Preprints
Filtering by Subject: Artificial Intelligence and Robotics
Deep Learning Improves Global Satellite Observations of Ocean Eddy Dynamics
Published: 2024-01-15
Subjects: Artificial Intelligence and Robotics, Fluid Dynamics, Oceanography and Atmospheric Sciences and Meteorology
Ocean eddies affect large-scale circulation and induce a kinetic energy cascade through their non-linear interactions. However, since global observations of eddy dynamics come from satellite altimetry maps that smooth eddies and distort their geometry, the strength of this cascade is underestimated. Here, we use deep learning to improve observational estimates of global surface geostrophic [...]
Open-source approach for reproducible substrate mapping using semantic segmentation on recreation-grade side scan sonar datasets
Published: 2023-12-21
Subjects: Analysis, Artificial Intelligence and Robotics, Databases and Information Systems, Environmental Monitoring, Hydrology, Natural Resources and Conservation, Numerical Analysis and Computation, Numerical Analysis and Scientific Computing, Programming Languages and Compilers, Software Engineering, Terrestrial and Aquatic Ecology, Water Resource Management
Knowledge of the variation and distribution of substrates at large spatial extents in aquatic systems, particularly rivers, is severely lacking, impeding species conservation and ecosystem restoration efforts. Air and space-borne remote sensing important for terrestrial and atmospheric measurements are limited in benthic environments due to river stage, turbidity, and canopy cover, requiring [...]
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., [...]
TROPOMI/S5P sensitivity limits with respect to detection of NO2 plumes from seagoing ships
Published: 2023-09-20
Subjects: Artificial Intelligence and Robotics, Atmospheric Sciences, Environmental Monitoring
The marine shipping industry is among the strong emitters of nitrogen oxides (NOx) -- a substance harmful to ecology and human health. Monitoring of emissions from shipping is a significant societal task. Currently, the only technical possibility to observe NO2 emission from seagoing ships on a global scale is using TROPOMI data. A range of studies reported that NO2 plumes from some individual [...]
A deep learning approach for deriving winter wheat phenology from optical and SAR time series at field level
Published: 2023-07-13
Subjects: Agricultural Science, Agriculture, Artificial Intelligence and Robotics, Environmental Monitoring
Information on crop phenology is essential when aiming to better understand the impacts of climate and climate change, management practices, and environmental conditions on agricultural production. Today’s novel optical and radar satellite data with increasing spatial and temporal resolution provide great opportunities to provide such information. However, so far, we largely lack methods that [...]
An Artificial Neural Network to Estimate the Foliar and Ground Cover Input Variables of the Rangeland Hydrology and Erosion Model
Published: 2023-07-12
Subjects: Artificial Intelligence and Robotics, Environmental Monitoring, Hydrology, Natural Resources and Conservation, Natural Resources Management and Policy, Soil Science
Models like the Rangeland Hydrology and Erosion Model (RHEM) are useful for estimating soil erosion, however, they rely on input parameters that are sometimes difficult or expensive to measure. Specifically, RHEM requires information about foliar and ground cover fractions that generally must be measured in situ, which makes it difficult to use models like RHEM to produce erosion or soil risk [...]
Mitigation effectiveness on groundwater-dependent ecosystems revealed by counterfactual AI
Published: 2023-07-09
Subjects: Artificial Intelligence and Robotics, Environmental Engineering, Hydrology, Sustainability, Water Resource Management
Overexploitation of groundwater threatens groundwater-bound aquatic and terrestrial biodiversity and ecosystem stability, underscoring the need to devise appropriate mitigation strategies. Yet, substantial scientific evidence that mitigation measures effectively protect groundwater ecosystems is presently nonexistent. We provide unique and compelling evidence, using counterfactual artificial [...]
Ten deep learning techniques to address small data problems with remote sensing
Published: 2023-06-09
Subjects: Artificial Intelligence and Robotics, Other Earth Sciences
Researchers and engineers have increasingly used Deep Learning (DL) for a variety of Remote Sensing (RS) tasks. However, data from local observations or via ground truth is often quite limited for training DL models, especially when these models represent key socio-environmental problems, such as the monitoring of extreme, destructive climate events, biodiversity, and sudden changes in ecosystem [...]
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 [...]
Enhancing Flood Risk Assessment Through Machine Learning and Open Data
Published: 2023-06-02
Subjects: Artificial Intelligence and Robotics, Environmental Indicators and Impact Assessment, Environmental Monitoring
Urban flooding causes billions of dollars in damages annually, with severe flood events becoming more frequent and destructive as our climate changes. While extreme weather is a primary driver of flooding, its consequences depend on the interconnectedness of urban systems - referred to as the Urban Multiplex, which includes the power grid, transportation network, natural surface water and [...]
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 [...]
Improving Shoreline Forecasting Models with Multi-Objective Genetic Programming
Published: 2023-01-11
Subjects: Artificial Intelligence and Robotics, Climate, Environmental Engineering, Environmental Monitoring, Geomorphology, Hydrology, Numerical Analysis and Scientific Computing, Oceanography, Sedimentology, Statistical Models
Given the current context of climate change and increasing population densities at coastal zones, there is an increasing need to be able to predict the development of our coasts. Recent advances in artificial intelligence allow for automatic analysis of observational data. This work makes use of Symbolic Regression, a type of Machine Learning algorithm, to evolve interpretable shoreline [...]
Contemporary and historical detection of small lakes using cross-sensor super resolution Landsat imagery
Published: 2022-11-17
Subjects: Artificial Intelligence and Robotics, Environmental Monitoring, Hydrology
Landsat is the longest-running environmental satellite program and has been used for surface water mapping of large water bodies since its launch in 1972. Remote sensing image resolution is increasingly being enhanced through single image super resolution (SR), a machine learning task typically performed by neural networks. Here, we show that a 10x SR model (Enhanced Super Resolution GAN, or [...]
Deep Learning-Based Super-Resolution of Digital Elevation Models in Data Poor Regions.
Published: 2022-10-29
Subjects: Artificial Intelligence and Robotics, Computer Engineering, Geomorphology
In order to develop reliable models, the geoscientific community requires high-resolution data sets. However, the collection of such data is a persistent challenge due to the limitations of resources. The concept of super-resolution, a method from the field of machine learning, can be used to predict a high-resolution version of a low-resolution dataset to improve usability in geoscientific [...]
Plant Breeding Biomolecular Classification in Quantum Bayesianism (QBism) Physics-Informed Neural Network Architecture
Published: 2022-08-31
Subjects: Artificial Intelligence and Robotics, Climate, Other Statistics and Probability, Plant Sciences, Probability, Quantum Physics, Research Methods in Life Sciences, Soil Science, Statistical, Nonlinear, and Soft Matter Physics, Sustainability, Systems Biology
In this brief communication, biomolecular plant breeding multi-classification inference is discussed when leveraging the advantages of Physics-informed Neural Network (PiNN) architecture. Albeit, the expected utility of Partial Differential Equation (PDE) inspired neural networks resides in its performance under limited data availability; a variety of neural network configurations result from PDE [...]