Crete fault scarp point cloud data

This paper assesses the along strike variation of active bedrock fault scarps using long range terrestrial laser scanning (t-LiDAR) data in order to determine the distribution behaviour of scarp height and the subsequently calculate long term throw-rates. Five faults on Cretewhich display spectacular limestone fault scarps have been studied using high resolution digital elevation model (HRDEM) data. We scanned several hundred square metres of the fault system including the footwall, fault scarp and hanging wall of the investigated fault segment. The vertical displacement and the dip of the scarp were extracted every metre along the strike of the detected fault segment based on the processed HRDEM. The scarp variability was analysed by using statistical and morphological methods. The analysis was done in a geographical information system (GIS) environment. Results show a normal distribution for the scanned fault scarp's vertical displacement. Based on these facts, the mean value of height was chosen to define the authentic vertical displacement. Consequently the scarp can be divided into above, below and within the range of mean (within one standard deviation) and quantify the modifications of vertical displacement. Therefore, the fault segment can be subdivided into areas which are influenced by external modification like erosion and sedimentation processes. Moreover, to describe and measure the variability of vertical displacement along strike the fault, the semi-variance was calculated with the variogram method. This method is used to determine how much influence the external processes have had on the vertical displacement. By combining of morphological and statistical results, the fault can be subdivided into areas with high external influences and areas with authentic fault scarps, which have little or no external influences. This subdivision is necessary for long term throw-rate calculations, because without this differentiation the calculated rates would be misleading and the activity of a fault would be incorrectly assessed with significant implications for seismic hazard assessment since fault slip rate data govern the earthquake recurrence. Furthermore, by using this workflow areas with minimal external influences can be determined, not only for throw-rate calculations, but also for determining samples sites for absolute dating techniques such as cosmogenic nuclide dating. The main outcomes of this study include: i) there is no direct correlation between the fault's mean vertical displacement and dip (R² less than 0.31); ii) without subdividing the scanned scarp into areas with differing amounts of external influences, the along strike variability of vertical displacement is ±35%; iii) when the scanned scarp is subdivided the variation of the vertical displacement of the authentic scarp (exposed by earthquakes only) is in a range of ±6% (the varies depending on the fault from 7 to 12%); iv) the calculation of the long term throw-rate (since 13 ka) for four scarps in Crete using the authentic vertical displacement is 0.35 ± 0.04 mm/yr at Kastelli 1, 0.31 ± 0.01 mm/yr at Kastelli 2, 0.85 ± 0.06 mm/yr at the Asomatos fault (Sellia) and 0.55 ± 0.05 mm/yr at the Lastros fault.

Bathymetry grids and maps of Mozambique Ridge compiled from cruises 64PE305, 64PE306, SO-87, SO-182, SO-183, ME-33/2, ME-63/1 bathymetry

Based on data from R.V. Pelagia, R.V. Sonne and R.V. Meteor multibeam sonar surveys, a high resolution bathymetry was generated for the Mozambique Ridge. The mapping area is divided into five sheets, one overview and four sub-sheets. The boundaries are (west/east/south/north): Sheet 1: 28°30' E/37°00' E/36°20' S/24°50' S; Sheet 2: 32°45' E/36°45' E/28°20' S/25°20' S; Sheet 3: 31°30' E/36°45' E/30°20' S/28°10' S; Sheet 4: 30°30' E/36°30' E/33°15' S/30°15' S; Sheet 5: 28°30' E/36°10' E/36°20' S/33°10' S. Each sheet was generated twice: one from swath sonar bathymetry only, the other one is completed with depths from ETOPO2 predicted bathymetry. Basic outcome of the investigation are Digital Terrain Models (DTM), one for each sheet with 0.05 arcmin (~91 meter) grid spacing and one for the entire area (sheet 1) with 0.1 arcmin grid spacing. The DTM's were utilized for contouring and generating maps. The grid formats are NetCDF (Network Common Data Form) and ASCII (ESRI ArcGIS exchange format). The Maps are formatted as jpg-images and as small sized PNG (Portable Network Graphics) preview images. The provided maps have a paper size of DIN A0 (1189 x 841 mm).

Bathymetry grids and maps of Mozambique Basin compiled from cruise SO183 bathymetry

Based on data from R/V Sonne multibeam sonar surveys in 2005 a high resolution bathymetry was generated for the Mozambique Basin. The area covers approx. 466,475 sqkm. The mapping area is divided into four sheets with boundaries (west/east/south/north): Sheet I (north-west), 37:00/39:45/-24:00/-20:20; Sheet II (north-east), 39:45/42:30/-24:00/-20:20; Sheet III (south-west), 37:00/39:45/-27:40/-24:00; Sheet IV (south-east), 39:45/42:30/-27:40/-24:00. Basic outcome of the investigation are Digital Terrain Models (DTM), one for each sheet with 0.05 arcmin (~91 meter) grid spacing and one for the entire area with 0.1 arcmin grid spacing. The DTM's were utilized for contouring and generating maps. Moreover the measured bathymetry was combined and compared with GEBCO bathymetry and predicted bathymetry, derived from altimeter satellites. The provided maps have a paper size of DIN A0 (1188.9 x 841 mm).

Present-day King George Island ice cap geometry measured by ground penetrating radar in 2008/09

We present a consistent data set for the ice thickness, the bedrock topography and the ice surface topography of the King George Island ice cap (Arctowski Icefield and the adjacent central part). The data set is composed of groundbased and airborne Ground Penetrating Radar (GPR) and differential GPS (DGPS) measurements, obtained during several field campaigns. The data set incorporates groundbased measurements in the safely accessible inner parts and airborne measurements in the heavily crevassed coastal areas of the ice cap. In particular, the inclusion of airborne GPR measurements with the 30MHz BGR-P30-System developed at the Institute of Geophysics (University of Münster) completes the picture of the ice geometry substantially. The compiled digital elevation model of the bedrock shows a rough, highly variable topography with pronounced valleys, ridges, and troughs. The mean ice thickness is approx. 238m, with a maximum value of approx. 400m in the surveyed area. Noticeable are bounded areas in the bedrock topography below sea level where marine based ice exists.

Volume changes of Jacobshavn Isbrae between 1985, 1997 and 2007

Following three decades of relative stability, Jakobshavn Isbrae, West Greenland, underwent dramatic thinning, retreat and speed-up starting in 1998. To assess the amount of ice loss, we analyzed 1985 aerial photos and derived a 40 m grid digital elevation model (DEM). We also obtained a 2007 40 m grid SPOT DEM covering the same region. Comparison of the two DEMs over an area of ~4000 km**2 revealed a total ice loss of 160 ± 4 km**3, with 107 ± 0.2 km**3 in grounded regions (0.27 mm eustatic sea-level rise) and 53 ± 4 km**3 from the disintegration of the floating tongue. Comparison of the DEMs with 1997 NASA Airborne Topographic Mapper data indicates that this ice loss essentially occurred after 1997, with +0.7 ± 5.6 km**3 between 1985 and 1997 and -160 ± 7 km**3 between 1997 and 2007. The latter is equivalent to an average specific mass balance of -3.7 ± 0.2 m/a over the study area. Previously reported thickening of the main glacier during the early 1990s was accompanied by similar-magnitude thinning outside the areas of fast flow, indicating that the land-based ice continued reacting to longer-term climate forcing.

Geological map of Heimefrontfjella, Dronning Maud Land, Antarctica (Scale 1:250,000)

The geological overview map was compiled from 15 geological maps (1 : 25,000) and is based on Jacobs et al. 1996. The topographic basemaps were adapted from unpublished 1:250,000 provisional topographic maps, Institut f. Angewandte Geodäsie, Frankfurt, 1983. Part of the contour lines are from Radarsat (Liu et al. 2001).

King George Island TanDEM-X DEM, link to GeoTIFF

We have generated a new digital elevation model for entire King George Island, Antarctica, using summer TanDEM-X bistatic SAR satellite data. The data was processed using differential SAR interferometry with an older DEM as reference. 4 TanDEM-X scenes from January 2012 were used as input. The new DEM was referenced to and validated against DGPS measurements. Height values are given in reference to ellipsoid (WGS84).

Soil organic carbon storage and soil properties for 50 soil profiles in the Lena River Delta including land form description and map

To project the future development of the soil organic carbon (SOC) storage in permafrost environments, the spatial and vertical distribution of key soil properties and their landscape controls needs to be understood. This article reports findings from the Arctic Lena River Delta where we sampled 50 soil pedons. These were classified according to the U.S.D.A. Soil Taxonomy and fall mostly into the Gelisol soil order used for permafrost-affected soils. Soil profiles have been sampled for the active layer (mean depth 58±10 cm) and the upper permafrost to one meter depth. We analyze SOC stocks and key soil properties, i.e. C%, N%, C/N, bulk density, visible ice and water content. These are compared for different landscape groupings of pedons according to geomorphology, soil and land cover and for different vertical depth increments. High vertical resolution plots are used to understand soil development. These show that SOC storage can be highly variable with depth. We recommend the treatment of permafrost-affected soils according to subdivisions into: the surface organic layer, mineral subsoil in the active layer, organic enriched cryoturbated or buried horizons and the mineral subsoil in the permafrost. The major geomorphological units of a subregion of the Lena River Delta were mapped with a land form classification using a data-fusion approach of optical satellite imagery and digital elevation data to upscale SOC storage. Landscape mean SOC storage is estimated to 19.2±2.0 kg C/m**2. Our results show that the geomorphological setting explains more soil variability than soil taxonomy classes or vegetation cover. The soils from the oldest, Pleistocene aged, unit of the delta store the highest amount of SOC per m**2 followed by the Holocene river terrace. The Pleistocene terrace affected by thermal-degradation, the recent floodplain and bare alluvial sediments store considerably less SOC in descending order.

Grain size distribution and sea level changes in Gåsfjärden fjord

We analysed long-term variations in grain-size distribution in sediments from Gåsfjärden, a fjord-like inlet on the south-west Baltic Sea, and explored potential drivers of the recorded changes in sediment grain-size data. Over the last 5.4 thousand years (ka), the relative sea level decreased 17 m in the study region, caused by isostatic land uplift. As a consequence, Gåsfjärden has been transformed from an open coastal setting into a semi-closed inlet surrounded on the east by numerous small islands. To quantitatively estimate the morphological changes in Gåsfjärden over the last 5.4 ka and to further link the changes to our grain-size data, a digital elevation model (DEM)-based openness index was calculated. In the period between 5.4 and 4.4 ka BP, the inlet was characterised by the largest openness index. During this interval, the highest sand contents (~0.4 %) and silt/clay ratios (~0. 3) in the sediment sequence were recorded, indicating relatively high bottom water energy. After 4.4 ka BP, the average sand content was halved to ~0.2 % and the silt/clay ratios showed a significant decreasing trend over the last 4 ka. These changes are found to be associated with the gradual embayment of Gåsfjärden as represented in the openness index. The silt/clay ratios exhibited a delayed and slower change compared with the sand contents, which further suggest that finer particles are less sensitive to changes in hydrodynamic energy. Our DEM-based coastal openness index has proved to be a useful tool for interpreting the sedimentary grain-size record.

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling, links to files in GeoTIFF format

Topographic variation, the spatial variation in elevation and terrain features, underpins a myriad of patterns and processes in geography and ecology and is key to understanding the variation of life on the planet. The characterization of this variation is scale-dependent, i.e. it varies with the distance over which features are assessed and with the spatial grain (grid cell resolution) of analysis. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale basic research and analytical applications, however to date, such technique is unavailable. Here we used the digital elevation model products of global 250 m GMTED and near-global 90 m SRTM to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile and tangential curvature, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches (median, average, minimum, maximum, standard deviation, percent cover, count, majority, Shannon Index, entropy, uniformity). While a global cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at http://www.earthenv.org and can serve as a basis for standardized hydrological, environmental and biodiversity modeling at a global extent.

Distribution models for mountain plant species: The value of elevation

The climatic conditions of mountain habitats are greatly influenced by topography. Large differences in microclimate occur with small changes in elevation, and this complex interaction is an important determinant of mountain plant distributions. In spite of this, elevation is not often considered as a relevant predictor in species distribution models (SDMs) for mountain plants. Here, we evaluated the importance of including elevation as a predictor in SDMs for mountain plant species. We generated two sets of SDMs for each of 73 plant species that occur in the Pacific Northwest of North America; one set of models included elevation as a predictor variable and the other set did not. AUC scores indicated that omitting elevation as a predictor resulted in a negligible reduction of model performance. However, further analysis revealed that the omission of elevation resulted in large over-predictions of species' niche breadths-this effect was most pronounced for species that occupy the highest elevations. In addition, the inclusion of elevation as a predictor constrained the effects of other predictors that superficially affected the outcome of the models generated without elevation. Our results demonstrate that the inclusion of elevation as a predictor variable improves the quality of SDMs for high-elevation plant species. Because of the negligible AUC score penalty for over-predicting niche breadth, our results support the notion that AUC scores alone should not be used as a measure of model quality. More generally, our results illustrate the importance of selecting biologically relevant predictor variables when constructing SDMs.