Airborne remote sensing of estuarine intertidal radionuclide concentrations

The ability to map industrial discharges through remote sensing provides a powerful tool in environmental monitoring. Radionuclide effluents have been discharged, under authorization, into the Irish Sea from BNFL (British Nuclear Fuels Plc.) sites at Sellafield and Springfields since 1952. The quantitative mapping of this anthropogenic radioactivity in estuarine intertidal zones is crucial for absolute interpretations of radionuclide transport. The spatial resolutions of traditional approaches e.g. point sampling and airborne gamma surveys are insufficient to support geomorphic interpretations of the fate of radionuclides in estuaries. The research presented in this thesis develops the use of airborne remote sensing to derive high-resolution synoptic data on the distribution of anthropogenic radionuclides in the intertidal areas of the Ribble Estuary, Lancashire, UK. From multidate surface sediment samples a significant relationship was identified between the Sellafieldderived 137Cs & 241Am and clay content (r2=0.93 & 0.84 respectively). Detailed in situ, and laboratory, reflectance (0.4-2.5mn) experiments demonstrated that significant relationships exist between Airborne Thematic Mapper (ATM) simulated reflectance and intertidal sediment grain-size. The spectral influence of moisture on the reflectance characteristics of the intertidal area is also evident. This had substantial implications for the timing of airborne image acquisition. Low-tide Daedalus ATM imagery (Natural Environmental Research Council) was collected of the Ribble Estuary on May 30th 1997. Preprocessing and linear unmixing of the imagery allowed accurate sub-pixel determinations of sediment clay content distributions (r2=0.8 1). Subsequently, the established relationships between 137Cs & 241Am and sediment grain-size enabled the radionuclide activity distributions across the entire intertidal area (92km2) to be mapped at a geomorphic scale (1.75m). The accuracy of these maps was assessed by comparison with in situ samples and the results of previous radiological studies within the estuary. Finally, detailed conclusions are made regarding radionuclide sinks and sources, and surface activity redistribution within the Ribble Estuary environment

Morphological Development of the German Wadden Sea from 1996 to 2009 Determined with the Waterline Method and SAR and Landsat Satellite Images

The Dutch, German, and Danish Wadden Sea contains some of the largest undisturbed tidal flats in the world of about 10,000 km2. The research areas covered in this thesis are the North Frisian, Neuwerk, and Cuxhaven regions of the German Wadden Sea. The goal of the thesis is to use the waterline method with SAR and optical images to derive topographic maps in order to analyze the morphological development of this valuable ecological system on large spatial and engineering time scales (90 km and 14 years). Compared to earlier applications, the method is improved with respect to the geocoding step and the data coverage of the complete tidal range. The results also allow analyzing smaller scale s developmental details, such as sandbars and estuaries. Topographical maps from 1996 to 1999, and 2004 to 2009 were generated. The largest morphological differences occurred between 2009 and 1996, also observed in the -2 m isobaths map. The Bed Elevation Range of the tidal flats includes all the elevation information from 1996 to 2009 in order to identify the maximum changes during the investigation period. It shows high morphodynamic regions are outer parts of the tidal flat, sandbars, and estuaries. Vertical nodal linear regression gives the direction of the morphological development (erosion or sedimentation). Our result shows that the rate of change is mostly between -0.1 to 0.1 m/yr. Extreme erosion rate reaches over -0.3 m/yr, while extreme sedimentation rate is up to 0.36 m/yr. The absolute amount of elevation change called turnover height has a growth rate of 8.2 mm/yr, indicating the growing morphodynamic activity over the investigation period. The net balance height of the whole investigation region shows an increasing trend of 6.8 mm/yr, demonstrating an overall sedimentation. According to large-scale analyses, the most dynamic areas are the sandbars. Tertiussand, D-Steert, Gelbsand, and Medemgrund/Medemsand are given detailed discussion in this thesis. The west side of the sandbars except for Medemgrund/Medemsand face the high wave and tidal energy arriving from the open North sea, and cause large erosion towards east, while Medemgrund/Medemsand located in the Elbe estuary show migration in the opposite direction. The three cross sections of Tertiussand, Gelbsand and Medemgrund all show clearly increasing elevation if comparing the average elevation over the years 1996-1999 and 2004-2009. Since the areas of Tertiussand and Gelbsand decreased, their increased elevation might relate to internal sediment redistribution. Medemgrund increasead in area, so its increased elevation could be compensated by the adjacent tidal flat Medemsand which has significant erosion towards the north and the sediment brought from Elbe River

Sediment type unsupervised classification of the Molenplaat, Westerschelde estuary, The Netherlands

Sediment stability or erosion resistance of intertidal zones depend on sediment physical characteristics and on biological factors. Obtaining accurate data on the basic biological, chemical and physical processes in sediments is expensive and difficult. Remote sensing methods can produce detailed information on ecological functioning in a cost-effective manner. A hyperspectral image of the Molenplaat, an intertidal flat in the Westerschelde estuary, the Netherlands, was acquired with the HyMap sensor in June 2004. The goal of this research is to perform, analyse and evaluate unsupervised classification methods for sediment types on the imagery. The unsupervised methods are based on Principal Component Analysis (PCA) or Iterative Self-Organizing Data Analysis Technique (ISODATA), and consist of three steps: (a) classification into spectrally distinct clusters, (b) post-clustering treatment, and (c) assignment of labels to the clusters. The result consists of 13 clusters after the post-clustering treatment, and of 8 or 9 classes after labelling for either the PCA or ISODATA method. A supervised Spectral Angle Mapper (SAM) classification was performed using field data to evaluate the unsupervised classification results. The labelling of the unsupervised clusters was also partly based on the SAM results, due to limited field data.The comparison of the results reveals that 69% and 73% of the pixels of PCA and ISODATA classification respectively were identically labelled in the supervised classification. Moreover, the mismatches were mainly found in two classes, while the other classes showed high similarities, indicating the plausibility of using unsupervised classification methods for intertidal sediment types. Additional strengths of the unsupervised classification methods are (a) the distinction of classes that were not visited during field work and not classified in the supervised classification, (b) the identification of spectrally distinct areas that should be characterised during field campaigns, and (c) the user-friendliness thanks to limited required field knowledge and short calculation time

Multiple stable states and catastrophic shifts in coastal wetlands: Progress, challenges, and opportunities in validating theory using remote sensing and other methods

open5siThe analysis by K.B. Moffett was partially supported by National Science Foundation grant EAR-1013843 to Stanford University. Any opinions, findings, and onclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The analysis by W. Nardin was partially supported by Office of Naval Research Award N00014-14-1-0114 to Boston University. The analysis by C. Wang was partially supported by National Natural Science Funds of China (41376120 and 41401413). The analysis by C. Wang and S. Temmerman was also partially supported by the European Union Programme Erasmus Mundus External Cooperation Window (EMECW)-Lot 14-China. K.B. Moffett thanks B.C. Smith for the analysis for the Wax Lake Delta example of Section 4.2 and S.M. Gorelick for the funding leading to the San Francisco Bay example of Section 4.3. W. Nardin thanks S. Fagherazzi and C. Woodcock for the funding leading to the Mekong River Delta example of Section 4.1. S. Silvestri thanks M. Marani for inspiring ideas and research on coastal wetland processes.Multiple stable states are established in coastal tidal wetlands (marshes, mangroves, deltas, seagrasses) by ecological, hydrological, and geomorphological feedbacks. Catastrophic shifts between states can be induced by gradual environmental change or by disturbance events. These feedbacks and outcomes are key to the sustainability and resilience of vegetated coastlines, especially as modulated by human activity, sea level rise, and climate change. Whereas multiple stable state theory has been invoked to model salt marsh responses to sediment supply and sea level change, there has been comparatively little empirical verification of the theory for salt marshes or other coastal wetlands. Especially lacking is long-term evidence documenting if or how stable states are established and maintained at ecosystem scales. Laboratory and field-plot studies are informative, but of necessarily limited spatial and temporal scope. For the purposes of long-term, coastal-scale monitoring, remote sensing is the best viable option. This review summarizes the above topics and highlights the emerging promise and challenges of using remote sensing-based analyses to validate coastal wetland dynamic state theories. This significant opportunity is further framed by a proposed list of scientific advances needed to more thoroughly develop the field.openMoffett K.B.; Nardin W.; Silvestri S.; Wang C.; Temmerman S.Moffett K.B.; Nardin W.; Silvestri S.; Wang C.; Temmerman S

Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment

The transition zone between land and water is difficult to map with conventional geophysical systems due to shallow water depth and often challenging environmental conditions. The emerging technology of airborne topobathymetric light detection and ranging (lidar) is capable of providing both topographic and bathymetric elevation information, using only a single green laser, resulting in a seamless coverage of the land–water transition zone. However, there is no transparent and reproducible method for processing green topobathymetric lidar data into a digital elevation model (DEM). The general processing steps involve data filtering, water surface detection and refraction correction. Specifically, the procedure of water surface detection and modelling, solely using green laser lidar data, has not previously been described in detail for tidal environments. The aim of this study was to fill this gap of knowledge by developing a step-by-step procedure for making a digital water surface model (DWSM) using the green laser lidar data. The detailed description of the processing procedure augments its reliability, makes it user-friendly and repeatable. A DEM was obtained from the processed topobathymetric lidar data collected in spring 2014 from the Knudedyb tidal inlet system in the Danish Wadden Sea. The vertical accuracy of the lidar data is determined to ±8 cm at a 95 % confidence level, and the horizontal accuracy is determined as the mean error to ±10 cm. The lidar technique is found capable of detecting features with a size of less than 1 m². The derived high-resolution DEM was applied for detection and classification of geomorphometric and morphological features within the natural environment of the study area. Initially, the bathymetric position index (BPI) and the slope of the DEM were used to make a continuous classification of the geomorphometry. Subsequently, stage (or elevation in relation to tidal range) and a combination of statistical neighbourhood analyses (moving average and standard deviation) with varying window sizes, combined with the DEM slope, were used to classify the study area into six specific types of morphological features (i.e. subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar and beach dune). The developed classification method is adapted and applied to a specific case, but it can also be implemented in other cases and environments

Spatio-temporal analysis of coastal sediment erosion in Cape Town through remote sensing and geoinformation science

Coastal erosion can be described as the landward or seaward propagation of coastlines. Coastal processes occur over various space and time scales, limiting in-situ approaches of monitoring change. As such it is imperative to take advantage of multisensory, multi-scale and multi-temporal modern spatial technologies for multi-dimensional coastline change monitoring. The research presented here intends to showcase the synergy amongst remote sensing techniques by showcasing the use of coastal indicators towards shoreline assessment over the Kommetjie and Milnerton areas along the Cape Town coastline. There has been little progress in coastal studies in the Western Cape that encompass the diverse and dynamic aspects of coastal environments and in particular, sediment movement. Cape Town, in particular; is socioeconomically diverse and spatially segregated, with heavy dependence on its 240km of coastline. It faces sea level rise intensified by real-estate development close to the high-water mark and on reclaimed land. Spectral indices and classification techniques are explored to accommodate the complex bio-optical properties of coastal zones. This allows for the segmentation of land and ocean components to extract shorelines from multispectral Landsat imagery for a long term (1991-2021) shoreline assessment. The DSAS tool used these extracted shorelines to quantify shoreline change and was able to determine an overall averaged erosional rate of 2.56m/yr. for Kommetjie and 2.35m/yr. for Milnerton. Beach elevation modelling was also included to evaluate short term (2016-2021) sediment volumetric changes by applying Differential Interferometry to Sentinel-1 SLC data and the Waterline method through a combination of Sentinel -1 GRD and tide gauge data. The accuracy, validation and correction of these elevation models was conducted at the pixel level by comparison to an in-field RTK GPS survey used to capture the current state of the beaches. The results depict a sediment deficit in Kommetjie whilst accretion is prevalent along the Milnerton coastline. Shoreline propagation and coastal erosion quantification leads to a better understanding of geomorphology, hydrodynamic and land use influences on coastlines. This further informs climate adaptation strategies, urban planning and can support further development of interactive coastal information systems

Relationship between Land Use and Water Quality and its Assessment Using Hyperspectral Remote Sensing in Mid- Atlantic Estuaries

Mid-Atlantic coastal waters are under increasing pressures from anthropogenic disturbances at various temporal and spatial scales exacerbated by the climate change. According to the National Oceanic Atmospheric Association (NOAA), 10 of the 22 estuaries in the Mid-Atlantic, including the Chesapeake Bay, exhibit high levels of eutrophic conditions while seven, including Delaware Bay, exhibit low conditions. Chesapeake Bay is the largest estuarine system in the United States and undergoes frequent eutrophication and low dissolved oxygen events. Although substantially lower in nutrients compared to other Mid-Atlantic Estuaries, the biological, chemical, and ecological status of the Delaware Bay has changed in the past few decades due to high coastal tourism, increased local resident populations, and agricultural activities which have increased nutrient inputs into this shallow coastal bay. As stated by the Academy of Natural Sciences, although the nutrient load has reduced since the Clean Water Act, years of nutrient accumulation, contaminations, and sedimentation have impacted estuarine systems substantially, long-term monitoring is lacking, and ecological responses are not well quantified. Eutrophication within the Bays has degraded water quality conditions advanced by sedimentation. Understanding the quality of the water in any aquatic ecosystem is a critical first step in order to identify characteristics of that ecosystem and draw conclusions about how well adapted the system is in terms of anthropogenic activity and climate change. Determining water quality in intertidal creeks along the Chesapeake and Delaware coastlines is important because land cover is constantly changing. Many of these tidal creeks are lined with forested riparian buffers that may be intercepting nutrients from running off into the waterways. Identifying water conditions, coupled with the marsh land cover, provides a strong foundation to see if the buffer systems are providing the ecosystem services they are designed to provide. Our primary goal in this chapter is to provide research findings on the application of the hyperspectral remote sensing to monitor specific land-use activities and water quality. Along with hyperspectral remote sensing, our monitoring was coupled with the integration of remotely sensed data, global positioning system (GPS), and geographic information system (GIS) technologies that provide a valuable tool for monitoring and assessing waterways in the Mid-Atlantic Estuaries

A multisource approach for coastline mapping and identification of shoreline changes

Coastal dynamics are driven by phenomena of exogenous and endogenous nature. Characterizing factors that influence their equilibrium and continuous monitoring are fundamental for effective environmental planning and management of coastal areas. In order to monitor shoreline changes, we developed a methodology based on a multisource and multitemporal approach. A database, related to the Ionian coast of Basilicata region (about 50 km), was implemented by using cartographic data (IGMI data), satellite imagery (SPOT-PX/XS, Landsat-TM, Corona) and aerial data covering the period form 1949 to 2001. In particular, airborne data (1 m spatial resolution) were acquired during a specific campaign we performed in 2000 and 2001. To obtain the best performance from the available data, we applied a data fusion procedure on visible and thermal information. Different algorithms were tested, such as band ratios and clustering for extracting the coastline. The best results from multispectral data were obtained using a threshold algorithm we devised by exploiting the green, red and NIR bands, whereas for panchromatic data we selected clustering as the more suitable method. Moreover, a GPS survey was performed to evaluate the influence of tidal effects