Filtering by Subject: Computer Sciences
Published: 2023-09-05
Subjects: Computer Sciences, Earth Sciences, Environmental Sciences, Mathematics
Rivers transport elements, minerals, chemicals, and pollutants produced in their upstream basins. A sample from a river is a mixture of all of its upstream sources, making it challenging to pinpoint the contribution from each individual source. Here, we show how a nested sample design and convex optimization can be used to efficiently unmix downstream samples of a well-mixed, conservative tracer [...]
Published: 2023-09-01
Subjects: Computer Sciences, Earth Sciences, Environmental Monitoring, Environmental Sciences, Geophysics and Seismology, Physical Sciences and Mathematics
We present SeisMIC, a fast, versatile, and adaptable open-source software to estimate seismic velocity changes from ambient seismic noise. SeisMIC includes a broad set of tools and functions to facilitate end-to-end processing of ambient noise data, from data retrieval and raw data analysis via spectrogram computation, over waveform coherence analysis, to post-processing of the final velocity [...]
Published: 2023-08-17
Subjects: Computer Sciences, Earth Sciences, Mathematics, Oceanography and Atmospheric Sciences and Meteorology, Statistics and Probability
We used computer vision (U-Net) model to leverage Standardized Precipitation Evapotranspiration Index (SPEI), Google Trends Search Interest (SI), and Twitter data to understand patterns with which people in Continental United States (CONUS) indicate awareness of and interest in droughts. We found significant statistical relationships between the occurrence of meteorological droughts (MD), as [...]
Published: 2023-07-11
Subjects: Computer Sciences, Earth Sciences, Environmental Sciences
Progress in Earth system science is accelerating rapidly, due to the increasing availability of multivariate datasets, often global, with moderate to high spatio-temporal resolutions. Turning these data into knowledge presents interoperability, technical, analytical, and other challenges. Earth System Data Cubes (ESDCs) have surfaced as essential tools, offering analysis-ready, cloud-optimised [...]
Published: 2023-06-06
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Geographic Information Sciences, Geography, Other Computer Sciences, Other Geography, Spatial Science
This paper explores the concept of leveraging generative AI as a mapping assistant for enhancing the efficiency of collaborative mapping. We present results of an experiment that combines multiple sources of volunteered geographic information (VGI) and large language models (LLMs). Three analysts described the content of crowdsourced Mapillary street-level photographs taken along roads in a small [...]
Published: 2023-04-14
Subjects: Biology, Computer Sciences, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Life Sciences, Oceanography and Atmospheric Sciences and Meteorology, Other Life Sciences, Physical and Environmental Geography, Physical Sciences and Mathematics, Planetary Sciences, Systems Biology
The modern world uses predictive computer models for many important purposes, including weather predictions, epidemic management, flood forecasting and warnings, and economic policymaking. We need to know how much we can trust the projections of these models, not only to achieve more accurate projections for systems, but also to undertake scientific learning about systems by incrementally testing [...]
Published: 2023-01-13
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geophysics and Seismology
During the RESOLVE project ("High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research"), continuous surface displacement and seismic array observations were obtained on Glacier d'Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic [...]
Published: 2023-01-13
Subjects: Computer Sciences, Earth Sciences, Physical Sciences and Mathematics
Semantic segmentation of clouds in Earth observation imagery is an important task in a variety of remote sensing contexts: from the application of atmospheric corrections to being able to accurately omit cloud pixels when extracting information about ground features. Here we introduce a deep learning approach based on the popular U-Net architecture. The core of the architecture is an U-Net with [...]
Published: 2022-11-17
Subjects: Computer Sciences, Earth Sciences, Environmental Sciences, Physical Sciences and Mathematics, Statistics and Probability
Errors, gaps and outliers complicate and sometimes invalidate the analysis of time series. While most fields have developed their own strategy to clean the raw data, no generic procedure has been promoted to standardize the pre-processing. This lack of harmonization makes the inter-comparison of studies difficult, and leads to screening methods that can be arbitrary or case-specific. This study [...]
Published: 2022-09-24
Subjects: Computer Sciences, Earth Sciences, Physical Sciences and Mathematics
Accurately characterizing clouds and their shadows is a long-standing problem in the Earth Observation community. Recent works showcase the necessity to improve cloud detection methods for imagery acquired by the Sentinel-2 satellites. However, the lack of consensus and transparency in existing reference datasets hampers the benchmarking of current cloud detection methods. Exploiting the [...]
Published: 2022-08-31
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Other Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Sustainability
We introduce a method for long-distance maritime route planning in polar regions, taking into account complex changing environmental conditions. The method allows the construction of optimised routes, describing the three main stages of the process: discrete modelling of the environmental conditions using a non-uniform mesh, the construction of mesh-optimal paths, and path smoothing. In order to [...]
Published: 2022-06-02
Subjects: Applied Statistics, Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geomorphology, Physical Sciences and Mathematics, Statistics and Probability
For decades, a full numerical description of the spatio-temporal dynamics of a landslide could be achieved only via physics-based models. The part of the geomorphology community focusing on data-driven model has instead focused on predicting where landslides may occur via susceptibility models. Moreover, they have estimated when landslides may occur via models that belong to the [...]
Published: 2022-04-20
Subjects: Computer Sciences, Earth Sciences, Engineering, Environmental Sciences
Most deep learning application studies have limited accessibility and reproducibility for researchers and students in many domains, especially in earth and climate sciences. In order to provide a step towards improving accessibility to deep learning models in such disciplines, this study presents a community-driven framework and repository, EarthAIHub, that is powered by TensorFlow.js, where deep [...]
Published: 2022-04-01
Subjects: Applied Mathematics, Computer Sciences, Earth Sciences, Mathematics
Time-dependent ground deformation is a key observable in active magmatic systems, but is challenging to characterize. Here we present a numerical framework for modeling transient deformation and stress around a subsurface, spheroidal pressurized magma reservoir within a viscoelastic half-space with variable material coefficients, utilizing a high-order finite-element method and explicit [...]
Published: 2022-03-28
Subjects: Computer Sciences, Earth Sciences, Environmental Sciences, Higher Education
Reproducible research is often perceived as a technological challenge, but it is rooted in the challenge to improve scholarly communication in an age of digitisation. When computers become involved and researchers want to allow other scientists to inspect, understand, evaluate, and build upon their work, they need to create a research compendium that includes the code, data, computing [...]