Preprints

Filtering by Subject: Theory and Algorithms

Machine learning and fault rupture: a review

Christopher Ren, Claudia Hulbert, Paul Johnson, Bertrand Rouet‐Leduc

Published: 2020-07-02
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geophysics and Seismology, Mathematics, Physical Sciences and Mathematics, Theory and Algorithms

Geophysics has historically been a data-driven field, however in recent years the exponential increase of available data has lead to increased adoption of machine learning techniques and algorithm for analysis, detection and forecasting applications to faulting. This work reviews recent advances in the application of machine learning in the study of fault rupture ranging from the laboratory to [...]

An Ethical Decision-Making Framework with Serious Gaming: Smart Water Case Study on Flooding

Gregory Ewing, Ibrahim Demir

Published: 2020-06-23
Subjects: Artificial Intelligence and Robotics, Civil and Environmental Engineering, Civil Engineering, Computer Sciences, Databases and Information Systems, Engineering, Engineering Education, Environmental Engineering, Hydraulic Engineering, Physical Sciences and Mathematics, Theory and Algorithms

Sensors and control technologies are being deployed extensively in both urban water networks and rural river systems, leading to unprecedented ability to sense and control our water environment. Because these sensor networks and control systems allow for higher resolution monitoring and decision making in both time and space, greater discretization of control will allow for an unprecedented [...]

Quantifying natural delta variability using a multiple-point geostatistics prior uncertainty model

Céline Scheidt, Anjali M. Fernandes, Chris Paola, Jef Caers

Published: 2018-09-30
Subjects: Artificial Intelligence and Robotics, Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Electrical and Computer Engineering, Engineering, Environmental Engineering, Geology, Geomorphology, Other Civil and Environmental Engineering, Other Engineering, Physical Sciences and Mathematics, Sedimentology, Stratigraphy, Theory and Algorithms

We address the question of quantifying uncertainty associated with autogenic pattern variability in a channelized transport system by means of a modern geostatistical method. This question has considerable relevance for practical subsurface applications as well, particularly those related to uncertainty quantification relying on Bayesian approaches. Specifically, we show how the autogenic [...]

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 [...]

Comparison of roving-window and search-window techniques for characterising landscape morphometry

Carlos Henrique Grohmann

Published: 2017-10-31
Subjects: Computer Sciences, Earth Sciences, Geographic Information Sciences, Geography, Geomorphology, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Theory and Algorithms

Neighbourhood analysis in a Geographical Information System (GIS) calculates the value of a given raster cell from the values of its neighboring cells. Common operations include filtering (high-pass, low-pass, etc) and smoothing (mean, mode) of data, operations that can be done by means of roving-windows or search-windows. Digital terrain analysis (or geomorphometry) relies on neighbourhood [...]

r.roughness – a new tool for morphometric analysis in GRASS

Carlos Henrique Grohmann

Published: 2017-10-30
Subjects: Computer Sciences, Earth Sciences, Geographic Information Sciences, Geography, Geomorphology, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Theory and Algorithms

This article briefly describes r.roughness, a shell script written to calculate the surface roughness of raster surfaces. The method is based on Hobson (1972), where roughness is defined as the ratio be- tween surface and plan area of square cells.

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