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  • Alexanderson, Helena, et al. (author)
  • Aeolian activity in Sweden: an unexplored environmental archive
  • 2016
  • Reports (other academic/artistic)abstract
    • During the course of this three-year project, we have studied aeolian deposits at 70 sites within sixteen areas in south-central Sweden. Inland dunes have been the focus, but some sites with coversand and coastal dunes have also been investigated. We have mapped dune morphology, mainly by LiDAR-based remote sensing, studied the internal sediment architecture by ground-penetrating radar profiling and in sediment exposures, documented the sedimentology of the deposits with field and laboratory methods as well as determined the age of the deposits with luminescence and radiocarbon dating. In this scientific report to the Geological Survey of Sweden, who funded the project, we present a summary of the project and its results. The largest and best developed dune fields are found at glacifluvial deposits in Värmland and Dalarna, while in areas south thereof there are mainly scattered dunes or coversand deposits. A range of dune types has been observed, but transverse dunes seem to be dominating and the majority of these are oriented roughly NE-SW. The bulk of the aeolian deposits were formed shortly after the local deglaciation and, once stabilised, do not appear to have been significantly reworked during the Holocene. Most Mid- and Late-Holocene aeolian deposits consist of coversand, apart from in coastal areas where e.g. young foredunes are found.Our results thus largely confirm the hypothesis of previous investigators but we do add a significant amount of new information. We provide, for the first time for most of our study areas, numerical ages for the aeolian deposits and thus provide the timing and duration of sand-drift events in south-central Sweden. The ages, in combination with detailed geomorphological mapping, allow us to distinguish phases of dune-field development, which are likely due to changes in wind patterns and vegetation cover, and also to correlate Swedish aeolian deposits to regional storminess periods. Based on sedimentological information we are able to reconstruct dominating depositional processes, transport paths and sediment sources. Additional outcomes of the project are e.g. methodological developments (LiDAR mapping, luminescence dating) and pilot studies of potential relevance for applied geology (coastal development).
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  • Holmqvist, Björn (author)
  • Classification of large pollen datasets using neural networks with application to mapping and modelling pollen data
  • 2005
  • Doctoral thesis (other academic/artistic)abstract
    • This thesis concerns the usage of large pollen databases and their application to mapping and modelling past vegetation. Maps of past taxon distributions are generated and classification techniques are used to compile maps of past woodland types. These visualisations of pollen data have applications in forest ecology and in modelling the impacts of climate change. Maps of the distribution limits of Picea abies in southern Scandinavia are compared with output from a bioclimatic model to explore distribution-climate relationships during the last 1500 years. Further a classification technique is used to map distributions of Danish forest types over the last 3000 years. Classification is done by assigning a sample to a group or a category of similar properties. The categories in this case are woodland types. The classification model is an artificial neural network as trained on an entire database of actual pollen assemblages, resulting in a classification model able to classify pollen samples to a woodland type. This classification model is then used on the grid of interpolated fossil pollen assemblages to produce woodland history maps. Classification methods group the most similar samples, but somewhere a decision has to be made on how many classes or groups to use. I have developed a method for choosing the number of classes that have the highest reproducibility . This is an objective, repeatable method for assessing the optimal number of clusters in a multivariate dataset.
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  • Result 1-6 of 6

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