable coherence for CCD or InSAR water level estimation. We have found that wetlands with tree cover exhibit the highest coherence and the least variance; wetlands with herbaceous cover exhibit high coherence, but also high variability of coherence; and wetlands with shrub cover exhibit high coherence, but variability intermediate between treed and herbaceous wetlands. From this knowledge, we have developed a novel image product that combines information about the magnitude of coherence and its variability with radar brightness (backscatter intensity). This product clearly displays the multitude of small wetlands over a wide area. With an interpretation key we have also developed, it is possible to distinguish different wetland types and assess year-to-year changes. In the next few years, satellite SAR systems, such as the European Sentinel and the Canadian RADARSAT Constellation Mission (RCM), will provide rapid revisit capabilities and standard data collection modes, enhancing the operational application of SAR data for assessing wetland conditions and monitoring water levels using InSAR techniques.

[1]  Lars M. H. Ulander,et al.  Repeat-pass SAR interferometry over forested terrain , 1995, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Claudio Prati,et al.  Improving slant-range resolution with multiple SAR surveys , 1993 .

[3]  Brian Brisco,et al.  Polarimetric Decompositions of Temperate Wetlands at C-Band , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4]  W. P. Waite,et al.  Use of Seasat satellite radar imagery for the detection of standing water beneath forest vegetation , 1981 .

[5]  Laurence C. Smith,et al.  Amazon floodplain water level changes measured with interferometric SIR-C radar , 2001, IEEE Trans. Geosci. Remote. Sens..

[6]  Brian Brisco,et al.  Evaluation of RADARSAT-2 Acquisition Modes for Wetland Monitoring Applications , 2015 .

[7]  Kevin B. Smith,et al.  Effects of seasonal hydrologic patterns in south Florida wetlands on radar backscatter measured from ERS-2 SAR imagery , 2003 .

[9]  Sang-Hoon Hong,et al.  Double-Bounce Component in Cross-Polarimetric SAR From a New Scattering Target Decomposition , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Joong-Sun Won,et al.  Interferometric Coherence Analysis of the Everglades Wetlands, South Florida , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Brian Brisco,et al.  Water resource applications with RADARSAT-2 – a preview , 2008, Int. J. Digit. Earth.

[12]  Philip A. Townsend,et al.  Relationships between forest structure and the detection of flood inundation in forested wetlands using C-band SAR , 2002 .

[13]  T. Dixon,et al.  Space-Based Detection of Wetlands' Surface Water Level Changes from L-Band SAR Interferometry , 2008 .

[14]  Robert Woodruff,et al.  Detecting seasonal flooding cycles in marshes of the Yucatan Peninsula with SIR-C polarimetric radar imagery , 1997 .

[15]  Urs Wegmüller,et al.  Retrieval of vegetation parameters with SAR interferometry , 1997, IEEE Trans. Geosci. Remote. Sens..

[16]  L. Hess,et al.  Radar detection of flooding beneath the forest canopy - A review , 1990 .

[17]  Zhong Lu,et al.  Radarsat-1 and ERS InSAR Analysis Over Southeastern Coastal Louisiana: Implications for Mapping Water-Level Changes Beneath Swamp Forests , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Zhong Lu,et al.  Multiple Baseline Radar Interferometry Applied to Coastal Land Cover Classification and Change Analyses , 2006 .

[19]  Zhong Lu,et al.  Integrated analysis of PALSAR/Radarsat-1 InSAR and ENVISAT altimeter data for mapping of absolute water level changes in Louisiana wetlands. , 2009 .

[20]  Jaan Praks,et al.  Interferometric SAR Coherence Models for Characterization of Hemiboreal Forests Using TanDEM-X Data , 2016, Remote. Sens..

[21]  D. Alsdorf,et al.  Repeat-pass multi-temporal interferometric SAR coherence variations with Amazon floodplain and lake habitats , 2010 .

[22]  Brian Brisco,et al.  A semi-automated tool for surface water mapping with RADARSAT-1 , 2009 .

[23]  Joong-Sun Won,et al.  Multi-temporal monitoring of wetland water levels in the Florida Everglades using interferometric synthetic aperture radar (InSAR) , 2010 .

[24]  Zhong Lu,et al.  Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter , 2014 .

[25]  Eric S. Kasischke,et al.  Monitoring South Florida Wetlands Using ERS-1 SAR Imagery , 1997 .