High Spatial Resolution Remote Sensing for Salt Marsh Mapping and Change Analysis at Fire Island National Seashore

Salt marshes are changing due to natural and anthropogenic stressors such as sea level rise, nutrient enrichment, herbivory, storm surge, and coastal development. This study analyzes salt marsh change at Fire Island National Seashore (FIIS), a nationally protected area, using object-based image analysis (OBIA) to classify a combination of data from Worldview-2 and Worldview-3 satellites, topobathymetric Light Detection and Ranging (LiDAR), and National Agricultural Imagery Program (NAIP) aerial imageries acquired from 1994 to 2017. The salt marsh classification was trained and tested with vegetation plot data. In October 2012, Hurricane Sandy caused extensive overwash and breached a section of the island. This study quantified the continuing effects of the breach on the surrounding salt marsh. The tidal inundation at the time of image acquisition was analyzed using a topobathymetric LiDAR-derived Digital Elevation Model (DEM) to create a bathtub model at the target tidal stage. The study revealed geospatial distribution and rates of change within the salt marsh interior and the salt marsh edge. The Worldview-2/Worldview-3 imagery classification was able to classify the salt marsh environments accurately and achieved an overall accuracy of 92.75%. Following the breach caused by Hurricane Sandy, bayside salt marsh edge was found to be eroding more rapidly (F1, 1597 = 206.06, p \u3c 0.001). However, the interior panne/pool expansion rates were not affected by the breach. The salt marsh pannes and pools were more likely to revegetate if they had a hydrological connection to a mosquito ditch (χ2 = 28.049, p \u3c 0.001). The study confirmed that the NAIP data were adequate for determining rates of salt marsh change with high accuracy. The cost and revisit time of NAIP imagery creates an ideal open data source for high spatial resolution monitoring and change analysis of salt marsh environments

Remote Sensing of Georgia Tidal Marsh Habitats Using Aerial Photography and Planetscope Satellite Imagery

Globally, tidal marshes cover about 90,800 km. Within the state of Georgia tidal marshes are primarily located behind the barrier islands and total 1,619 km2. The combination of high salinity environments and daily inundation, and being dependent on river output, make these dynamic systems. Tidal marshes provide numerous ecosystem services such as carbon and nitrogen sequestration, flood control, coastal protection, and numerous biogeochemical processes. Due to their unique position, tidal marshes are under threat from sea level rise, drought, coastal development, and large-scale disturbance events. Tidal freshwater marshes are especially susceptible to these threats due to their geographic location and small extent which have been historically understudied. By mapping tidal marshes, species composition is better understood and can be used to scale up ecosystem services, biogeochemical processes, and above ground biomass using remote sensing imagery. This study uses aerial orthoimagery along with a digital elevation model, National Wetland Inventory, and vegetation indices to map salt, brackish, and tidal freshwater marshes along the entire coast of Georgia. Higher spectral and spatial resolution PlanetScope 4- and 8-band satellite imagery was also used to map salt, brackish, and tidal freshwater marshes of the three main watersheds in coastal Georgia which include the Ogeechee, Altamaha, and Satilla Rivers. The aerial orthoimagery classification had an accuracy of 86.3% with salt marshes making up 67.8%, brackish 28.7%, and tidal freshwater 3.5% of the classified image and showed the importance of using a DEM and NWI for tidal marsh mapping. The PlanetScope classifications were comparable to the aerial classification with an accuracy of 86.5% (Ogeechee), 88.1% (Altamaha), and 75.9% (Satilla). Differences between the 4-band and 8-band PlanetScope imagery proved to be minimal. Due to the vulnerability of salt marshes to climate change, this study aims to contribute and expand upon current remote sensing studies on tidal marsh mapping

Remote Sensing Applications in Monitoring of Protected Areas：A Bibliometric Analysis

The development of remote sensing platforms and sensors and improvement in science and technology provide crucial support for the monitoring and management of protected areas. This paper presents an analysis of research publications, from a bibliometric perspective, on the remote sensing of protected areas. This analysis is focused on the period from 1991 to 2018. For data, a total of 4546 academic publications were retrieved from the Web of Science database. The VOSviewer software was adopted to evaluate the co-authorships among countries and institutions, as well as the co-occurrences of author keywords. The results indicate an increasing trend of annual publications in the remote sensing of protected areas. This analysis reveals the major topical subjects, leading countries, and most influential institutions around the world that have conducted relevant research in scientific publications; this study also reveals the journals that include the most publications, and the collaborative patterns related to the remote sensing of protected areas. Landsat, MODIS, and LiDAR are among the most commonly used satellites and sensors. Research topics related to protected area monitoring are mainly concentrated on change detection, biodiversity conservation, and climate change impact. This analysis can help researchers and scholars better understand the intellectual structure of the field and identify the future research directions

Remote Sensing Applications in Monitoring of Protected Areas

Protected areas (PAs) have been established worldwide for achieving long-term goals in the conservation of nature with the associated ecosystem services and cultural values. Globally, 15% of the world’s terrestrial lands and inland waters, excluding Antarctica, are designated as PAs. About 4.12% of the global ocean and 10.2% of coastal and marine areas under national jurisdiction are set as marine protected areas (MPAs). Protected lands and waters serve as the fundamental building blocks of virtually all national and international conservation strategies, supported by governments and international institutions. Some of the PAs are the only places that contain undisturbed landscape, seascape and ecosystems on the planet Earth. With intensified impacts from climate and environmental change, PAs have become more important to serve as indicators of ecosystem status and functions. Earth’s remaining wilderness areas are becoming increasingly important buffers against changing conditions. The development of remote sensing platforms and sensors and the improvement in science and technology provide crucial support for the monitoring and management of PAs across the world. In this editorial paper, we reviewed research developments using state-of-the-art remote sensing technologies, discussed the challenges of remote sensing applications in the inventory, monitoring, management and governance of PAs and summarized the highlights of the articles published in this Special Issue

Identifying salt marsh shorelines from remotely sensed elevation data and imagery

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Farris, A. S., Defne, Z., & Ganju, N. K. Identifying salt marsh shorelines from remotely sensed elevation data and imagery. Remote Sensing, 11(15), (2019): 1795, doi: 10.3390/rs11151795.Salt marshes are valuable ecosystems that are vulnerable to lateral erosion, submergence, and internal disintegration due to sea level rise, storms, and sediment deficits. Because many salt marshes are losing area in response to these factors, it is important to monitor their lateral extent at high resolution over multiple timescales. In this study we describe two methods to calculate the location of the salt marsh shoreline. The marsh edge from elevation data (MEED) method uses remotely sensed elevation data to calculate an objective proxy for the shoreline of a salt marsh. This proxy is the abrupt change in elevation that usually characterizes the seaward edge of a salt marsh, designated the “marsh scarp.” It is detected as the maximum slope along a cross-shore transect between mean high water and mean tide level. The method was tested using lidar topobathymetric and photogrammetric elevation data from Massachusetts, USA. The other method to calculate the salt marsh shoreline is the marsh edge by image processing (MEIP) method which finds the unvegetated/vegetated line. This method applies image classification techniques to multispectral imagery and elevation datasets for edge detection. The method was tested using aerial imagery and coastal elevation data from the Plum Island Estuary in Massachusetts, USA. Both methods calculate a line that closely follows the edge of vegetation seen in imagery. The two methods were compared to each other using high resolution unmanned aircraft systems (UAS) data, and to a heads-up digitized shoreline. The root-mean-square deviation was 0.6 meters between the two methods, and less than 0.43 meters from the digitized shoreline. The MEIP method was also applied to a lower resolution dataset to investigate the effect of horizontal resolution on the results. Both methods provide an accurate, efficient, and objective way to track salt marsh shorelines with spatially intensive data over large spatial scales, which is necessary to evaluate geomorphic change and wetland vulnerability.This project was supported by the U.S. Geological Survey (USGS) Coastal/Marine Natural Hazards and Resources Program as well as the Massachusetts O ce of Coastal Zone Management under interagency agreement 16ENMALQ006000

National wetland mapping in China: a new product resulting from object-based and hierarchical classification of Landsat 8 OLI images

Spatially and thematically explicit information of wetlands is important to understanding ecosystem functions and services, as well as for establishment of management policy and implementation. However, accurate wetland mapping is limited due to lacking an operational classification system and an effective classification approach at a large scale. This study was aimed to map wetlands in China by developing a hybrid object-based and hierarchical classification approach (HOHC) and a new wetland classification system for remote sensing. Application of the hybrid approach and the wetland classification system to Landsat 8 Operational Land Imager data resulted in a wetland map of China with an overall classification accuracy of 95.1%. This national scale wetland map, so named CAS_Wetlands, reveals that China’s wetland area is estimated to be 451,084 ± 2014 km2, of which 70.5% is accounted by inland wetlands. Of the 14 sub-categories, inland marsh has the largest area (152,429 ± 373 km2), while coastal swamp has the smallest coverage (259 ± 15 km2). Geospatial variations in wetland areas at multiple scales indicate that China’s wetlands mostly present in Tibet, Qinghai, Inner Mongolia, Heilongjiang, and Xinjiang Provinces. This new map provides a new baseline data to establish multi-temporal and continuous datasets for China’s wetlands and biodiversity conservation

Salt Marsh Response to Dynamic Environmental Change:

Thesis advisor: Gail KinekeThesis advisor: Noah SnyderSalt marshes are some of the world’s richest ecosystems and provide a plethora of benefits to coastlines and bays in terms of storm protection and chemistry. To ensure salt marsh survival under increasing rates of sea level rise, management practices have been trending towards natural sustainability measures to increase marsh resilience. To benefit these efforts, it is necessary to understand how natural salt marshes respond to environmental change in terms of sediment deposition and evolution of vegetation and open water. This study uses aerial image digitization to understand how Nauset Marsh in Cape Cod MA, a protected salt marsh on Cape Cod National Seashore, has responded to sea level rise and half a century of inlet migration. Digitized images from 1974-2019 were used to track changes to vegetation extent and open water features during study periods of different inlet migration stages. Observed changes were used to ascertain trends of marsh loss or adaptation based on previous research on ponding cycles and vegetation extent. Results indicate that Nauset Marsh has been relatively stable over the last half century, with the most significant change observed in Vegetated Marsh loss of 6.71% ± 3.19 primarily due to edge erosion near the present-day inlet. Despite net feature stability, significant differences in feature evolution trends were observed during different stages of inlet migration. Most notably, inlet breaching and migration correlated with dynamic feature changes throughout the marsh, while the static inlet period correlated with expansion of open water features near the inlet location. The evolution of Nauset Marsh suggests that inlet migration improves marsh resilience through periodic increases in sediment deposition in a natural salt marsh with sufficient sediment supply.Thesis (MS) — Boston College, 2023.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Earth and Environmental Sciences

Satellite Observations and Spatiotemporal Assessment of Salt Marsh /Dieback Along Coastal South Carolina (1990-2019)

Coastal wetland mapping is often difficult because of the heterogeneous vegetation compositions and associated tidal effects. Past studies in the Gulf/Atlantic coast states have reported acute marsh dieback events in which marsh rapidly browned and thinned, leaving stubble of dead stems or mudflad with damaged ecosystem services. Reported marsh dieback in South Carolina (SC), USA, however, have been limited. Previous studies have suggested a suite of possibly abiotic and biotic attributes responsible for salt marsh dieback. However, there are no consensus answers in current literature explaining what led to marsh dieback in past decades, especially from the spatiotemporal perspective. In this study, the U-Net was employed, and an adaptive deep learning approach was developed to map statewide salt marshes in estuarine emergent wetlands of SC from 20 Sentinel-2A&B images. Then all marsh dieback events were identified in the North Inlet-Winyah Bay (NIWB) estuary, SC, from 1990 to 2019. With 30 annually collected Landsat images, the Normalized Difference Vegetation Index (NDVI) series was extracted. A Stacked Denoising Autoencoder neural network was developed to identify the NDVI anomalies on the trajectories. All marsh dieback patches were extracted, and their inter-annual changes were examined. Among these were the five most severe marsh dieback events (1991, 1999, 2000, 2002, and 2013). The spatiotemporal relationships between the dieback series and the associated environmental variables in an intertidal marsh in the estuary were investigated. Daily Evaporative Demand Drought Index (EDDI), daily precipitation data from Parameter Elevation Regressions on Independent Slopes Model (PRISM), and station-based water quality observations (dissolved oxygen, specific conductivity, salinity, turbidity, pH, and temperature) in the estuary were retrieved. This study cogitates the environmental influence on coastal marsh from a spatiotemporal perspective using a long-term satellite time series analysis. The findings could provide insights into marsh ecological resilience and facilitate coastal ecosystem management

WETLAND EROSION IN GALVESTON BAY BY OCEAN WAVES

Wave energy has been identified as a major cause of wetland edge erosion in general. This dissertation focuses on the numerical modeling of wind-wave and sediment transport affecting erosion and accretion of salt marsh edges and experimental investigations on the relationship between wave and salt marsh edge erosion. First, the physical aspect of cold front-induced waves on salt-marsh erosion was investigated. We modeled changes in water level and wave conditions during the passage of cold fronts on Galveston Island, Texas. We found that wind gusts and abrupt direction shifts produced high energy wave events, propagated toward the wetland edge during the simulation period. Field measurements agreed with the modeled predictions in terms of both tidal water level and significant wave heights. We also calculated the wave power during the entire measurement period and found that cold front-induced waves significantly increased the potential erosion of salt marsh edges. Second, a laboratory experiment investigated the resistance of the salt marsh to wave energy. Wave properties affecting salt marsh core samples were investigated. The wave power of the input waves was calculated based on spectrum analysis. Then the relationship between wave power and erosion rate was discussed based on dimensional analysis. As the input wave height increased, erosion generally increased, and more erosion was found in the portion of the samples where the wave breaking was frequent. Third, surveys using Unmanned Aerial Vehicle (UAV) were conducted to identify salt marsh boundary erosion and potential wind-wave vulnerability. Using UAV images and Global Navigation Satellite System receivers, the wetland areas located on the bay side of Galveston Bay were photographed over a year to observe the change in the boundary. Erosion rates have been calculated for several wetlands on Galveston Island. An average of 0.76 m of lateral erosion was recorded over the measurement period. Through the wave simulation during this period, the relationship between wave energy and erosion rate was derived. Lastly, sediment transport and processes along the wetland edge were investigated based on the large scale and detailed model. Sediment fluxes along the Galveston Bay entrance and West Bay area were quantified during the cold front passages. Erosion and accretion along the salt marsh boundary by tides, currents, and waves were investigated. In the relative sea level rise simulation model, it was found that the wetland edge region had the ability to adapt to a relatively high sea level, not lowering their platform level significantly