The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Potential of RapidEye image data for sediment monitoring of the German tidal flats

The Wadden Sea is located in the southeastern part of the North Sea forming an extended intertidal area along the Dutch, German and Danish coast. It is a highly dynamic and largely natural ecosystem influenced by climatic changes and anthropogenic use of the North Sea. Changes in the environment of the Wadden Sea, natural or anthropogenic origin, cannot be monitored by the standard measurement methods alone, because large-area surveys of the intertidal flats are often difficult due to tides, tidal channels and unstable underground. For this reason, remote sensing offers effective monitoring tools. In this study a multi-sensor concept for classification of intertidal areas in the Wadden Sea has been developed. Basis for this method is a combined analysis of RapidEye (RE) and TerraSAR-X (TSX) satellite data coupled with ancillary vector data about the distribution of vegetation, mussel beds and sediments. The classification of the vegetation and mussel beds is based on a decision tree and a set of hierarchically structured algorithms which use object and texture features. The sediments are classified by an algorithm which uses thresholds and a majority filter. Further improvements focus on radiometric enhancement and atmospheric correction. First results show that we are able to identify vegetation and mussel beds with the use of multi-sensor remote sensing. The classification of the sediments in the tidal flats is a challenge compared to vegetation and mussel beds. The results demonstrate that the sediments cannot be classified with high accuracy by their spectral properties alone due to their similarity which is predominately caused by their water content.

Satellite image map of King George Island, Antarctica

A new topographic database for King George Island, one of the most visited areas in Antarctica, is presented. Data from differential GPS surveys, gained during the summers 1997/98 and 1999/2000, were combined with up to date coastlines from a SPOT satellite image mosaic, and topographic information from maps as well as from the Antarctic Digital Database. A digital terrain model (DTM) was generated using ARC/INFO GIS. From contour lines derived from the DTM and the satellite image mosaic a satellite image map was assembled. Extensive information on data accuracy, the database as well as on the criteria applied to select place names is given in the multilingual map. A lack of accurate topographic information in the eastern part of the island was identified. It was concluded that additional topographic surveying or radar interferometry should be conducted to improve the data quality in this area. In three case studies, the potential applications of the improved topographic database are demonstrated. The first two examples comprise the verification of glacier velocities and the study of glacier retreat from the various input data-sets as well as the use of the DTM for climatological modelling. The last case study focuses on the use of the new digital database as a basic GIS (Geographic Information System) layer for environmental monitoring and management on King George Island.

The Global Plankton Database: an inventory and data from the Former Soviet Union expeditions

At present time, there is a lack of knowledge on the interannual climate-related variability of zooplankton communities of the tropical Atlantic, central Mediterranean Sea, Caspian Sea, and Aral Sea, due to the absence of appropriate databases. In the mid latitudes, the North Atlantic Oscillation (NAO) is the dominant mode of atmospheric fluctuations over eastern North America, the northern Atlantic Ocean and Europe. Therefore, one of the issues that need to be addressed through data synthesis is the evaluation of interannual patterns in species abundance and species diversity over these regions in regard to the NAO. The database has been used to investigate the ecological role of the NAO in interannual variations of mesozooplankton abundance and biomass along the zonal array of the NAO influence. Basic approach to the proposed research involved: (1) development of co-operation between experts and data holders in Ukraine, Russia, Kazakhstan, Azerbaijan, UK, and USA to rescue and compile the oceanographic data sets and release them on CD-ROM, (2) organization and compilation of a database based on FSU cruises to the above regions, (3) analysis of the basin-scale interannual variability of the zooplankton species abundance, biomass, and species diversity.

Probability sampling protocol of classification maps from spaceborne/airborne image

To deliver sample estimates provided with the necessary probability foundation to permit generalization from the sample data subset to the whole target population being sampled, probability sampling strategies are required to satisfy three necessary not sufficient conditions: (i) All inclusion probabilities be greater than zero in the target population to be sampled. If some sampling units have an inclusion probability of zero, then a map accuracy assessment does not represent the entire target region depicted in the map to be assessed. (ii) The inclusion probabilities must be: (a) knowable for nonsampled units and (b) known for those units selected in the sample: since the inclusion probability determines the weight attached to each sampling unit in the accuracy estimation formulas, if the inclusion probabilities are unknown, so are the estimation weights. This original work presents a novel (to the best of these authors' knowledge, the first) probability sampling protocol for quality assessment and comparison of thematic maps generated from spaceborne/airborne Very High Resolution (VHR) images, where: (I) an original Categorical Variable Pair Similarity Index (CVPSI, proposed in two different formulations) is estimated as a fuzzy degree of match between a reference and a test semantic vocabulary, which may not coincide, and (II) both symbolic pixel-based thematic quality indicators (TQIs) and sub-symbolic object-based spatial quality indicators (SQIs) are estimated with a degree of uncertainty in measurement in compliance with the well-known Quality Assurance Framework for Earth Observation (QA4EO) guidelines. Like a decision-tree, any protocol (guidelines for best practice) comprises a set of rules, equivalent to structural knowledge, and an order of presentation of the rule set, known as procedural knowledge. The combination of these two levels of knowledge makes an original protocol worth more than the sum of its parts. The several degrees of novelty of the proposed probability sampling protocol are highlighted in this paper, at the levels of understanding of both structural and procedural knowledge, in comparison with related multi-disciplinary works selected from the existing literature. In the experimental session the proposed protocol is tested for accuracy validation of preliminary classification maps automatically generated by the Satellite Image Automatic MapperT (SIAMT) software product from two WorldView-2 images and one QuickBird-2 image provided by DigitalGlobe for testing purposes. In these experiments, collected TQIs and SQIs are statistically valid, statistically significant, consistent across maps and in agreement with theoretical expectations, visual (qualitative) evidence and quantitative quality indexes of operativeness (OQIs) claimed for SIAMT by related papers. As a subsidiary conclusion, the statistically consistent and statistically significant accuracy validation of the SIAMT pre-classification maps proposed in this contribution, together with OQIs claimed for SIAMT by related works, make the operational (automatic, accurate, near real-time, robust, scalable) SIAMT software product eligible for opening up new inter-disciplinary research and market opportunities in accordance with the visionary goal of the Global Earth Observation System of Systems (GEOSS) initiative and the QA4EO international guidelines.

Database of Ice-Rich Yedoma Permafrost (IRYP)

Vast portions of Arctic and sub-Arctic Siberia, Alaska and the Yukon Territory are covered by ice-rich silty to sandy deposits that are containing large ice wedges, resulting from syngenetic sedimentation and freezing. Accompanied by wedge-ice growth in polygonal landscapes, the sedimentation process was driven by cold continental climatic and environmental conditions in unglaciated regions during the late Pleistocene, inducing the accumulation of the unique Yedoma deposits up to >50 meters thick. Because of fast incorporation of organic material into syngenetic permafrost during its formation, Yedoma deposits include well-preserved organic matter. Ice-rich deposits like Yedoma are especially prone to degradation triggered by climate changes or human activity. When Yedoma deposits degrade, large amounts of sequestered organic carbon as well as other nutrients are released and become part of active biogeochemical cycling. This could be of global significance for future climate warming as increased permafrost thaw is likely to lead to a positive feedback through enhanced greenhouse gas fluxes. Therefore, a detailed assessment of the current Yedoma deposit coverage and its volume is of importance to estimate its potential response to future climate changes. We synthesized the map of the coverage and thickness estimation, which will provide critical data needed for further research. In particular, this preliminary Yedoma map is a great step forward to understand the spatial heterogeneity of Yedoma deposits and its regional coverage. There will be further applications in the context of reconstructing paleo-environmental dynamics and past ecosystems like the mammoth-steppe-tundra, or ground ice distribution including future thermokarst vulnerability. Moreover, the map will be a crucial improvement of the data basis needed to refine the present-day Yedoma permafrost organic carbon inventory, which is assumed to be between 83±12 (Strauss et al., 2013, doi:10.1002/2013GL058088) and 129±30 (Walter Anthony et al., 2014, doi:10.1038/nature13560) gigatonnes (Gt) of organic carbon in perennially-frozen archives. Hence, here we synthesize data on the circum-Arctic and sub-Arctic distribution and thickness of Yedoma for compiling a preliminary circum-polar Yedoma map. For compiling this map, we used (1) maps of the previous Yedoma coverage estimates, (2) included the digitized areas from Grosse et al. (2013) as well as extracted areas of potential Yedoma distribution from additional surface geological and Quaternary geological maps (1.: 1:500,000: Q-51-V,G; P-51-A,B; P-52-A,B; Q-52-V,G; P-52-V,G; Q-51-A,B; R-51-V,G; R-52-V,G; R-52-A,B; 2.: 1:1,000,000: P-50-51; P-52-53; P-58-59; Q-42-43; Q-44-45; Q-50-51; Q-52-53; Q-54-55; Q-56-57; Q-58-59; Q-60-1; R-(40)-42; R-43-(45); R-(45)-47; R-48-(50); R-51; R-53-(55); R-(55)-57; R-58-(60); S-44-46; S-47-49; S-50-52; S-53-55; 3.: 1:2,500,000: Quaternary map of the territory of Russian Federation, 4.: Alaska Permafrost Map). The digitalization was done using GIS techniques (ArcGIS) and vectorization of raster Images (Adobe Photoshop and Illustrator). Data on Yedoma thickness are obtained from boreholes and exposures reported in the scientific literature. The map and database are still preliminary and will have to undergo a technical and scientific vetting and review process. In their current form, we included a range of attributes for Yedoma area polygons based on lithological and stratigraphical information from the original source maps as well as a confidence level for our classification of an area as Yedoma (3 stages: confirmed, likely, or uncertain). In its current version, our database includes more than 365 boreholes and exposures and more than 2000 digitized Yedoma areas. We expect that the database will continue to grow. In this preliminary stage, we estimate the Northern Hemisphere Yedoma deposit area to cover approximately 625,000 km². We estimate that 53% of the total Yedoma area today is located in the tundra zone, 47% in the taiga zone. Separated from west to east, 29% of the Yedoma area is found in North America and 71 % in North Asia. The latter include 9% in West Siberia, 11% in Central Siberia, 44% in East Siberia and 7% in Far East Russia. Adding the recent maximum Yedoma region (including all Yedoma uplands, thermokarst lakes and basins, and river valleys) of 1.4 million km² (Strauss et al., 2013, doi:10.1002/2013GL058088) and postulating that Yedoma occupied up to 80% of the adjacent formerly exposed and now flooded Beringia shelves (1.9 million km², down to 125 m below modern sea level, between 105°E - 128°W and >68°N), we assume that the Last Glacial Maximum Yedoma region likely covered more than 3 million km² of Beringia. Acknowledgements: This project is part of the Action Group "The Yedoma Region: A Synthesis of Circum-Arctic Distribution and Thickness" (funded by the International Permafrost Association (IPA) to J. Strauss) and is embedded into the Permafrost Carbon Network (working group Yedoma Carbon Stocks). We acknowledge the support by the European Research Council (Starting Grant #338335), the German Federal Ministry of Education and Research (Grant 01DM12011 and "CarboPerm" (03G0836A)), the Initiative and Networking Fund of the Helmholtz Association (#ERC-0013) and the German Federal Environment Agency (UBA, project UFOPLAN FKZ 3712 41 106).

Compilation of results of the STRATAGEM project as ISO-image of the final CD-ROM

The study of the Neogene (Miocene to Holocene) stratigraphic record on the glaciated Atlantic margin of NW Europe has, to date, largely been undertaken on an ad-hoc basis. Whereas a systematic approach to understanding the stratigraphic development of Palaeogene and older strata has been undertaken in areas such as the North Sea, West of Shetland and Norway, the problem of establishing a Neogene framework has been only partly addressed by academia and the oil industry. In most cases where a Neogene stratigraphy has been constructed, this has been largely in response to problem solving and risk assessment in a restricted area. Nevertheless, in the past few years it has become increasingly apparent that there is a common history in the Neogene development of the passive Atlantic margin of NW Europe, between mid-Norway and SW Ireland. The inspection and interpretation of an extensive geophysical and geological database has identified several regionally significant and correlatable unconformities along this continental margin. Thus, a regional approach to the stratigraphical development of the Neogene succession on the glaciated European Atlantic margin is undertaken in this volume.

A BRDF-BPDF database for the analysis of Earth targets reflectances

A database of representative BRDF and BPDF derived from the POLDER measurements. From the huge amount of data acquired by the spaceborne instrument over a period of 7 years, we selected a set of targets with high quality observations. The selection aimed at a large number of observations, free of cloud or aerosol contamination, acquired in diverse observation geometry with a focus on the backscatter direction that shows the specific Hot-Spot signature. The targets are sorted according to the 16-classes IGBP land cover classification system and the target selection aims at a spatial representativeness within the class. The database thus provides a set of high quality BRDF and BPDF samples that can be used to assess the typical variability of natural surface reflectances or to evaluate models.