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Remote Sens. 2017, 9(2), 158; doi:10.3390/rs9020158

Seasonal Change in Wetland Coherence as an Aid to Wetland Monitoring

1
Canada Centre for Mapping and Earth Observation, 560 Rochester St., Ottawa, ON K1A 0E4, Canada
2
TerreVista Earth Imaging, 441 Cormac Road, Cormac, ON K0J 1M0, Canada
3
Environment Canada, 1125 Colonel by Drive, Ottawa, ON K1A 0H3, Canada
4
Lancaster Geographics, 187 Mulberry Lane, Lake Clear, RR 2, Eganville, ON K0J 1T0, Canada
*
Author to whom correspondence should be addressed.
Academic Editors: Qiusheng Wu, Charles Lane, Melanie Vanderhoof, Chunqiao Song, Deepak R. Mishra and Prasad S. Thenkabail
Received: 29 November 2016 / Revised: 22 January 2017 / Accepted: 9 February 2017 / Published: 15 February 2017
(This article belongs to the Special Issue Remote Sensing of Climate Change and Water Resources)
View Full-Text   |   Download PDF [12125 KB, uploaded 15 February 2017]   |  

Abstract

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. View Full-Text
Keywords: SAR; InSAR; coherence; hydrology; flooded vegetation; change detection SAR; InSAR; coherence; hydrology; flooded vegetation; change detection
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Brisco, B.; Ahern, F.; Murnaghan, K.; White, L.; Canisus, F.; Lancaster, P. Seasonal Change in Wetland Coherence as an Aid to Wetland Monitoring. Remote Sens. 2017, 9, 158.

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