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Diagenetic stability of non-traditional stable isotope systems (Ca, Sr, Mg, Zn) in teeth – An in-vitro alteration experiment of biogenic apatite in i…
2021
Stable isotope ratios and trace element concentrations of fossil bones and teeth are important geochemical proxies for the reconstruction of diet and past environment in archaeology and palaeontology. However, since diagenesis can significantly alter primary diet-related isotope signatures and elemental compositions, it is important to understand and quantify alteration processes. Here, we present the results of in-vitro alteration experiments of dental tissues from a modern African elephant molar reacted in aqueous solutions at 30 °C and 90 °C for 4 to 63 days. Dental cubes with ≈ 3 mm edge length, comprising both enamel and dentin, were placed into 2 mL of acidic aqueous sol…
Partitioning of nitrogen during melting and recycling in subduction zones and the evolution of atmospheric nitrogen
2019
Abstract The subduction of sediment connects the surface nitrogen cycle to that of the deep Earth. To understand the evolution of nitrogen in the atmosphere, the behavior of nitrogen during the subduction and melting of subducted sediments has to be estimated. This study presents high-pressure experimental measurements of the partitioning of nitrogen during the melting of sediments at sub-arc depths. For quantitative analysis of nitrogen in minerals and glasses, we calibrated the electron probe micro-analyzer on synthetic ammonium feldspar to measure nitrogen concentrations as low as 500 μg g−1. Nitrogen abundances in melt and mica are used together with mass balance calculations to determi…
Optimized Class-Separability in Hyperspectral Images
2016
International audience; Image visualization techniques are mostly based on three bands as RGB color composite channels for human eye to characterize the scene. This, however, is not effective in case of hyper-spectral images (HSI) because they contain dozens of informative spectral bands. To eliminate redundancy of spectral information among these bands, dimensionality reduction (DR) is applied while at the same trying to retain maximum information. In this paper, we propose a new method of information-preserved hyper-spectral satellite image visualization that is based on fusion of unsupervised band selection techniques and color matching function (CMF) stretching. The results show consist…
The joint sets on the Lilstock Benches, UK. Observations based on mapping a full resolution UAV-based image
2021
Outcrop studies of fracture networks are important to understand fractured reservoirs in the subsurface, but complete maps of all fractures in large outcrops are rare due to limitations of outcrop and image resolution. We manually mapped the first full-resolution UAV-based, Gigapixel dataset and DEM of the wave-cut Lilstock Benches in the southern Bristol Channel basin, a classic outcrop of layer-bound fracture networks in limestones. We present a map of the patterns and age relationships of successive sets of joints in dm-thick limestone layers separated by claystone beds. Using interpretation criteria based on crosscutting relationships, abutting and joint length, up to eight successive s…
Recent Advances in Techniques for Hyperspectral Image Processing
2009
International audience; Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than thirty years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspec- tral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the high-dimensional nature of the data, and to integrate the spa- tial and spectral information. Performance of the discussed techniques is evaluated in …
Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging
2017
Made available in DSpace on 2018-12-11T17:11:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-03-01 Suomen Akatemia Small unmanned aerial vehicle (UAV) based remote sensing is a rapidly evolving technology. Novel sensors and methods are entering the market, offering completely new possibilities to carry out remote sensing tasks. Three-dimensional (3D) hyperspectral remote sensing is a novel and powerful technology that has recently become available to small UAVs. This study investigated the performance of UAV-based photogrammetry and hyperspectral imaging in individual tree detection and tree species classification in boreal forests. Eleven test sites with 4151 reference trees repr…
Automotive Radar in a UAV to Assess Earth Surface Processes and Land Responses
2020
The use of unmanned aerial vehicles (UAVs) in earth science research has drastically increased during the last decade. The reason being innumerable advantages to detecting and monitoring various environmental processes before and after certain events such as rain, wind, flood, etc. or to assess the current status of specific landforms such as gullies, rills, or ravines. The UAV equipped sensors are a key part to success. Besides commonly used sensors such as cameras, radar sensors are another possibility. They are less known for this application, but already well established in research. A vast number of research projects use professional radars, but they are expensive and difficult to hand…
FAME: Software for analysing rock microstructures
2016
Determination of rock microstructures leads to a better understanding of the formation and deformation of polycrystalline solids. Here, we present FAME (Fabric Analyser based Microstructure Evaluation), an easy-to-use MATLAB®-based software for processing datasets recorded by an automated fabric analyser microscope. FAME is provided as a MATLAB®-independent Windows® executable with an intuitive graphical user interface. Raw data from the fabric analyser microscope can be automatically loaded, filtered and cropped before analysis. Accurate and efficient rock microstructure analysis is based on an advanced user-controlled grain labelling algorithm. The preview and testing environments simplif…
Estimating Missing Information by Cluster Analysis and Normalized Convolution
2018
International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.
SVM-based classification of High resolution Urban Satellites Images using Dense SURF and Spectral Information
2018
Remote-sensing focusing on image classification knows a large progress and receives the attention of the remote-sensing community day by day. Combining many kinds of extracted features has been successfully applied to High resolution urban satellite images using support vector machine (SVM). In this paper, we present a methodology that is promoting a performed classification by using pixel-wise SURF description features combined with spectral information in Cielab space for the first time on common scenes of urban imagery. The proposed method gives a promising classification accuracy when compared with the two types of features used separately.