Pigment data set from the SeaWiFS Bio-optical Archive and Storage System (1961-1996)

The oceans play a critical role in the Earth's climate, but unfortunately, the extent of this role is only partially understood. One major obstacle is the difficulty associated with making high-quality, globally distributed observations, a feat that is nearly impossible using only ships and other ocean-based platforms. The data collected by satellite-borne ocean color instruments, however, provide environmental scientists a synoptic look at the productivity and variability of the Earth's oceans and atmosphere, respectively, on high-resolution temporal and spatial scales. Three such instruments, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) onboard ORBIMAGE's OrbView-2 satellite, and two Moderate Resolution Imaging Spectroradiometers (MODIS) onboard the National Aeronautic and Space Administration's (NASA) Terra and Aqua satellites, have been in continuous operation since September 1997, February 2000, and June 2002, respectively. To facilitate the assembly of a suitably accurate data set for climate research, members of the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project and SeaWiFS Project Offices devote significant attention to the calibration and validation of these and other ocean color instruments. This article briefly presents results from the SIMBIOS and SeaWiFS Project Office's (SSPO) satellite ocean color validation activities and describes the SeaWiFS Bio-optical Archive and Storage System (SeaBASS), a state-of-the-art system for archiving, cataloging, and distributing the in situ data used in these activities.

Geophysical mapping of the sediment architecture in the Orkhon Valley, Mongolia

Ground penetrating radar (GPR) and capacitive coupled resistivity (CCR) measurements were conducted in order to image subsurface structures in the Orkhon Valley, Central Mongolia. The data are extended by information from drill cores to the entire transects distinguishing different sedimentary environments in the valley. The Orkhon Valley is part of the high sensitive Steppe region in Central Mongolia, one of the most important cultural landscapes in Central Asia. There, archaeological, geoarchaeological and sedimentological research aims to reconstruct the landscape evolution and the interaction between man and environment during the last millennia since the first settlement. In May 2009 and 2010 geophysical surveys have been conducted including transects with lengths between 1.5 and 30 km crossing the entire valley and a kilometre-scaled grid in the southern part of the investigation area. The geoelectrical and GPR data revealed the existence of two layers characterized by different resistivity values and radar reflectors. The two layers do not only represent material contrasts, but also reflect the influence of sporadic permafrost which occurs in several areas of Mongolia. The results help to reconstruct the evolution of the braided Orkhon River and therefore give important hints to understand the environmental history of the Orkhon Valley.

Grain-size distribution, sedimentation rate and x-ray fluorescence data of four sediment cores off the Senegal River estuary

Fine-grained sediment depocenters on continental shelves are of increased scientific interest since they record environmental changes sensitively. A north-south elongated mud depocenter extends along the Senegalese coast in mid-shelf position. Shallow-acoustic profiling was carried out to determine extent, geometry and internal structures of this sedimentary body. In addition, four sediment cores were retrieved with the main aim to identify how paleoclimatic signals and coastal changes have controlled the formation of this mud depocenter. A general paleoclimatic pattern in terms of fluvial input appears to be recorded in this depositional archive. Intervals characterized by high terrigenous input, high sedimentation rates and fine grain sizes occur roughly contemporaneously in all cores and are interpreted as corresponding to intensified river discharge related to more humid conditions in the hinterland. From 2750 to 1900 and from 1000 to 700 cal a BP, wetter conditions are recorded off Senegal, an observation which is in accordance with other records from NW-Africa. Nevertheless, the three employed proxies (sedimentation rate, grain size and elemental distribution) do not always display consistent inter-core patterns. Major differences between the individual core records are attributed to sediment remobilization which was linked to local hydrographic variations as well as reorganizations of the coastal system. The Senegal mud belt is a layered inhomogeneous sedimentary body deposited on an irregular erosive surface. Early Holocene deceleration in the rate of the sea-level rise could have enabled initial mud deposition on the shelf. These favorable conditions for mud deposition occur coevally with a humid period over NW-Africa, thus, high river discharge. Sedimentation started preferentially in the northern areas of the mud belt. During mid-Holocene, a marine incursion led to the formation of an embayment. Afterwards, sedimentation in the north was interrupted in association with a remarkable southward shift in the location of the active depocenter as it is reflected by the sedimentary architecture and confirmed by radiocarbon dates. These sub-recent shifts in depocenters location are caused by migrations of the Senegal River mouth. During late Holocene times, the weakening of river discharge allowed the longshore currents to build up a chain of beach barriers which have forced the river mouth to shift southwards.

Gridded bathymetry from multibeam echosounder HS-DS2 data of the cruise M52/1 (2002)

Bathymetry based on data recorded during M52-1 between 02.01.2002 and 01.02.2002 in the Black Sea. The cruise was focused on studying the distribution, structure and architecture of gas hydrate deposits in the Black Sea as well as their relationship to fluid migration pathways. While high-resolution geoacoustic investigation tools covering a whole range of frequencies and techniques render detailed images of near-surface gas hydrates and associated fluid migration pathways.

Airborne hyperspectral image data of Heron Reef, Australia

This airborne hyperspectral (19 bands) image data of Heron Reef, Great Barrier Reef, Australia is derived from Compact Airborne Spectrographic Imager (CASI) data acquired on 1st and 3rd of July 2002, latitude -23.45, longitude 151.92. Processing and correction to at-surface data was completed by Karen Joyce (Joyce, 2004). Raw imagery consisted several images corresponding to the number of flight paths taken to cover the entire Heron Reef. Spatial resolution is one meter. Radiometric corrections converted the at-sensor digital number values to at surface spectral radiance values using sensor specific calibration coefficients and CSIRO's c-WomBat-c atmospheric correction software. Geometric corrections were done using field collected coordinates of features identified in the image. Projection used was Universal Transverse Mercator Zone 56 South and Datum used was WGS 84. Image data is in TIFF format.

Corel Geological Drafting Kit (CGDK) - an extensible CorelDRAW VBA program for geological drafting

Corel Geological Drafting Kit (CGDK), a program written in VBA, has been designed to assist geologists and geochemists with their drafting work. It obtains geological data from a running Excel application directly, and uses the data to plot geochemical diagrams and to construct stratigraphic columns. The software also contains functions for creating stereographic projections and rose diagrams, which can be used for spatial analysis, on a calibrated geological map. The user-friendly program has been tested to work with CorelDRAW 13 - 14 - 15 and Excel 2003 - 2007.

Reference list of 265 sources used for the discovery of relationships between data clusters and metadata properties

Visual cluster analysis provides valuable tools that help analysts to understand large data sets in terms of representative clusters and relationships thereof. Often, the found clusters are to be understood in context of belonging categorical, numerical or textual metadata which are given for the data elements. While often not part of the clustering process, such metadata play an important role and need to be considered during the interactive cluster exploration process. Traditionally, linked-views allow to relate (or loosely speaking: correlate) clusters with metadata or other properties of the underlying cluster data. Manually inspecting the distribution of metadata for each cluster in a linked-view approach is tedious, specially for large data sets, where a large search problem arises. Fully interactive search for potentially useful or interesting cluster to metadata relationships may constitute a cumbersome and long process. To remedy this problem, we propose a novel approach for guiding users in discovering interesting relationships between clusters and associated metadata. Its goal is to guide the analyst through the potentially huge search space. We focus in our work on metadata of categorical type, which can be summarized for a cluster in form of a histogram. We start from a given visual cluster representation, and compute certain measures of interestingness defined on the distribution of metadata categories for the clusters. These measures are used to automatically score and rank the clusters for potential interestingness regarding the distribution of categorical metadata. Identified interesting relationships are highlighted in the visual cluster representation for easy inspection by the user. We present a system implementing an encompassing, yet extensible, set of interestingness scores for categorical metadata, which can also be extended to numerical metadata. Appropriate visual representations are provided for showing the visual correlations, as well as the calculated ranking scores. Focusing on clusters of time series data, we test our approach on a large real-world data set of time-oriented scientific research data, demonstrating how specific interesting views are automatically identified, supporting the analyst discovering interesting and visually understandable relationships.