Coastal Zones 1

This work shows and discusses the  wind fields as evaluated from SAR, in-situ measurements and atmospheric model in the Gulf of Oristano,  western coast of the Sardinia (Western Mediterranean Sea), a small basin about 10 km by 18 km wide. The SAR derived wind fields have been obtained from the images of the COSMO-SkyMed, Radarsat-2 and Sentinel-1A satellites through a fully two-dimensional continuous wavelet method (2D-CWT),
the experimental wind field from a wind measuring system set along the gulf coast, and the  model winds
from the WRF model.
The results of the 2D-CWT are good for all satellites, as the directions extracted from the SAR images are very close to those measured.  However, the SAR derived wind fields appear different, both in strength and spatial layout, from the modeled and measured fields. The different wind speed strength, possibly due  to a still not consolidated  radar calibration, could be easily corrected taking the in-situ data as reference. But the SAR derived wind fields, exhibiting very detailed spatial variations, result different and hardly comparable with the spatially smoother modeled fields. The knowledge of the spatial variations of the wind fields can be very important for the oceanographic applications and constitutes the adjoint value brought by SAR in the description of the coastal wind fields. For  this reason  the SAR derived wind fields should be taken as reference in any kind of application.

While mangroves comprise less than 0.1% of the entire earth’s surface, and are among the most productive and biologically important ecoystems worldwide, providing essential ecosystem services to coastal communities and biological resources. They harbour twice as much biomass as tropical forest, while providing essential habitats for fish nurseries, protection against storms and food and livelihoods. According to the Millennium Ecosystem Assessment, the market value of seafood from mangroves has been estimated between at $7,500 and $167,500/km²/year. Even though they are very resilient, and able to grow in harsh salinity and other environments, there is a lot of evidence that they are generally decreasing worldwide. Mangroves are vastly unprotected (less than 7% occur in protected areas worldwide) and are threatened by conversion to aquaculture, development, and affected by changes in water balance due to dams, and chemical pollution. They nevertheless provide great opportunities for restoration activities and climate mitigation projects.

To support conservation activities in Mozambique, WWF Germany developed a semi-automated processing chain to map mangroves consistently over time, and assess both gains and losses in mangrove extent. Validation was provided by very high resolution satellite imagery and in situ data. Mangroves were found to be both increasing and decreasing singificantly, in different parts of the country. In the Zambezi delta, mangroves are expanding upstream, while in Angoche, mangroves were found to be decreasing along edges, evidence of human activities. WWF is expecting to expand this mapping effort worldwide in 14 priority places in South America, Africa and Asia.

The intertidal zone is generally characterized by shallow depth and limited access as a result of the tidal regime. Therefore, the intertidal morphology is generally poorly known with consequences in the hydrodynamic model efficiency related with the sediment transport and deposit. Remote sensing systems have been used for synoptically map and monitor the intertidal bottom topography. Among this systems SAR has the advantage over optical systems, of working without solar illumination and all weather conditions. The waterline method combined with the tide height is the most used method to generate the intertidal elevation model. The method can be used both with SAR and optical spaceborne systems. The method consists on the identification of the boundary between the water body and the exposed land mass. Knowing the waterline is a line of equal elevation, the bottom topography model is obtained by stacking several waterlines extracted in different tide conditions. The approach is dependent on the accuracy of the waterline extraction method that in turn is dependent on the weather and sea waves conditions at the image acquisition time, that are not comparable along the time frame. Instead, an approach based on the temporal analysis of the scattering proprieties of the land cover can be an added value to existing method.  In fact, numerous studies have demonstrated the dependence of radar backscatter on surface roughness and on the dielectric proprieties of the surface. In particular, microwave scattering models have been used to characterize SAR backscattering coefficient, sigma naught, as a function of the local characteristics of the soil moisture or moisture. In this work we present an approach based on the temporal analysis of the backscattering coefficient and its correlation with the tide height. As we are interested in the intertidal area we have focused on the low elevation areas and considered as a first step a three-class problem aimed at the discrimination of water, intertidal area and beach berm (dry sand) classes. The water class can be discriminated based on the low temporal variability of the backscattering coefficient as compared to the intertidal area. As expected, the beach berm class has also a low temporal variability of the backscattering coefficient. To discriminate between these two classes we used the average (in time) backscattering coefficient. In fact, beach berm shows very high backscatter values for most of the pixels. The average backscattering coefficient for the water and beach berm classes are the boundary limits (down and up limits) for the correlation function. The intertidal class can be discriminated based on the high temporal variability of the backscattering coefficient as compared to the other two classes. A threshold must be defined to discriminate low and high variability. Pixels belonging to the intertidal area are further analyzed in terms of the temporal behavior of the backscattering coefficient and used to estimate the bottom topography height. For that, a sigmoid function is adjusted to the backscattering coefficient values time series. The height of the pixel is estimated using the inflection point of the estimated sigmoid function. The proposed methodology has been applied to time-series of TERRASAR-X (X-band) and Sentinle-1A (C-band) images acquired over Tagus estuary (Lisbon region).

This study was funded by the Portuguese Science Foundation FCT, under the grant UID/GEO/50019/2013

Indonesian territorial waters cover about three million square kilometres, thereby being larger than the Mediterranean Sea, and are home to more than 3.000 species of fish and more than 500 species of corals. The Indonesian coastline is longer than 80.000 kilometres, and the Indonesian archipelago encompasses more than 17.000 islands. Major ship traffic routes, connecting the economic centres on the South China Sea (and beyond) with Europe, Africa, Australia, or the Persian Gulf, run through Indonesian waters.
The joint German-Indonesian Pilot Study IndoNACE (Indonesian seas Numerical Assessment of the Coastal Environment) aims at improving the information on the state of the Indonesian marine environment that is gained from satellite data. Synthetic aperture radar (SAR) data are used to produce oil pollution density maps of two dedicated regions of interest (ROIs) in Indonesian waters, namely the Western Java Sea and the Strait of Makassar.
Marine mineral oil spills show up on SAR imagery as dark patches, which however can be confused with other, atmospheric or oceanic, phenomena such as wind shadowing, biogenic slicks, etc.  Historical and actual SAR data from ESA’s ENVISAT archive and Sentinel 1A Rolling Archive, respectively, have been used for the generation of a pollution occurrence map that includes all detected oil pollution. All available SAR images of the two ROIs were visually inspected, and special emphasis was put on the discrimination between anthropogenic (mineral oil) spills and biogenic slicks, since both species tend to cause similar features on SAR imagery. The crude statistical chart was improved by including information on the SAR coverage and local weather conditions (basically the wind speed, which is the limiting factor for the visibility of oil pollution on SAR imagery). As a result a pollution density map of both ROIs was generated and is being kept up-to-date through the inclusion of actual SAR data.
In parallel, maps of particularly vulnerable coastal areas within both ROIs were produced, based upon United Nations Environmental Program (UNEP) -data and complemented by environmental data hosted by the Indonesian partner institute. An existing numerical model is being adapted and, in combination with a tracer dispersion model, high-resolution numerical forward and backward tracer experiments are being performed. Using the previously gained information sets on existing pollution and on sensitive coastal areas as input for the tracer experiments we demonstrate that our approach can be used to identify strongly affected coastal areas (with most oil pollution being driven onshore), but also sensitive parts of major ship traffic lanes (where any oil pollution is likely to be driven into Marine Protected Areas).

In the Middle ages, the North Frisian islands on the Germnan North Sea coast did not yet exist, but were still what was called the ‘Uthlande’ (outer lands) and what was part of, or connected with, the mainland. Vast areas along the coast were dominated by swamps, marshes, and swamp forests, which often made any settlements difficult or impossible. In the sparse settlements on the German North Sea coast houses were often built on dwelling mounds, protected by small dikes. Systems of drainage ditches were built to remove the water from the farmlands, thereby allowing for any kind of agriculture.

Two major storm surges changed the shape of the North Frisian coastline dramatically: on January 16, 1362, after more than 24 hours of severe westerly storm, an immense storm tide flooded the coast, causing the small dikes to break at many places, and eventually causing the death of a great number of cattle and men. As a result of that storm surge, which is also known as Saint Marcellus’ flood or ‘Grote Mandrenke’ (‘great drowning of men’), huge land areas were lost to the sea, and it took a long time until new dikes were built to protect the remaining marsh land. The new farmland was characterized by a dense system of ditches, the dikes enclosed larger polders than in the centuries before, and farmhouses on terps were connected by narrow lanes.

Another major storm surge occurred on October 11, 1634, again killing cattle and men, after the dikes had broken at many places. This second ‘Grote Mandrenke’ (also known as Burchardi flood) hit the area of North Frisia in an economically weak period, only a few decades after the plague had caused many deaths. The island of Strand, in the centre of the North Frisian coast, was cut into parts by the flood, and farmland, farms, and whole villages were destroyed. The Burchardi flood is still the most-known storm surge in history in the area of the North Frisian Wadden Sea.

Over the following centuries, great parts of this former agricultural area have been buried under muddy and sandy sediments, which nowadays form the German Wadden Sea. This area is being flooded, and falls dry, once during each tidal cycle, thereby making archaeological excavations very difficult. However, under the permanent action of the tidal forces the muddy and sandy marine sediments may be partly driven away, and traces of former peat digging, drainage systems, and settlements may appear again on the surface. Since those areas are difficult to reach, and thus to observe from ground, and since airborne surveillance is cost-intensive, high-resolution space borne sensors become an alternative source of data that can be used by archaeologists for their frequent surveillance of the area.

SAR signatures of both former settlements and remnants of former systems of ditches and of peat cutting, dating back to periods before the major storm surges in the 14^th and 17^th centuries, can be found on high-resolution Radarsat-2 and TerraSAR/TanDEM-X images. Here, strongest and clearest signatures were found on TerraSAR/TanDEM-X images acquired in the new ‘staring spotlight’ mode, with pixel sizes on the order of 0.1 m². In many cases, the observed signatures of former ditches are due to different sediment types, which in turn are due to the actual ditch morphology. Fossil roots and other organic material may result in denser and harder sediments, which may be directly sensed by the space borne SAR, or which may cause additional sedimentation that can be seen on SAR imagery. Different sediments may also cause different biological productivity, and they are therefore often marked by benthic organisms, which may cause different surface roughness patterns. It is those patterns that are sensed by the high-resolution SAR sensors. We demonstrate that Radarsat-2 and TerraSAR/TanDEM-X imagery are well suited for both qualitative and quantitative archaeological surveys, the former focussing on the origin of the observed signatures and the latter on their spatial extent.