(Table 1) Magnetozone boundaries, age and sedimentation rate at DSDP Hole 93-605

Natural Remanent Magnetization (NRM) was measured for regularly spaced samples from the 620-m-thick, lower middle Eocene to upper Maestrichtian section of DSDP Site 605. The total NRM of the Eocene chalks was too low (5-50 µA/m) to establish a reliable magnetic polarity stratigraphy. However, the results from the somewhat more clayrich Paleocene-upper Maestrichtian section are useful. A fourfold quality classification of the results of progressive demagnetization studies aided in determining the polarity of the original remanence. Two types (1 and 2a) showed a Characteristic Remanent Magnetization (ChRM) direction with reversed and normal polarity, respectively; the third type (2b) can be interpreted as having a reversed ChRM, which could not be cleaned, whereas the fourth type (3) is considered to be unreliable. The Site 605 magnetic polarity stratigraphy compares well with published sections, adding important detail to the correlation with planktonic microfossil zones and, hence, to the resolution of this portion of the time scale (C24-C32 on the Berggren et al., 1985, scale). The Cretaceous/Tertiary boundary occurs in a reversed polarity zone that has been correlated with Subchron C29r. We suspect the presence of an unconformity at the boundary between lithostratigraphic Units Va and IV a location which is also the level of Reflection Horizon A*.

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.

BSRN Toolbox V2.0 - a tool to create quality checked output files from BSRN datasets and station-to-archive files

The BSRN Toolbox is a software package supplied by the WRMC and is freely available to all station scientists and data users. The main features of the package include a download manager for Station- to-Archive files, a tool to convert files into human readable TAB-separated ASCII-tables (similar to those output by the PANGAEA database), and a tool to check data sets for violations of the "BSRN Global Network recommended QC tests, V2.0" quality criteria. The latter tool creates quality codes, one per measured value, indicating if the data are "physically possible," "extremely rare," or if "intercomparison limits are exceeded." In addition, auxiliary data such as solar zenith angle or global calculated from diffuse and direct can be output. All output from the QC tool can be visualized using PanPlot (doi:10.1594/PANGAEA.816201).

Air photography Samoylov Island

For the qualitative description of surface properties like vegetation cover or land-water-ratio of Samoylov Island as well as for the evaluation of fetch homogeneity considerations of the eddy covariance measurements and for the up-scaling of chamber flux measurements, a detailed surface classification of the island at the sub-polygonal scale is necessary. However, up to know only grey-scale Corona satellite images from the 1960s with a resolution of 2 x 2 m and recent multi-spectral LandSat images with a resolution of 30 x 30 m were available for this region. Both are not useable for the desired classification because of missing spectral information and inadequate resolution, respectively. During the Lena 2003 expedition, a survey of the island by air photography was carried out in order to obtain images for surface classification. The photographs were taken from a helicopter on 10.07.2002, using a Canon EOS100 reflex camera, a Soligor 19-23 mm lens and colour slide film. The height from which the photographs were taken was approximately 600 meters. Due to limited flight time, not all the area of the island could be photographed and some regions could only be photographed with a slanted view. As a result, the images are of a varying quality and resolution. In Potsdam, after processing the films were scanned using a Nikon LS-2000 scanner at maximal resolution setting. This resulted in a ground resolution of the scanned images of approximately 0.3x0.3 m. The images were subsequently geo-referenced using the ENVI software and a referenced Corona image dating from 18.07.1964 (Spott, 2003). Geo-referencing was only possible for the Holocene river terrace areas; the floodplain regions in the western part of the island could not be referenced due to the lack of ground reference points. In Figure 3.7-1, the aerial view of Samoylov Island composed of the geo-referenced images is shown. Further work is necessary for the classification and interpretation of the images. If possible, air photography surveys will be carried out during future expeditions in order to determine changes in surface pattern and composition.