Salt Marsh Monitoring in Jamaica Bay, New York from 2003 to 2013: A Decade of Change from Restoration to Hurricane Sandy

Campbell, Andrew R.; Wang, Yeqiao; Christiano, Mark; Stevens, Sara

doi:10.3390/rs9020131

Cited by 39 publications

(29 citation statements)

References 42 publications

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“…To improve management outcomes, understanding vegetation trends at larger scales is critical, and remote sensing of aerial imagery provides a cost-effective means of monitoring tidal wetland sites where access may be challenging. In particular, object-based image analysis (OBIA) is a promising technique for monitoring tidal salt marshes (Dronova, 2015), and has been applied to looking at vegetation across spatial scales in these ecosystems Gorelick, 2013, 2016), but has only recently been used to explore change over time (Campbell et al, 2017). Previous geospatial work using aerial imagery has largely taken place in the North SF Bay, where freshwater river runoff buffers Bay salinity .…”

Section: Introductionmentioning

confidence: 99%

“…Often, pixel-based approaches are hampered by their inability to consider both the pixel identity and spatial context in classifying landscapes . To account for these issues, object-based approaches are increasingly used to categorize heterogeneous landscapes like tidal wetlands (Wang et al, 2004;Gorelick, 2013, 2016;Dronova, 2015;Campbell et al, 2017). In tidal wetland restoration projects, sediment is highly dynamic over time, imagery must be gathered at low tide for optimal visualization while surface water and debris can vary greatly between images Fulfrost et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Further, vegetation patches may be heterogeneous, leading to salt-and-pepper speckle artifacts that confuse delineation and interpretation of cover types (Moffett and Gorelick, 2013). By smoothing local noise and allowing for supervised classification for each year, OBIA can help address some of these issues (Dronova, 2015), but it has rarely been used for monitoring restoration outcomes (but see Campbell et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Vegetation Development in a Tidal Marsh Restoration Project during a Historic Drought: A Remote Sensing Approach

Chapple

Dronova

2017

Front. Mar. Sci.

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Tidal wetland restoration efforts can be challenging to monitor in the field due to unstable local conditions and poor site access. However, understanding how restored systems evolve over time is essential for future management of their ecological benefits, many of which are related to vegetation dynamics. Physical attributes, such as elevation and distance to channel play important roles in governing vegetation expansion in developing tidal wetlands. However, in Mediterranean ecosystems, drought years, wet years, and their resulting influence on salinity levels may also play a crucial role in determining the trajectory of restoration projects, but the influence of weather variability on restoration outcomes is not well-understood. Here, we use object-based image analysis (OBIA) and change analysis of high-resolution IKONOS and WorldView-2 satellite imagery to explore whether mean annual rates of change from mudflat to vegetation are lower during drought years with higher salinity (2011-2015) compared to years with lower salinity (2009-2011) at a developing restoration site in California's San Francisco Bay. We found that vegetation increased at a mean rate of 1,979 m 2 /year during California's historic drought, 10.4 times slower than the rate of 20,580 m 2 /year between 2009 and 2011 when the state was not in drought. Vegetation was significantly concentrated in areas closer to channel edges, where salinity stress is ameliorated, and the magnitude of the effect increased in the 2015 image. In our image analysis, we found that different distributions of water, mud, and algae between years led to different segmentation settings for each set of images, highlighting the need for more robust and reproducible OBIA strategies in complex wetlands. Our results demonstrate that adaptive monitoring efforts in variable climates should take into account the influence of weather on tidal wetland ecosystems, and that high-resolution remote sensing can be an effective means of assessing these dynamics.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Vegetation Development in a Tidal Marsh Restoration Project during a Historic Drought: A Remote Sensing Approach

Chapple

Dronova

2017

Front. Mar. Sci.

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“…Hyperspectral remote sensing provides promising approaches in the monitoring of global tidal wetlands [47][48][49]. High spatial resolution satellite data have been effectively applied in water and wetland mapping and change analysis [50][51][52][53][54]. Sentinel satellites have demonstrated enhanced capacities in the monitoring of changing water and wetland environments, in recent years [55][56][57][58][59][60].…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing of Floodpath Lakes and Wetlands: A Challenging Frontier in the Monitoring of Changing Environments

Wang

2018

Remote Sensing

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Monitoring of changing lake and wetland environments has long been among the primary focus of scientific investigation, technology innovation, management practice, and decision-making analysis. Floodpath lakes and wetlands are the lakes and associated wetlands affected by seasonal variations of water level and water surface area. Floodpath lakes and wetlands are, in particular, sensitive to natural and anthropogenic impacts, such as climate change, human-induced intervention on hydrological regimes, and land use and land cover change. Rapid developments of remote sensing science and technologies, provide immense opportunities and capacities to improve our understanding of the changing lake and wetland environments. This special issue on Remote Sensing of Floodpath Lakes and Wetlands comprise featured articles reporting the latest innovative research and reflects the advancement in remote sensing applications on the theme topic. In this editorial paper, we review research developments using state-of-the-art remote sensing technologies for monitoring dynamics of floodpath lakes and wetlands; discuss challenges of remote sensing in inventory, monitoring, management, and governance of floodpath lakes and wetlands; and summarize the highlights of the articles published in this special issue.

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“…For wetland process studies, polar orbiting optical and synthetic aperture radar (SAR) satellites with spatial resolutions of 5-250 meters have generally represented a compromise in terms of spatial resolution and temporal resolution (revisit time), which are both important for monitoring wetland dynamics. Satellite imagery with spatial resolutions finer than five meters is more suited to characterizing wetland spatial variability and producing detailed wetland maps [19][20][21]. However, many of the satellites acquiring this high spatial resolution imagery are commercial, requiring users to purchase imagery and at times also requiring tasking of the satellites for image acquisition over a given study site.…”

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confidence: 99%

Evaluation of Approaches for Mapping Tidal Wetlands of the Chesapeake and Delaware Bays

2019

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The spatial extent and vegetation characteristics of tidal wetlands and their change are among the biggest unknowns and largest sources of uncertainty in modeling ecosystem processes and services at the land-ocean interface. Using a combination of moderate-high spatial resolution (≤30 meters) optical and synthetic aperture radar (SAR) satellite imagery, we evaluated several approaches for mapping and characterization of wetlands of the Chesapeake and Delaware Bays. Sentinel-1A, Phased Array type L-band Synthetic Aperture Radar (PALSAR), PALSAR-2, Sentinel-2A, and Landsat 8 imagery were used to map wetlands, with an emphasis on mapping tidal marshes, inundation extents, and functional vegetation classes (persistent vs. non-persistent). We performed initial characterizations at three target wetlands study sites with distinct geomorphologies, hydrologic characteristics, and vegetation communities. We used findings from these target wetlands study sites to inform the selection of timeseries satellite imagery for a regional scale random forest-based classification of wetlands in the Chesapeake and Delaware Bays. Acquisition of satellite imagery, raster manipulations, and timeseries analyses were performed using Google Earth Engine. Random forest classifications were performed using the R programming language. In our regional scale classification, estuarine emergent wetlands were mapped with a producer’s accuracy greater than 88% and a user’s accuracy greater than 83%. Within target wetland sites, functional classes of vegetation were mapped with over 90% user’s and producer’s accuracy for all classes, and greater than 95% accuracy overall. The use of multitemporal SAR and multitemporal optical imagery discussed here provides a straightforward yet powerful approach for accurately mapping tidal freshwater wetlands through identification of non-persistent vegetation, as well as for mapping estuarine emergent wetlands, with direct applications to the improved management of coastal wetlands.

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Salt Marsh Monitoring in Jamaica Bay, New York from 2003 to 2013: A Decade of Change from Restoration to Hurricane Sandy

Cited by 39 publications

References 42 publications

Vegetation Development in a Tidal Marsh Restoration Project during a Historic Drought: A Remote Sensing Approach

Vegetation Development in a Tidal Marsh Restoration Project during a Historic Drought: A Remote Sensing Approach

Remote Sensing of Floodpath Lakes and Wetlands: A Challenging Frontier in the Monitoring of Changing Environments

Evaluation of Approaches for Mapping Tidal Wetlands of the Chesapeake and Delaware Bays

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