Development of a Bi-National Great Lakes Coastal Wetland  and Land Use Map Using Three-Season PALSAR and  Landsat Imagery

Bourgeau-Chavez, L. L.; Endres, Sarah L.; Battaglia, Michael; Miller, Mary Ellen; Banda, Elizabeth; Laubach, Zachary M.; Higman, Phyllis; Chow-Fraser, Pat; Marcaccio, James V.

doi:10.3390/rs70708655

Cited by 85 publications

(86 citation statements)

References 35 publications

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“…Advanced techniques such as SAR-Optical fusion (Bourgeau-Chavez et al, 2015), Classification Tree Analysis (CTA), and Stochastic Gradient Boosting (SGB) (Baker et al, 2006) have shown success in mapping wetlands. However, mainly due to their seasonal variability, manual interpretation may be favoured for small areas using TC transformations (Fickas et al, 2016).…”

Section: Wetlandsmentioning

confidence: 99%

A Review of Free Optical Satellite Imagery for Watershed-Scale Landscape Analysis

Bevington

Gleason²,

Giroux-Bougard³

et al. 2018

JWSM

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Tyler de Jong is a researcher based in Whitehorse, Yukon with Global Water Futures at McMaster University. Email: tyler.dejong@mcmaster.caWatershed-scale landscape analysis includes many disciplines, including ecological, hydrological, and geographical sciences. e recent proliferation of free optical satellite imagery (FOSI) has changed the possibilities for the monitoring of environmental change at local and global scales. Many reviews exist for discipline-specific remote sensing applications; however, this article seeks to highlight the rapidly growing archive of FOSI and applied tools that can be used by all levels of users. Herein, ten techniques and eight applications of FOSI are reviewed, along with the specifications and limitations of various sources of FOSI. Although this review focuses on Western Canada, the democratization of FOSI is globally relevant, and the objective is to explain basic concepts via figures and reference materials to help summarize this rapidly changing field. KEYWORDS free optical satellite imagery; remote sensing; watershed science; environmental monitoring; open dataRemote sensing is the science of obtaining information about an object from a distance. is information can be collected from terrestrial, aquatic, aerial, or satellite platforms. Optical imaging sensors aboard these platforms record image data consisting of emitted or reflected electromagnetic energy. Since 2008, the availability of free optical satellite imagery (FOSI) has grown exponentially since the United States Geological Survey (USGS) first opened its image archives (Woodcock et al., 2008). As such, the Earth is currently being imaged many times per day at a variety of spatial resolutions (Malenovský et al., 2012;Roy et al., 2014). e availability of FOSI has enabled the development of free online visualization tools (see Appendix A), free open source remote sensing soware (see Appendix B), and free analysis-ready remote sensing products (see Appendix C). e abundance of FOSI has empowered natural resource managers, researchers, and others to increase, and ultimately improve, the monitoring and quantification of watershed-scale environmental change.Review articles have addressed vegetation mapping (Xie et al., 2008), land cover classification (Phiri & Morgenroth, 2017), forest inventories , and large area mapping techniques (Gómez et al., 2016; Hansen & Loveland, 2012 IntroductionAbstract of: 1) fundamental concepts; 2) common datasets; 3) data portals; 4) processing techniques; and 5) applied examples of watershed-scale remote sensing. e objective is to provide readers new to satellite remote sensing with a comprehensive reference guide explained in plain language, and to provide advanced users with a helpful compilation of reference materials.is section provides a synthesis of fundamental concepts in Earth observation (EO) remote sensing science, with a focus on passive optical sensors that measure and record energy emitted from external sources (typically the sun). Earth observation satellites have ne...

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Section: Wetlandsmentioning

confidence: 99%

A Review of Free Optical Satellite Imagery for Watershed-Scale Landscape Analysis

Bevington

Gleason²,

Giroux-Bougard³

et al. 2018

JWSM

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“…The U.S. Environmental Protection Agency (EPA) has a regulatory mission related to air and water quality and a long history of supporting large-area assessments of resource status, which includes the work described by Bourgeau-Chavez and colleagues [73]. Their efforts support a binational (U.S. and Canada) assessment of coastal wetlands within the basin surrounding the North American Great Lakes.…”

Section: Purpose Of This Special Issuementioning

confidence: 99%

The Challenges of Remote Monitoring of Wetlands

2015

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Wetlands are highly productive and support a wide variety of ecosystem goods and services. Various forms of global change impose compelling needs for timely and reliable information on the status of wetlands worldwide, but several characteristics of wetlands make them challenging to monitor remotely: they lack a single, unifying land-cover feature; they tend to be highly dynamic and their energy signatures are constantly changing; and steep environmental gradients in and around wetlands produce narrow ecotones that often are below the resolving capacity of remote sensors. These challenges and needs set the context for a special issue focused on wetland remote sensing. Contributed papers responded to one of three overarching questions aimed at improving remote, large-area monitoring of wetlands: (1) What approaches and data products are being developed specifically to support regional to global long-term monitoring of wetland landscapes? (2) What are the promising new technologies and sensor/multisensor approaches for more accurate and consistent detection of wetlands? (3) Are there studies that demonstrate how remote long-term monitoring of wetland landscapes can reveal changes that correspond with changes in land cover and land use and/or changes in climate?

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“…Alternatively, many studies have relied on microwave imagery to map flood levels [24][25][26][27]. Radar sensors have several advantages over optical and thermal ones that make them particularly applicable to monitoring hydrologic conditions of wetlands.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Monitoring of the Flooding Regime and Hydroperiod of Doñana Marshes with Landsat Time Series (1974–2014)

et al. 2016

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This paper presents a semi-automatic procedure to discriminate seasonally flooded areas in the shallow temporary marshes of Doñana National Park (SW Spain) by using a radiommetrically normalized long time series of Landsat MSS, TM, and ETM+ images . Extensive field campaigns for ground truth data retrieval were carried out simultaneous to Landsat overpasses. Ground truth was used as training and testing areas to check the performance of the method. Simple thresholds on TM and ETM band 5 (1.55-1.75 µm) worked significantly better than other empirical modeling techniques and supervised classification methods to delineate flooded areas at Doñana marshes. A classification tree was applied to band 5 reflectance values to classify flooded versus non-flooded pixels for every scene. Inter-scene cross-validation identified the most accurate threshold on band 5 reflectance ( < 0.186) to classify flooded areas (Kappa = 0.65). A joint TM-MSS acquisition was used to find the MSS band 4 (0.8 a 1.1 µm) threshold. The TM flooded area was identical to the results from MSS 4 band threshold < 0.10 despite spectral and spatial resolution differences. Band slicing was retrospectively applied to the complete time series of MSS and TM images. About 391 flood masks were used to reconstruct historical spatial and temporal patterns of Doñana marshes flooding, including hydroperiod. Hydroperiod historical trends were used as a baseline to understand Doñana's flooding regime, test hydrodynamic models, and give an assessment of relevant management and restoration decisions. The historical trends in the hydroperiod of Doñana marshes show two opposite spatial patterns. While the north-western part of the marsh is increasing its hydroperiod, the southwestern part shows a steady decline. Anomalies in each flooding cycle allowed us to assess recent management decisions and monitor their hydrological effects.

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Development of a Bi-National Great Lakes Coastal Wetland and Land Use Map Using Three-Season PALSAR and Landsat Imagery

Cited by 85 publications

References 35 publications

A Review of Free Optical Satellite Imagery for Watershed-Scale Landscape Analysis

A Review of Free Optical Satellite Imagery for Watershed-Scale Landscape Analysis

The Challenges of Remote Monitoring of Wetlands

Long-Term Monitoring of the Flooding Regime and Hydroperiod of Doñana Marshes with Landsat Time Series (1974–2014)

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