Study of the fronts of Johnsons and Hurd Glaciers (Livingston Island, Antarctica) from 1957 to 2013, with links to shapefiles

The study of glacier fronts combines different geomatics measurement techniques as the classic survey using total station or theodolite, technical GNSS (Global Navigation Satellite System), using laser-scanner or using photogrammetry (air or ground). The measure by direct methods (classical surveying and GNSS) is useful and fast when accessibility to the glaciers fronts is easy, while it is practically impossible to realize, in the case of glacier fronts that end up in the sea (tide water glaciers). In this paper, a methodology that combines photogrammetric methods and other techniques for lifting the front of the glacier Johnsons, inaccessible is studied. The images obtained from the front, come from a non-metric digital camera; its georeferencing to a global coordinate system is performed by measuring points GNSS support in accessible areas of the glacier front side and applying methods of direct intersection in inaccessible points of the front, taking measurements with theodolite. The result of observations obtained were applied to study the temporal evolution (1957-2014) of the position of the Johnsons glacier front and the position of the Argentina, Las Palmas and Sally Rocks lobes front (Hurd glacier).

Atmospheric, oceanic and hydrological polar motion excitation mechanisms based on a combination of geometric and gravimetric space observations

The goal of our study is to determine accurate time series of geophysical Earth rotation excitations to learn more about global dynamic processes in the Earth system. For this purpose, we developed an adjustment model which allows to combine precise observations from space geodetic observation systems, such as Satellite Laser Ranging (SLR), Global Navigation Satellite Systems (GNSS), Very Long Baseline Interferometry (VLBI), Doppler Orbit determination and Radiopositioning Integrated on Satellite (DORIS), satellite altimetry and satellite gravimetry in order to separate geophysical excitation mechanisms of Earth rotation. Three polar motion time series are applied to derive the polar motion excitation functions (integral effect). Furthermore we use five time variable gravity field solutions from Gravity Recovery and Climate Experiment (GRACE) to determine not only the integral mass effect but also the oceanic and hydrological mass effects by applying suitable filter techniques and a land-ocean mask. For comparison the integral mass effect is also derived from degree 2 potential coefficients that are estimated from SLR observations. The oceanic mass effect is also determined from sea level anomalies observed by satellite altimetry by reducing the steric sea level anomalies derived from temperature and salinity fields of the oceans. Due to the combination of all geodetic estimated excitations the weaknesses of the individual processing strategies can be reduced and the technique-specific strengths can be accounted for. The formal errors of the adjusted geodetic solutions are smaller than the RMS differences of the geophysical model solutions. The improved excitation time series can be used to improve the geophysical modeling.

Tab. 6+7: Altitudes and variations of altitudes in the area of the Filchner and Neumayer Stations

The determination of the strain and velocity behaviour of the ice surface near the two German Antarctic Stations on Filchner/Ronne and Ekström ice shelves was performed by the use of various geodetic measuring techniques. The relative positions and heights of control points valid for reference data were deduced from terrestrial observations (horizontal and vertical angle selectro optical distances). After a second sampling of data, these values served as the basis for the deformation analyses. Doppler-Satellite-observations (Navy Navigation Satellite System) made absolute positioning (latitude, longitude, height) of special points possible. These Doppler observations, supported by azimuth measurements (gyro-theodolite and sun observations) provided the datum of control networks (translations and orientation). After the repetition of these observations, the drift rates and azimuths of the control points as wenas the rotanon rates of the surface elements could be given. From vertical angles and horizontal distances differences in height end refraction coefficients were calculated. On days without clouds the refraction coefflcients increased by arnounts of up to 3.0 (in extreme cases up to 5.0). Distances over 1 km have to be subdivided to reach a standard deviation level of an heigh: difference better than 0.05 m. In order to determine the heterögeneity of refraction, some height differences should be measured with higher accuracy end-by subdivision of distances.

Seabed photographs taken along OFOS profiles during POLARSTERN cruise PS96 (ANT-XXXI/2 FROSN)

Within the context of the overall ecological working programme Dynamics of Antarctic Marine Shelf Ecosystems (DynAMo) of the PS96 (ANT-XXXI/2) cruise of RV "Polarstern" to the Weddell Sea (Dec 2015 to Feb 2016), seabed imaging surveys were carried out along drift profiles by means of the Ocean Floor Observation System (OFOS) of the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Bremerhaven. The setup and mode of deployment of the OFOS was similar to that described by Bergmann and Klages (2012, doi:10.1016/j.marpolbul.2012.09.018). OFOS is a surface-powered gear equipped with two downward-looking cameras installed side-by-side: one high-resolution, wide-angle still camera (CANON® EOS 5D Mark III; lens: Canon EF 24 f/1.4L II, f stop: 13, exposure time: 1/125 sec; in-air view angles: 74° (horizontal), 53° (vertical), 84° (diagonal); image size: 5760 x 3840 px = 21 MPix; front of pressure resistant camera housing consisting of plexiglass dome port) and one high-definition color video camera (SONY® FCB-H11). The system was vertically lowered over the stern of the ship with a broadband fibre-optic cable, until it hovers approximately 1.5 m above the seabed. It was then towed after the slowly sailing ship at a speed of approximately 0.5 kn (0.25 m/s). The ship's Global Acoustic Positioning System (GAPS), combining Ultra Short Base Line (USBL), Inertial Navigation System (INS) and satellite-based Global Positioning System (GPS) technologies, was used to gain highly precise underwater position data of the OFOS. During the profile, OFOS was kept hanging at the preferred height above the seafloor by means of the live video feed and occasional minor cable-length adjustments with the winch to compensate small-scale bathymetric variations in seabed morphology. Information on water depth and height above the seafloor were continuously recorded by means of OFOS-mounted sensors (GAPS transponder, Tritech altimeter). Three lasers, which are placed beside the still camera, emit parallel beams and project red light points, arranged as an equilateral triangle with a side length of 50 cm, in each photo, thus providing a scale that can be used to calculate the seabed area depicted in each image and/or measure the size of organisms or seabed features visible in the image. In addition, the seabed area depicted was estimated using altimeter-derived height above seafloor and optical characteristics of the OFOS still camera. In automatic mode, a seabed photo, depicting an area of approximately 3.45 m**2 (= 2.3 m x 1.5 m; with variations depending on the actual height above ground), was taken every 30 seconds to obtain series of "TIMER" stills distributed at regular distances along the profiles that vary in length depending on duration of the cast. At a ship speed of 0.5 kn, the average distance between seabed images was approximately 5 m. Additional "HOTKEY" photos were taken from interesting objects (organisms, seabed features, such as putative iceberg scours) when they appeared in the live video feed (which was also recorded, in addition to the stills, for documentation and possible later analysis). If any image from this collection is used, please cite the reference as given above.

Global distributions of picophytoplankton abundance and biomass - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The smallest marine phytoplankton, collectively termed picophytoplankton, have been routinely enumerated by flow cytometry since the late 1980s, during cruises throughout most of the world ocean. We compiled a database of 40,946 data points, with separate abundance entries for Prochlorococcus, Synechococcus and picoeukaryotes. We use average conversion factors for each of the three groups to convert the abundance data to carbon biomass. After gridding with 1° spacing, the database covers 2.4% of the ocean surface area, with the best data coverage in the North Atlantic, the South Pacific and North Indian basins. The average picophytoplankton biomass is 12 ± 22 µg C L-1 or 1.9 g C m-2. We estimate a total global picophytoplankton biomass, excluding N2-fixers, of 0.53 - 0.74 Pg C (17 - 39 % Prochlorococcus, 12 - 15 % Synechococcus and 49 - 69 % picoeukaryotes). Future efforts in this area of research should focus on reporting calibrated cell size, and collecting data in undersampled regions.

The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files

The CMCC Global Ocean Physical Reanalysis System (C-GLORS) is used to simulate the state of the ocean in the last decades. It consists of a variational data assimilation system (OceanVar), capable of assimilating all in-situ observations along with altimetry data, and a forecast step performed by the ocean model NEMO coupled with the LIM2 sea-ice model. KEY STRENGTHS: - Data are available for a large number of ocean parameters - An extensive validation has been conducted and is freely available - The reanalysis is performed at high resolution (1/4 degree) and spans the last 30 years KEY LIMITATIONS: - Quality may be discontinuos and depend on observation coverage - Uncertainty estimates are simply derived through verification skill scores

Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM)

Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.

Global distributions of picoheterothrophs (Bacteria and Archaea) abundance and biomass - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

We compiled a database of bacterial abundance of 39 766 data points. After gridding with 1° spacing, the database covers 1.3% of the ocean surface. There is data covering all ocean basins and depth except the Southern Hemisphere below 350 m or from April until June. The average bacterial biomass is 3.9 ± 3.6 µg l-1 with a 20-fold decrease between the surface and the deep sea. We estimate a total ocean inventory of about 1.3 - 1029 bacteria. Using an average of published open ocean measurements for the conversion from abundance to carbon biomass of 9.1 fg cell-1, we calculate a bacterial carbon inventory of about 1.2 Pg C. The main source of uncertainty in this inventory is the conversion factor from abundance to biomass.

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.