Maps of coastal and marine geomorphology between Albenga and Savona (NW Mediterranean Sea, Italy)

In this paper, we present a map describing the main geomorphological features of the coastal and marine area between the towns of Albenga and Savona (Ligurian Sea, NW Mediterranean) corresponding to a coastal stretch of ~40 km. To produce this map, we collated data from the literature, orthophotos, perspective photos, multibeam and side scan sonar data, and undertook direct surveys to ground truth data obtained using indirect techniques. We divided the information into nine thematic layers, including bathymetry, natural coastal types, geomorphological elements, seafloor coverage (both geological and biological), coastal and nearshore dynamics, human influence on coastal and marine environments, coastal occupation and protected areas.

Time-series of seagrass and land cover maps from 1972 to 2010, in South East Queensland, Australia, with links to GeoTIFFs

Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972-2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.

Ground-penetrating radar (GPR) point measurements of ice thickness in Austria

Glacier thickness is an important factor in the course of glacier retreat in a warming climate. Thiese study data presents the results (point data) of GPR surveys on 66 Austrian mountain glaciers carried out between 1995 and 2014. The glacier areas range from 0.001 to 18.4 km**2, and their ice thickness has been surveyed with an average density of 36 points/km**2 . The glacier areas and surface elevations refer to the second Austrian glacier inventory (mapped between 1996 and 2002). According to the glacier state recorded in the second glacier inventory, the 64 glaciers cover an area of 223.3±3.6 km**3. Maps of glacier thickness have been calculated by Fischer and Kuhn (2013) with a mean thickness of 50±3 m and contain an glacier volume of 11.9±1.1 km**3. The mean maximum ice thickness is 119±5 m. The ice thickness measurements have been carried out with the transmitter of Narod and Clarke (1994) combined with restively loaded dipole antennas (Wu and King, 1965; Rose and Vickers, 1974) at central wavelengths of 6.5 (30 m antenna length) and 4.0 MHz (50 m antenna length). The signal was recorded trace by trace with an oscilloscope. 168 m/µs as used by Haeberli et al. (1982), Bauder (2001), and Narod and Clarke (1994), the signal velocity in air is assumed to be 300 m/µs. Details on the method can be are found in Fischer and Kuhn (2013), as well as Span et al. (2005) and Fischer et al. (2007).

Inventory of thermo-erosional valleys and streams in three ice-rich permafrost lowlands adjacent to the Laptev Sea, with links to maps in ArcGIS format

This dataset provides an inventory of thermo-erosional landforms and streams in three lowland areas underlain by ice-rich permafrost of the Yedoma-type Ice Complex at the Siberian Laptev Sea coast. It consists of two shapefiles per study region: one shapefile for the digitized thermo-erosional landforms and streams, one for the study area extent. Thermo-erosional landforms were manually digitized from topographic maps and satellite data as line features and subsequently analyzed in a Geographic Information System (GIS) using ArcGIS 10.0. The mapping included in particular thermo-erosional gullies and valleys as well as streams and rivers, since development of all of these features potentially involved thermo-erosional processes. For the Cape Mamontov Klyk site, data from Grosse et al. [2006], which had been digitized from 1:100000 topographic map sheets, were clipped to the Ice Complex extent of Cape Mamontov Klyk, which excludes the hill range in the southwest with outcropping bedrock and rocky slope debris, coastal barrens, and a large sandy floodplain area in the southeast. The mapped features (streams, intermittent streams) were then visually compared with panchromatic Landsat-7 ETM+ satellite data (4 August 2000, 15 m spatial resolution) and panchromatic Hexagon data (14 July 1975, 10 m spatial resolution). Smaller valleys and gullies not captured in the maps were subsequently digitized from the satellite data. The criterion for the mapping of linear features as thermo-erosional valleys and gullies was their clear incision into the surface with visible slopes. Thermo-erosional features of the Lena Delta site were mapped on the basis of a Landsat-7 ETM+ image mosaic (2000 and 2001, 30 m ground resolution) [Schneider et al., 2009] and a Hexagon satellite image mosaic (1975, 10 m ground resolution) [G. Grosse, unpublished data] of the Lena River Delta within the extent of the Lena Delta Ice Complex [Morgenstern et al., 2011]. For the Buor Khaya Peninsula, data from Arcos [2012], which had been digitized based on RapidEye satellite data (8 August 2010, 6.5 m ground resolution), were completed for smaller thermo-erosional features using the same RapidEye scene as a mapping basis. The spatial resolution, acquisition date, time of the day, and viewing geometry of the satellite data used may have influenced the identification of thermo-erosional landforms in the images. For Cape Mamontov Klyk and the Lena Delta, thermo-erosional features were digitized using both Hexagon and Landsat data; Hexagon provided higher resolution and Landsat provided the modern extent of features. Allowance of up to decameters was made for the lateral expansion of features between Hexagon and Landsat acquisitions (between 1975 and 2000).

The distribution of meiofauna in surface sediments of the Fladen Ground, North Sea

A general study of structure, biomass, and dynamic estimates on meiofauna was carried out during PREFLEX (1975) and FLEX (1976), in 117- 141 m water depth. On the basis of these data an attempt was made to estimate meiofauna production, and this is discussed in relation to the energy input from the spring phytoplankton bloom. Sampling was performed at five stations, but only the stations 1, 4, and 5 were covered by a complete series from August 1975 to July 1976. At each station, from four replicate box core samples, two were withdrawn to study the abundance, distribution, and biomass of meiofauna, the content of chloroplastic pigment equivalents (CPE), and chemical and grain size analyses. At all stations grain size fell in the range of fine sand having median diameters (MD) of < 125 µm. From station 1 to 5 an increase in MD was observed. Highest values of CPE (7.81 µg m l**-1) and organic matter (4.7 %) were obtained in June and July (1976)/ August (1975), respectively. Meiofauna abundance was fairly uniform at all stations examined. Station 1 displayed maximal numbers during the whole investigation period. The abundance per 100 cm**2 varied between 15,550 and 34,900 organisms. All meiofauna studied both in total and as separate taxa showed annual cycles of abundance. Low abundance values were recorded during early summer, and maximum values during winter. High numbers of Foraminifera were obtained for August 1975 (9,460 per 100 cm**2) and July 1976 (9,710 per 100 cm**2). From December to June the values decreased from 3,280 to 1,030 per 100 cm**2. At station 1 maximum values of meiofauna biomass were recorded ranging from 1.5 to 2.7 g DWT m**-2. The mean meiofauna dry weight amounted to 2.1 g DWT m**-2. Based on minimum production, the P/B ratio for the area of station 1 might have a mean of 1.4. Taking into consideration generation times we believe that a turnover ratio of 2 is a conservative value for the Fladen Ground meiofauna. The annual production would amount to 4.2 g DWT m**-2 yr**-1. This is 27.5 % of the energy supply during the spring phytoplankton bloom, which is channelled into the meiofauna. The hypothesis is put forward that the energetic strategy of deep offshore meiofauna differs distinctively from that of shallow inshore meiofauna. While the shallow inshore meiofauna show a relatively fast response to organic matter input, the deep offshore meiofauna reacts much more slowly, the food energy consumption seems to be spread out over a longer period.