Remote Sensing for Wetland Mapping and Historical Change Detection at the Nisqually River Delta

Ballanti, L.; Byrd, Kristin B.; Woo, Isa; Ellings, Christopher S.

doi:10.3390/su9111919

Cited by 47 publications

(41 citation statements)

References 47 publications

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“…Coastal and near-shore marine ecosystems are facing unprecedented pressures from land use modification. Many studies have analysed change dynamics in wetland ecosystems due to the utilisation of remote sensing techniques [4][5][6] resulting from a combination of two factors: (1) greater open access to longer time series of image archives and their derived products and (2) more easily accessed tools for using remote sensing data and their products to monitor change from local to global scales. The Landsat (SLATS), which uses satellite imagery to monitor woody vegetation clearing in native vegetation including mangroves and estuarine regions [33], but no studies have focused on using remote sensing to map biome variability and change dynamics in Great Barrier Reef catchments on a landscape scale.…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing of Mangroves and Estuarine Communities in Central Queensland, Australia

2020

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Great Barrier Reef catchments are under pressure from the effects of climate change, landscape modifications, and hydrology alterations. With the use of remote sensing datasets covering large areas, conventional methods of change detection can expose broad transitions, whereas workflows that excerpt data for time-series trends divulge more subtle transformations of land cover modification. Here, we combine both these approaches to investigate change and trends in a large estuarine region of Central Queensland, Australia, that encompasses a national park and is adjacent to the Great Barrier Reef World Heritage site. Nine information classes were compiled in a maximum likelihood post classification change analysis in 2004–2017. Mangroves decreased (1146 hectares), as was the case with estuarine wetland (1495 hectares), and saltmarsh grass (1546 hectares). The overall classification accuracies and Kappa coefficient for 2004, 2006, 2009, 2013, 2015, and 2017 land cover maps were 85%, 88%, 88%, 89%, 81%, and 92%, respectively. The cumulative area of open forest, estuarine wetland, and saltmarsh grass (1628 hectares) was converted to pasture in a thematic change analysis showing the “from–to” change. We generated linear regression relationships to examine trends in pixel values across the time series. Our findings from a trend analysis showed a decreasing trend (p value range = 0.001–0.099) in the vegetation extent of open forest, fringing mangroves, estuarine wetlands, saltmarsh grass, and grazing areas, but this was inconsistent across the study site. Similar to reports from tropical regions elsewhere, saltmarsh grass is poorly represented in the national park. A severe tropical cyclone preceding the capture of the 2017 Landsat 8 Operational Land Imager (OLI) image was likely the main driver for reduced areas of shoreline and stream vegetation. Our research contributes to the body of knowledge on coastal ecosystem dynamics to enable planning to achieve more effective conservation outcomes.

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Section: Introductionmentioning

confidence: 99%

Remote Sensing of Mangroves and Estuarine Communities in Central Queensland, Australia

2020

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“…A paper by Ballanti et al [103] used an object-oriented approach that performs hierarchical classification using commercial software (eCognition Developer) to identify changes within the watershed and wetland ecosystems. Data for the Nisqually River Delta between 1957 and 2015 were used for case studies.…”

Section: Supervisedmentioning

confidence: 99%

Methods and Challenges Using Multispectral and Hyperspectral Images for Practical Change Detection Applications

Kwan

2019

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Multispectral (MS) and hyperspectral (HS) images have been successfully and widely used in remote sensing applications such as target detection, change detection, and anomaly detection. In this paper, we aim at reviewing recent change detection papers and raising some challenges and opportunities in the field from a practitioner’s viewpoint using MS and HS images. For example, can we perform change detection using synthetic hyperspectral images? Can we use temporally-fused images to perform change detection? Some of these areas are ongoing and will require more research attention in the coming years. Moreover, in order to understand the context of our paper, some recent and representative algorithms in change detection using MS and HS images are included, and their advantages and disadvantages will be highlighted.

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“…For this reason, we chose to study marsh formation processes in the Nisqually River Delta (NRD) near Olympia, Washington, United States. The NRD is a model site for addressing this data gap because it is one of the largest wetland restoration projects to date in the Pacific Northwest and has ample data on site characteristics (David et al ; Ellings et al ; Woo et al ) and land use change (Ballanti et al ). For this study, we concentrated on a 308 ha parcel of marsh that was restored in the Billy Frank Jr. Nisqually National Wildlife Refuge (NISQ) in November 2009 (unit 3, Fig.…”

Section: Introductionmentioning

confidence: 99%

Carbon accumulation and vertical accretion in a restored versus historic salt marsh in southern Puget Sound, Washington, United States

Drexler

Woo

Fuller

et al. 2019

Restoration Ecology

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Few comparisons exist between vertical accretion (VA) and carbon accumulation rates (CARs) in restored versus historic (i.e. reference) marshes. Here, we compare these processes in a formerly diked, sparsely vegetated, restored salt marsh (Six Gill Slough, SG), whose surface is subsided relative to the tidal frame, to an adjacent, relatively pristine, historic salt marsh (Animal Slough, AS). Six sediment cores were collected at both AS and SG approximately 6 years after restoration. Cores were analyzed for bulk density (BD), % loss of ignition, % organic carbon, and 210Pb. We found that sharp changes in BD in surface layers of SG cores were highly reliable markers for the onset of restoration. The mean VA since restoration at SG (0.79 [SD = 0.29] cm/year) was approximately twice that of AS (0.41 [SD = 0.16] cm/year). In comparison, the VA at AS over 50 years was 0.30 (SD = 0.09) cm/year. VA consisted almost entirely of inorganic sediment at SG whereas at AS it was approximately 55%. Mean CARs at SG were somewhat greater than at AS, but the difference was not significant due to high variability (SG: 81–210 g C m−2 year−1; AS: 115–168 g C m−2 year−1). The mean CAR at AS over the past 50 years was 118 (SD = 23) g C m−2 year−1. This study demonstrates that a sparsely vegetated, restored salt marsh can quickly begin to accumulate carbon and that historic and restored marshes can have similar CARs despite highly divergent formation processes.

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Remote Sensing for Wetland Mapping and Historical Change Detection at the Nisqually River Delta

Cited by 47 publications

References 47 publications

Remote Sensing of Mangroves and Estuarine Communities in Central Queensland, Australia

Remote Sensing of Mangroves and Estuarine Communities in Central Queensland, Australia

Methods and Challenges Using Multispectral and Hyperspectral Images for Practical Change Detection Applications

Carbon accumulation and vertical accretion in a restored versus historic salt marsh in southern Puget Sound, Washington, United States

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