Simulating the moderating effect of a lake on downwind temperatures

A steady-state, two-dimensional numerical model is used to simulate air temperatures and humidity downwind of a lake at night. Thermal effects of the lake were modelled for the case of moderate and low surface winds under the cold-air advective conditions that occur following the passage of a cold front. Surface temperatures were found to be in good agreement with observations. A comparison of model results with thermal imagery indicated the model successfully predicts the downwind distance for which thermal effects due to the lake are significant.     

Sea‐level and ocean‐current control on carbonate‐platform growth,Maldives, Indian Ocean

Multichannel high‐resolution seismic and multibeam data were acquired from the Maldives‐isolated carbonate platform in the Indian Ocean for a detailed characterization of the Neogene bank architecture of this edifice. The goal of the research is to decipher the controlling factors of platform evolution, with a special emphasis on sea‐level changes and changes of the oceanic currents. The stacking pattern of Lower to Middle Miocene depositional sequences, with an evolution of a ramp geometry to a flat‐topped platform, reflects variations of accommodation, which here are proposed to be primarily governed by fluctuations of relative sea level. Easterly currents during this stage of bank growth controlled an asymmetric east‐directed progradation of the bank edge. During the late middle Miocene, this system was replaced by a twofold configuration of bank development. Bank growth continued synchronously with partial bank demise and associated sediment‐drift deposition. This turnover is attributed to the onset and/or intensification of the Indian monsoon and related upwelling and occurrence of currents, locally changing environmental conditions and impinging upon the carbonate system. Mega spill over lobes, shaped by reversing currents, formed as large‐scale prograding complexes, which have previously been interpreted as deposits formed during a forced regression. On a regional scale, a complex carbonate‐platform growth can occur, with a coexistence of bank‐margin progradation and aggradation, as well as partial drowning. It is further shown that a downward shift of clinoforms and offlapping geometries in carbonate platforms are not necessarily indicative for a sea‐level driven forced regression. Findings are expected to be applicable to other examples of Cenozoic platforms in the Indo‐Pacific region.     

Automated mapping of rock slope geometry,kinematics and stability with RSS-GIS

A GIS-implemented, deterministic approach for the automated spatial evaluation of geometrical and kinematical properties of rock slope terrains is presented. Based on spatially distributed directional information on planar geological fabrics and DEM-derived topographic attribute data, the internal geometry of rock slopes can be characterized on a grid cell basis. For such computations, different approaches for the analysis and regionalization of available structural directional information applicable in specific tectonic settings are demonstrated and implemented in a GIS environment. Simple kinematical testing procedures based on feasibility criteria can be conducted on a pixel basis to determine which failure mechanisms are likely to occur at particular terrain locations. In combination with hydraulic and strength data on geological discontinuities, scenario-based rock slope stability evaluations can be performed. For conceptual investigations on rock slope failure processes, a GIS-based specification tool for a 2-D distinct element code (UDEC) was designed to operate with the GIS-encoded spatially distributed rock slope data. The concepts of the proposed methodology for rock slope hazard assessments are demonstrated at three different test sites in Germany.     

Applying landscape-ecological concept and GIS modelling for assessing and mapping of ecological situation of mountainous landscapes (on the case of Syunik marz,Armenia)

Regional landscape-ecological studies have acquired a special topicality as they assure efficient environmental conservation and sustainable use of natural resources. A landscape-ecological analysis was performed based on four basic integral indices: (1) ecological potential, (2) ecological stability, (3) ecological load and (4) ecological tension. The values of basic integral indices of the landscape-ecological analysis were calculated as sums of respective factors expressed in scores and multiplied by their significance reflecting coefficients. In agreement with that rule, a formula was derived of calculation of basic indices of landscape-ecological analysis. Subsequently, those factors were integrated by ‘Model Builder’ in ArcGIS applying ‘Weighted Sum’ functions. Finally, through geographic information systems modelling, maps of basic indices of landscape-ecological analysis were produced. In conclusion – ecological potential, stability, load and tension are best indicators for the assessment of the landscape-ecological situation of the studied territory.     

A Composite Semisupervised SVM for Classification of Hyperspectral Images

This letter presents a novel composite semisupervised support vector machine (SVM) for the spectral-spatial classification of hyperspectral images. In particular, the proposed technique exploits the following: 1) unlabeled data for increasing the reliability of the training phase when few training samples are available and 2) composite kernel functions for simultaneously taking into account spectral and spatial information included in the considered image. Experiments carried out on a hyperspectral image pointed out the effectiveness of the presented technique, which resulted in a significant increase of the classification accuracy with respect to both supervised SVMs and progressive semisupervised SVMs with single kernels, as well as supervised SVMs with composite kernels.     

The determination of potential difference by the joint application of measured and synthetical gravity data: a case study in Hungary

In an elementary approach every geometrical height difference between the staff points of a levelling line should have a corresponding average g value for the determination of potential difference in the Earth’s gravity field. In practice this condition requires as many gravity data as the number of staff points if linear variation of g is assumed between them. Because of the expensive fieldwork, the necessary data should be supplied from different sources. This study proposes an alternative solution, which is proved at a test bed located in the Mecsek Mountains, Southwest Hungary, where a detailed gravity survey, as dense as the staff point density (~1 point/34 m), is available along a 4.3-km-long levelling line. In the first part of the paper the effect of point density of gravity data on the accuracy of potential difference is investigated. The average g value is simply derived from two neighbouring g measurements along the levelling line, which are incrementally decimated in the consecutive turns of processing. The results show that the error of the potential difference between the endpoints of the line exceeds 0.1 mm in terms of length unit if the sampling distance is greater than 2 km. Thereafter, a suitable method for the densification of the decimated g measurements is provided. It is based on forward gravity modelling utilising a high-resolution digital terrain model, the normal gravity and the complete Bouguer anomalies. The test shows that the error is only in the order of 10⁻³mm even if the sampling distance of g measurements is 4 km. As a component of the error sources of levelling, the ambiguity of the levelled height difference which is the Euclidean distance between the inclined equipotential surfaces is also investigated. Although its effect accumulated along the test line is almost zero, it reaches 0.15 mm in a 1-km-long intermediate section of the line.     

Changes in timber haul emissions in the context of shifting forest management and infrastructure

Background  

Although significant amounts of carbon may be stored in harvested wood products, the extraction of that carbon from the forest generally entails combustion of fossil fuels. The transport of timber from the forest to primary milling facilities may in particular create emissions that reduce the net sequestration value of product carbon storage. However, attempts to quantify the effects of transport on the net effects of forest management typically use relatively sparse survey data to determine transportation emission factors. We developed an approach for systematically determining transport emissions using: 1) -remotely sensed maps to estimate the spatial distribution of harvests, and 2) - industry data to determine landscape-level harvest volumes as well as the location and processing totals of individual mills. These data support spatial network analysis that can produce estimates of fossil carbon released in timber transport.     

Mapping of aggregated floodplain plant communities using image fusion of CASI and LiDAR data

Combined optical and laser altimeter data offer the potential to map and monitor plant communities based on their spectral and structural characteristics. A problem unresolved is, however, that narrowly defined plant communities, i.e. plant communities at a low hierarchical level of classification in the Braun-Blanquet system, often cannot be linked directly to remote sensing data for vegetation mapping. We studied whether and how a floristic dataset can be aggregated into a few major discrete, mappable classes without substantial loss of ecological meaning. Multi-source airborne data (CASI and LiDAR) and floristic field data were collected for a floodplain along the river Waal in the Netherlands. Mapping results based on floristic similarity alone did not achieve highest levels of accuracy. Ordination of floristic data showed that terrain elevation and soil moisture were the main underlying environmental drivers shaping the floodplain vegetation, but grouping of plant communities based on their position in the ordination space is not always obvious. Combined ordination-based grouping with floristic similarity clustering led to syntaxonomically relevant aggregated plant assemblages and yielded highest mapping accuracies.