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EN
MinPlot is a MATLAB®-based mineral formula recalculation and compositional plotting program for electron microprobe analyses (EPMA). The program offers recalculation and structural formula assignment for 15 different mineral groups: Garnet, pyroxene, olivine, amphibole, feldspar, mica, staurolite, cordierite, chlorite, chloritoid, talc, epidote, titanite, spinel, and sulfides. MinPlot is a fast and easy to use command line program and requires no prior computer programming knowledge. Percent mass fractions of oxides are loaded from datafiles and the user answers simple prompts to select mineral type, normalization scheme, and plotting options. Recalculated mineral formulas are automatically saved as output files and plots may be further manually customized by the user prior to saving. MinPlot can perform thousands of calculations in seconds and the modular nature of the program makes it simple to add new calculation routines in future releases. Combined, these features make MinPlot a powerful and useful program for the processing of EPMA data.
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Content available remote Using TeX Markup Language for 3D and 2D Geological Plotting
EN
The paper presents technical application of TeX high-level, descriptive markup language for processing geological dataset from soil laboratory. Geotechnical measurements included equivalent soil cohesion, absolute and absolute deformation index, soil compressibility coefficient by time of immersion depth, exposure time to compressive strength to samples and physical and mechanical properties (humidity, density). Dataset was received from laboratory based experimental tests of the physical and mechanical properties of soils. Data were converted to csv table and processed by LaTeX. Methodology is based on LaTeX packages: {tikz}, {tikz-3dplot}, {tikzpicture}, {pgfplot}, {filecontetns}, {spy} for 3D plotting showing correlation in variables and descriptive statistical analysis based on the data array processing. Results demonstrated LaTeX scripts and graphics: 2D and 3D scatterplots, ternaries, bar charts, boxplots, zooming techniques detailing fragment of the plot, flowchart. Research novelty consists in technical approach of TeX language application for geo- logical data processing and graphical visualization. Engineering graphics by TeX was demonstrated with screenshots of the codes used for plotting.
EN
Single crown detection in forest stands based on VHR imagery has been the subject of research for over a decade. Recent progress in crown detection shows how hotspots can be isolated from tree crowns. The spatial distribution of hotspots is related to tree species, stand development and clown density. Due to high resolution (spectral & spatial) of the QuickBird data set, insight into the relationship between crown-hotspots, tree age and crown density - can be analyzed in more detail. The data fusion of spatial information obtained by forest inventory, GPS measurements and the relation between SILP attribute and geometrical database (digital forest map . LMN) allows to build up the connection to the spectral signature registered by the satellite imagery. Estimation of crown diameter based on the hotspots from Quickbird data, as well as the spatial distribution of the total crown area is the main goal of this study. Various concepts (Thyssen polygon, irregular triangulation etc) open diverse modeling possibilities. In this study, a selection of available models is applied to the point set of crownhotspots. For this purpose, Quickbird image (15.09.2003) of a part of the Niepolomice Forest (south Poland) was used. Crown distribution and development of stands are related to the age and height of trees. The cross validation between different measurements clarify the potential of VHR data to achieve a reliable level of crown density estimation. This allows extrapolating the model over the whole forest area. For the forest management, stand age, species and height are the attributes incorporated in the SILP database (Polish State Forest). However, for the evaluation of successful growth per stand, crown density estimations are crucial and can change abruptly in a few growing seasons due to calamities. Only remote sensing methods and geoinformation techniques can assure low-cost and quick data collection over large forest areas and they are crucial when the needed information is reliable enough to provide decision support.
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