Preprints

Filtering by Subject: Categorical Data Analysis

Pygoda: a graphical interface to efficiently visualise and explore large sets of geolocated time series

Yann Ziegler, Jonathan L. Bamber

Published: 2023-10-24
Subjects: Categorical Data Analysis, Climate, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Monitoring, Environmental Sciences, Environmental Studies, Fresh Water Studies, Geographic Information Sciences, Geophysics and Seismology, Glaciology, Graphics and Human Computer Interfaces, Hydrology, Longitudinal Data Analysis and Time Series, Meteorology, Other Earth Sciences, Other Statistics and Probability, Spatial Science

Modern-day data sets in geosciences may comprise hundreds or thousands of geolocated time series. Despite all the automated tools and new algorithms now available to process and prepare those data before using them in research projects, it can be useful or even necessary to visualise and investigate them manually. Whether it be for data quality assessment, for the preparation of a training data [...]

Köppen meets Neural Network: Revision of the Köppen Climate Classification by Neural Networks

Ji Luo

Published: 2022-08-23
Subjects: Artificial Intelligence and Robotics, Categorical Data Analysis, Climate, Earth Sciences, Ecology and Evolutionary Biology, Environmental Indicators and Impact Assessment, Environmental Monitoring, Multivariate Analysis

Climate change and development of data-oriented methods are appealing for new climate classification schemes. Based on the most widely used Köppen-Geiger scheme, this article proposes a neural network based climate classification method from a data science perspective. In conventional schemes, empirically handcrafted rules are used to divide climate data into climate types, resulting in certain [...]

Spatial association between regionalizations using the information-theoretical V-measure

Jakub Nowosad, Tomasz Stepinski

Published: 2018-04-19
Subjects: Categorical Data Analysis, Computer Sciences, Environmental Sciences, Geographic Information Sciences, Geography, Numerical Analysis and Scientific Computing, Physical Sciences and Mathematics, Social and Behavioral Sciences, Statistics and Probability, Theory and Algorithms

There is a keen interest in inferring spatial associations between different variables spanning the same study area. We present a method for quantitative assessment of such associations in the case where spatial variables are either in the form of regionalizations or in the form of thematic maps. The proposed index of spatial association – called the V-measure – is adapted from a measure [...]

Global assessment and mapping of changes in mesoscale landscapes: 1992–2015

Jakub Nowosad, Tomasz Stepinski, Pawel Netzel

Published: 2018-02-16
Subjects: Categorical Data Analysis, Computer Sciences, Earth Sciences, Environmental Sciences, Geographic Information Sciences, Geography, Longitudinal Data Analysis and Time Series, Numerical Analysis and Scientific Computing, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Statistics and Probability

Monitoring global land cover changes is important because of concerns about their impact on environment and climate. The release by the European Space Agency (ESA) of a set of worldwide annual land cover maps covering the 1992–2015 period makes possible a quantitative assessment of land change on the global scale. While ESA land cover mapping effort was motivated by the need to better [...]

Towards machine ecoregionalization of Earth’s landmass using pattern segmentation method

Jakub Nowosad, Tomasz Stepinski

Published: 2018-02-16
Subjects: Categorical Data Analysis, Computer Sciences, Earth Sciences, Environmental Sciences, Geographic Information Sciences, Geography, Numerical Analysis and Scientific Computing, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Statistics and Probability

We present and evaluate a quantitative method for delineation of ecophysigraphic regions throughout the entire terrestrial landmass. The method uses the new pattern-based segmentation technique which attempts to emulate the qualitative, weight-of-evidence approach to a delineation of ecoregions in a computer code. An ecophysiographic region is characterized by homogeneous physiography defined by [...]

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