Preprints
Filtering by Subject: Theory and Algorithms
Virtual image patch-based cloud removal for Landsat images
Published: 2022-07-31
Subjects: Theory and Algorithms
The inevitable thick cloud contamination in Landsat images has severely limited the usability and applications of these images. Developing cloud removal algorithms has been a hot research topic in recent years. Many previous algorithms used one or multiple cloud-free images in the same area acquired on other dates as reference image(s) to reconstruct missing pixel values. Although it has been [...]
GANSim-3D for conditional geomodelling: theory and field application
Published: 2021-12-23
Subjects: Artificial Intelligence and Robotics, Computational Engineering, Geology, Hydrology, Numerical Analysis and Scientific Computing, Oil, Gas, and Energy, Theory and Algorithms, Water Resource Management
Geomodelling of subsurface reservoirs is important for water resources, hydrocarbon exploitation, and Carbon Capture and Storage (CCS). Traditional geostatistics-based approaches cannot abstract complex geological patterns and are thus not able to simulate very realistic earth models. We present a Generative Adversarial Networks (GANs)-based 3D reservoir simulation framework, GANSim-3D, which can [...]
Data Science for Geoscience: Recent Progress and Future Trends from the Perspective of a Data Life Cycle
Published: 2021-05-04
Subjects: Artificial Intelligence and Robotics, Databases and Information Systems, Earth Sciences, Environmental Sciences, Numerical Analysis and Scientific Computing, Theory and Algorithms
Data science receives increasing attention in a variety of geoscience disciplines and applications. Many successful data-driven geoscience discoveries have been reported recently, and the number of geoinformatics and data science sessions have begun to increase in many geoscience conferences. Across academia, industry, and governmental sectors, there is a strong interest to know more about the [...]
Machine learning and fault rupture: a review
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
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
Published: 2018-10-01
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
Published: 2018-04-20
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
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
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
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.