Integrating climate and local factors for geomorphological distribution models

Earth surface processes (ESPs) drive landscape development and ecosystem processes in high‐latitude regions by creating spatially heterogeneous abiotic and biotic conditions. Ongoing global change may potentially alter the activity of ESPs through feedback on ground conditions, vegetation and the carbon cycle. Consequently, accurate modeling of ESPs is important for improving understanding of the current and future distributions of these processes. The aims of this study were to: (1) integrate climate and multiple local predictors to develop realistic ensemble models for the four key ESPs occurring at high latitudes (slope processes, cryoturbation, nivation and palsa mires) based on the outputs of 10 modern statistical techniques; (2) test whether models of ESPs are improved by incorporating topography, soil and vegetation predictors to climate‐only models; (3) examine the relative importance of these variables in a multivariate setting. Overall, the models showed high transferability with the mean area under curve of a receiver operating characteristics (AUC) ranging from 0.83 to 0.96 and true skill statistics (TSS) from 0.52 to 0.87 for the most complex models. Even though the analyses highlighted the importance of the climate variables as the most influential predictors, three out of four models benefitted from the inclusion of local predictors. We conclude that disregarding local topography and soil conditions in spatial models of ESPs may cause a significant source of error in geomorphological distribution models. Copyright © 2014 John Wiley & Sons, Ltd.     

Radiometric stability assessment of an airborne photogrammetric sensor in a test field

Radiometric stability is a desired property of digital photogrammetric large-format sensors. This article presents a methodology for determining the radiometric stability of airborne imaging sensors in operational conditions in a test field and the results of stability evaluation of a large-format photogrammetric frame sensor DMC, from Intergraph. The imagery was collected in two days using nine different exposure settings, and images collected with variable exposure time and aperture were compared. The results showed promising stability in many cases, up to a level of 2% of the radiance, but less favorable results also appeared. Possible reasons for the unfavorable results could be the limitations of the experimental set-up or the instability of the sensor. DMC showed high radiometric performance potential, but high sensitivity to the exposure settings. Based on the results, recommendations for the future test field calibration and validation procedures were given. One limitation of the analysis was the insufficient information about the sensor stability potential; proposals were given to sensor manufacturers concerning the necessary information.     

Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models

The Finnish Meteorological Institute has calculated statistics for the new reference period of 1981–2010. During this project, the grid size has been reduced from 10 to 1 km, the evaluation of the interpolation has been improved, and comparisons between different methods has been performed. The climate variables of interest were monthly mean temperature and mean precipitation, for which the spatial variability was explained using auxiliary information: mean elevation, sea percentage, and lake percentage. We compared three methods for spatial prediction: kriging with external drift (KED), generalized additive models (GAM), and GAM combined with residual kriging (GK). Every interpolation file now has attached statistical key figures describing the bias and the normality of the prediction error. According to the cross-validation results, GAM was the best method for predicting mean temperatures, with only very small differences relative to the other methods. For mean precipitation, KED produced the most accurate predictions, followed by GK. In both cases, there was notable seasonal variation in the statistical skill scores. For the new reference period and future interpolations, KED was chosen as the primary method due to its robustness and accuracy.     

Demonstration of a virtual active hyperspectral LiDAR in automated point cloud classification

In this paper, a measurement system for the acquisition of a virtual hyperspectral LiDAR dataset is presented. As commercial hyperspectral LiDARs are not yet available, the system provides a novel type of data for the testing and developing of future hyperspectral LiDAR algorithms. The measurement system consists of two parts: first, backscattered reflectance spectra are collected using a spectrometer and a cutting-edge technology, white-light supercontinuum laser source; second, a commercial monochromatic LiDAR system is used for ranging. A virtual hyperspectral LiDAR dataset is produced by data fusion. Such a dataset was collected on a Norway spruce (Picea abies) sample. The performance of classification was tested using an experimental hyperspectral algorithm based on a novel combination of the Spectral Correlation Mapper and a region growing algorithm. The classifier was able to automatically distinguish between needles, branches and background, in other words, perform a difficult task using only traditional TLS data.     

Exploring the reservoir potential of Lower Cretaceous Clinoforms in the Fingerdjupet Subbasin,Norwegian Barents Sea

Sandy clinothems are of interest as hydrocarbon reservoirs but there is no proven, economic, clinothem reservoir in the Norwegian Barents Sea. We used high-resolution, 2D and 3D seismic, including proprietary data, to identify a previously untested, Barremian, clinoform wedge in the Fingerdjupet Subbasin (FSB). Data from recent well 7322/7-1 plus seismic have been used to characterize this wedge and older Lower Cretaceous clinoforms in the FSB. In the latest Hauterivian – early Barremian, during post-rift tectonic quiescence, shelf-edge clinoforms (foreset height > 150 m) prograded into an under-filled basin. Increased sediment input was related to regional uplift of the hinterland (northern Barents Shelf). Early Barremian erosion in the north-western FSB and mass wasting towards the SE were followed by deposition of delta-scale (<80 m high), high-angle (c. 8°) clinoform sets seaward of older shelf-edge clinoforms. This may be the local expression of a regional, early Barremian, regressive event. By the close of the Barremian, clinoforms had prograded, within a narrow, elongate basin, across the FSB and towards the uplifted Loppa High. A seismic wedge of high-angle (10–12°), low-relief, delta-scale (25–80 m) clinoform sets occurs between shelf-edge clinoforms to the NW and the uplifted area to the SE. Well 7322/7-1, positioned on a direct hydrocarbon indicator, <1 km NNW of the high-angle, low-relief, delta-scale clinoforms, found upward coarsening siltstone-cycles linked to relative sea-level fluctuations on a marine shelf. Sand may have accumulated, offshore from the well, in high-angle, low-relief foresets of the delta-scale clinothems (which are typical geometries elsewhere interpreted as ‘delta-scale, sand-prone subaqueous clinoforms’). Deposition was controlled by the paleosurface, storms and longshore currents on an otherwise mud-dominated shelf. The study highlights challenges associated with exploration for sandstone reservoirs in seismic wedges on an outer shelf.     

Automatic determination of stream networks from DEMs by using road network data to locate culverts

Determining stream networks automatically from digital elevation models is an issue that is actively being studied. The quality of elevation models has increased over time, but many hydrologically critical features, such as culverts, are often missing from the elevation data. To analyze the surficial water flow, one must either prepare a special elevation model or post-process an already-existing model.

This study builds on the traditional, well-established method of determining the stream network from digital elevation models. We have extended the traditional method by locating culverts automatically, using road network data as an input. We show, by comparison to the reference data, that the culverts being most relevant for the stream network can be found with good accuracy. We demonstrate that by including the automatically located culverts in the automatic stream network determination, the quality of the generated network can be noticeably improved.     

A 22 GHz receiver with high phase stability for radioastron space-VLBI-mission

A space-qualified low-noise 22 GHz receiver for the international space-VLBI mission Radioastron has been constructed. The microwave electronics is realized by using thermally matched hybrid circuits. The most important properties of the receiver are phase stability, sensitivity and reliability. The high sensitivity is due to a cooled low noise HEMT amplifier (LNA). The measured receiver noise temperature is less than 100 K. The phase stability is achieved by compact structure and thermal stabilization. Phase stabilities of better than 0.13°/°C and 0.2°/°C for the receiver and the LNA units are measured, respectively. The calculated reliability of the receiver exceeds the requirement of 0.97 for the three year mission.