Preprints
Filtering by Subject: Computer Sciences
Towards an Open and Integrated Cyberinfrastructure for River Morphology Research in the Big Data Era
Published: 2024-02-16
Subjects: Computer and Systems Architecture, Computer Engineering, Computer Sciences, Databases and Information Systems, Engineering, Environmental Education, Environmental Engineering, Geomorphology, Hydrology, Systems and Communications, Water Resource Management
The objective of this paper is to present the initial illustration of a cyberinfrastructure named the River MORPhology Information System (RIMORPHIS) that addresses the current limitations related to river morphology data and tools. A new specification for data and semantics on river morphology datasets has been developed to support the web-based platform for discovering and visualization of [...]
Unsupervised Structural Damage Assessment from Space using the Segment Anything Model (USDA-SAM): A Case Study of the 2023 Türkiye Earthquake
Published: 2024-01-23
Subjects: Computer Sciences, Earth Sciences, Engineering, Environmental Sciences
This paper explores advanced deep learning methods, specifically utilising the Segment Anything Model (SAM) along with image processing techniques, to evaluate the structural damages caused by the devastating earthquake that occurred in Turkey on February 6, 2023. Leveraging exceptionally high-resolution pre- and post-disaster imagery provided by Maxar Technologies, this paper showcases the [...]
Deep learning with simulated laser scanning data for 3D point cloud classification
Published: 2024-01-17
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Numerical Analysis and Scientific Computing, Other Earth Sciences
Laser scanning is an active remote sensing technique applied in many disciplines to acquire state-of-the-art spatial measurements. Semantic labeling is often necessary to extract information from the raw point cloud. Deep learning methods constitute a data-hungry solution for the semantic segmentation of point clouds. In this work, we investigate the use of simulated laser scanning for training [...]
Wealth over Woe: global biases in hydro-hazard research
Published: 2024-01-12
Subjects: Computer Sciences, Hydrology, Nature and Society Relations, Sustainability
Floods, droughts, and rainfall-induced landslides are hydro-geomorphic hazards that affect millions of people every year. Anticipation, mitigation, and adaptation to these hazards is increasingly outpaced by their changing magnitude and frequency due to climate change. A key question for society is whether the research we pursue has the potential to address knowledge gaps and to reduce potential [...]
Never train an LSTM on a single basin
Published: 2023-12-05
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Hydrology, Physical Sciences and Mathematics
Machine learning (ML) has an increasing role in the hydrological sciences, and in particular, certain types of time series modeling strategies are popular for rainfall-runoff modeling. A large majority of studies that use this type of model do not follow best practices, and there is one mistake in particular that is very common: training deep learning models on small, homogeneous data sets (i.e., [...]
Pygoda: a graphical interface to efficiently visualise and explore large sets of geolocated time series
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 [...]
A Deep Learning framework to map riverbed sand mining budgets in large tropical deltas
Published: 2023-10-20
Subjects: Computer Sciences, Earth Sciences, Environmental Education, Environmental Health and Protection, Environmental Monitoring, Environmental Sciences, Natural Resource Economics, Natural Resources and Conservation, Natural Resources Management and Policy, Other Environmental Sciences, Planetary Geomorphology, Planetary Sedimentology, Sustainability, Water Resource Management
Rapid urbanization has dramatically increased the demand for river sand, leading to soaring sand extraction rates that often exceed natural replenishment in many rivers globally. However, our understanding of the geomorphic and social-ecological impacts arising from Sand Mining (SM) remains limited, primarily due to insufficient data on sand extraction rates. Conventionally, bathymetry surveys [...]
Using convex optimization to efficiently apportion tracer and pollutant sources from point concentration observations
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 [...]
SeisMIC - an Open Source Python Toolset to Compute Velocity Changes from Ambient Seismic Noise
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 [...]
Understanding Drought Awareness from Web Data
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 [...]
Data Cubes for Earth System Research: Challenges Ahead
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 [...]
ChatGPT as a mapping assistant: A novel method to enrich maps with generative AI and content derived from street-level photographs
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 [...]
Calling for a National Model Benchmarking Facility
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 [...]
Mapping glacier basal sliding with machine learning
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 [...]
Residual U-Net with Attention for Detecting Clouds in Satellite Imagery
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 [...]