Wetland Mapping with Synthetic Aperture Radar

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Imaging radars provide information that is fundamentally different from sensors that operate in the visible and infrared portions of the electromagnetic spectrum. Although the interpretation of radar imagery is not as fully developed as that of optical data, radar sensors have many advantages over more traditional optical sensors (Smith, 1997). For example, they can collect data regardless of solar illumination and cloud cover. Not being restricted by clouds is especially important when collecting data during the rainy season, when wetlands are often easier to discriminate. The Wetlands Subcommittee of the Federal Geographic Data Committee (1992) found that acquiring cloud-free imagery during the optimal time period was a key obstacle to mapping wetlands with satellite data. In many areas in the United States, this optimal period may only last two to three weeks. Radar sensors also have the potential to penetrate vegetative canopies to detect the character of the ground layer, soil moisture, and flooding beneath the canopy (Kasischke and Bourgeau-Chavez, 1997; Kasischke et al., 1997a; Kasischke et al., 1997b).

Sensitivity of radar to water, due to its high dielectric constant, is extremely valuable to the remote sensing of wetlands. Radar is not only sensitive to soil moisture. It can also differentiate between moist soil and standing water (Kasischke and Bourgeau-Chavez, 1997, Land et al. 2008). The presence of standing water interacts with the radar signal differently depending on the dominant vegetation type. When exposed to open water without vegetation, specular reflection occurs and a dark signal is observed (Dwivedi et al., 1999). The radar signal is often dampened in wetlands dominated by herbaceous vegetation when a layer of water is present (Kasischke et al., 1997a). Conversely, the radar signal is often increased in forested wetlands when standing water is present due to the double-bounce effect (Dwivedi et al., 1999). The double-bounce effect is more pronounced in forested wetlands when using L- band (24 cm) data but can also be seen when using C- band (5.6 cm) data (Ustin et al., 1991). This high sensitivity to standing water and soil moisture makes radar an efficient tool for determining hydropattern (Kasischke et al., 1997a; Rao et al., 1999). Radar can even detect the water content of plants and in this way plant health and senescence can be inferred.

Many of the first studies applying radar to wetlands and other ecosystems used Seasat imagery (Pope et al., 1997; Ramsey et al., 1998). This satellite was a synthetic aperture radar (SAR) satellite, which was launched in 1978, carried an L-HH band detector, and was intended for oceanographic mapping (Lillesand and Kiefer, 1994). It was also found, however, that this radar band was especially sensitive to flooding. All of the other radar sensors that are mentioned in this section will also be SAR systems. SAR technology allows the increased spatial resolution that is necessary in regional wetland mapping. Studies conducted with Shuttle Imaging Radar (SIR) -C and the Japanese Earth Resources Satellite (JERS) -1 L-HH band imagery have confirmed this finding (Hess et al., 1990; Hess et al., 1995; Townsend and Walsh, 1998). C-HH imagery like that acquired by RADARSAT, has a limited ability to map flooding beneath forest canopies (Wang et al., 1995). C-VV radar imagery, such as the imagery acquired by the European Remote Sensing Satellite (ERS), can be used to map flooding beneath forest canopies but only during leaf-off seasons (Kasischke and Bourgeau-Chavez, 1997; Sahagian and Melack, 1996).

Discrimination of several different types of marshes, swamp thickets, and swamp forests is also possible with radar imagery due to varying stem height and density (Pope et al., 1994). Others have found that the difference between C-HH band and C-VV band was highly sensitive to flooding. Although this combination of C- band HH and C- band VV is not currently available on one satellite, the combination of ERS1/2 and RADARSAT data could achieve this ratio (Pope et al., 1997). The combination of the L- band JERS-1 and C- band RADARSAT also has the potential to increase wetland mapping accuracy since these two bands are sensitive to varying structural details due to their different wavelengths (Sahagian and Melack, 1996).

Radar not only has potential to detect different types of wetlands; it can also be used to study the condition and function of these valuable areas. Recent advances in radar remote sensing data and processing have made the estimation of biomass and other forest parameters possible on a landscape scale (Le Toan, 1992; Kellndorfer, 1998; Kasischke, 1997b). Information concerning biomass in wetlands could be used to indicate the health and functioning of such areas. The ratio of cross-polarized (HV or VH) backscattering coefficients of L- to C- bands has been shown to be well correlated with biomass (Kasischke et al., 1997b). Total biomass can be accurately estimated using AIRSAR P- (68 cm), L-, and C- bands, an airborne synthetic aperture sensor (Mougin et al., 1999). AIRSAR's L- band with HH polarization was found to reveal drainage patterns in forested wetlands as a result of the double bounce effect (Wilen and Smith, 1996). C-HH band radar can be used to infer inundation patterns in low biomass sites (Morrissey et al., 1994; Kasischke and Bourgeau-Chavez, 1997; Kasischke, 1997a; Hess et al., 1995). Interferometric techniques can be used to create digital elevation models from radar imagery. These models can then be used to aid in the wetland mapping process.

Radar data holds potential for the mapping of wetlands but this potential has not been fully explored and the techniques needed too do so are not as well developed as those of optical data. The ability of radar to map flooding under forest canopies, where optical data would not be able to detect inundation, is particularly promising (Kasischke and Bourgeau-Chavez, 1997, Lang et al. 2008). Methods that use a combination of different bands and polarizations is optimal but synergistic approaches that use imagery from multiple radar instruments as well as optical data will also provide good results (Smith, 1997). The use of multi-temporal radar data combined via an intensity, hue, and saturation (IHS) transformation has also been found to improve wetland mapping (Kushwaha et al., 2000). Although microwave sensors can currently only be used to estimate soil moisture within the first 10 cm of soil, new models are being developed to help extend this estimate (Li et al., 1998). The opportunity to explore the potential of radar data will improve as many SAR satellites are currently or will soon be launched. These extra satellites will not only increase the amount of data available for analysis, they will also increase collection frequency, and the variety of polarizations and frequencies available (Ramsey, 1997).

References

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