Preprints
Filtering by Subject: Artificial Intelligence and Robotics
A Review of Machine Learning in Snow Water Equivalent Monitoring
Published: 2024-05-10
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Databases and Information Systems, Earth Sciences, Hydrology, Numerical Analysis and Scientific Computing, Oceanography and Atmospheric Sciences and Meteorology
In recent years, the scientific community focused on snow dynamics has witnessed a surge in efforts aimed at enhancing Snow Water Equivalent (SWE) monitoring capabilities, largely propelled by the incorporation of Machine Learning (ML) techniques. This comprehensive review delves into the current state of research within this evolving domain, shedding light on the indispensable role of precise [...]
Interpretable Quality Control of Sparsely Distributed Environmental Sensor Networks Using Graph Neural Networks
Published: 2024-05-03
Subjects: Artificial Intelligence and Robotics, Earth Sciences
Environmental sensor networks play a crucial role in monitoring key parameters essential for understanding Earth’s systems. To ensure the reliability and accuracy of collected data, effective quality control (QC) measures are essential. Conventional QC methods struggle to handle the complexity of environmental data. Conversely, advanced techniques such as neural networks, are typically not [...]
Sentinel-1 SAR-based Globally Distributed Landslide Detection by Deep Neural Networks
Published: 2024-04-05
Subjects: Artificial Intelligence and Robotics, Geomorphology
Efficient response to large and widespread multiple landslide events (MLEs) demands rapid and effective landslide detection. Despite extensive efforts using optical remotely sensed imagery, limitations in global, day & night, and all-weather operational capabilities remain. To address these gaps, we introduce an approach that harnesses Deep Neural Networks (DNNs) and Synthetic Aperture Radar [...]
An ensemble neural network approach for space-time landslide predictive modelling
Published: 2024-02-27
Subjects: Artificial Intelligence and Robotics, Geomorphology, Multivariate Analysis
There is an urgent need for accurate and effective Landslide Early Warning Systems (LEWS). Most LEWS are currently based on a single temporally-aggregated measure of rainfall derived from either in-situ measurements or satellite-based rainfall estimates. Relying on a summary metric of precipitation may not capture the complexity of the rainfall signal and its dynamics in space and time in [...]
Using computer vision to detect and segment fire behavior classifications in UAS-captured images
Published: 2024-02-21
Subjects: Artificial Intelligence and Robotics, Forest Management, Natural Resources and Conservation
The widely adaptable capabilities of artificial intelligence, in particular deep learning and computer vision has led to significant research output regarding fire and smoke detection. Previous studies often focus on themes like early fire detection, increased operational awareness, and post-fire assessment. To further test the capabilities of deep learning detection in these scenarios, we [...]
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 [...]
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 [...]