Search Results - "Environmental Data Science"

Why we need to focus on developing ethical, responsible, and trustworthy artificial intelligence approaches for environmental science by McGovern, Amy, Ebert-Uphoff, Imme, Gagne, David John, Bostrom, Ann

“…Abstract Given the growing use of Artificial intelligence (AI) and machine learning (ML) methods across all aspects of environmental sciences, it is imperative…”
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Neural network attribution methods for problems in geoscience: A novel synthetic benchmark dataset by Mamalakis, Antonios, Ebert-Uphoff, Imme, Barnes, Elizabeth A.

“…Abstract Despite the increasingly successful application of neural networks to many problems in the geosciences, their complex and nonlinear structure makes…”
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Machine Learning for Smart and Energy-Efficient Buildings by Das, Hari Prasanna, Lin, Yu-Wen, Agwan, Utkarsha, Spangher, Lucas, Devonport, Alex, Yang, Yu, Drgoňa, Ján, Chong, Adrian, Schiavon, Stefano, Spanos, Costas J.

“…Abstract Energy consumption in buildings, both residential and commercial, accounts for approximately 40% of all energy usage in the United States, and similar…”
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Graph characterization of higher-order structure in atmospheric chemical reaction mechanisms by Silva, Sam J., Halappanavar, Mahantesh M.

“…Abstract Atmospheric chemical reactions play an important role in air quality and climate change. While the structure and dynamics of individual chemical…”
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Extreme heat wave sampling and prediction with analog Markov chain and comparisons with deep learning by Miloshevich, George, Lucente, Dario, Yiou, Pascal, Bouchet, Freddy

“…Abstract We present a data-driven emulator, a stochastic weather generator (SWG), suitable for estimating probabilities of prolonged heat waves in France and…”
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Unsupervised clustering identifies thermohaline staircases in the Canada Basin of the Arctic Ocean by Schee, Mikhail G., Rosenblum, Erica, Lilly, Jonathan M., Grisouard, Nicolas

“…Abstract Thermohaline staircases are a widespread stratification feature that impacts the vertical transport of heat and nutrients and are consistently…”
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Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention by Lepioufle, Jean-Marie, Schneider, Philipp, Hamer, Paul David, Ødegård, Rune Åvar, Vallejo, Islen, Cao, Tuan Vu, Taherkordi, Amir, Wojcikowski, Marek

“…Abstract In environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical…”
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Bayesian state-space synthetic control method for deforestation baseline estimation for forest carbon credits by Takahata, Keisuke, Suetsugu, Hiroshi, Fukaya, Keiichi, Shirota, Shinichiro

“…Abstract Carbon credits from the reducing emissions from deforestation and degradation (REDD+) projects have been criticized for issuing junk carbon credits…”
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Domain adaptation with transfer learning for pasture digital twins by Pylianidis, Christos, Kallenberg, Michiel G.J., Athanasiadis, Ioannis N.

“…Abstract Domain adaptation is important in agriculture because agricultural systems have their own individual characteristics. Applying the same treatment…”
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FloodGNN-GRU: a spatio-temporal graph neural network for flood prediction by Kazadi, Arnold, Doss-Gollin, James, Sebastian, Antonia, Silva, Arlei

“…Abstract Classical approaches for flood prediction apply numerical methods for the solution of partial differential equations that capture the physics of…”
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Broadening participation in environmental data science: Insights from practitioners by Caitlin R. Fong, Carmen Galaz García, Emman Abbasi, Nick Gubbins, Zeynab Jouzi

“…Environmental data science (EDS) is a nascent STEM sub-discipline where we have the opportunity to shape the culture, to work to create an environment that…”
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Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning by Novitasari, Maria Carolina, Quaas, Johannes, Rodrigues, Miguel R. D.

“…Abstract Precipitation is one of the most relevant weather and climate processes. Its formation rate is sensitive to perturbations such as by the interactions…”
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An explainable multi-agent recommendation system for energy-efficient decision support in smart homes by Zharova, Alona, Boer, Annika, Knoblauch, Julia, Schewina, Kai Ingo, Vihs, Jana

“…Abstract Transparent, understandable, and persuasive recommendations support the electricity consumers’ behavioral change to tackle the energy efficiency…”
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Understanding precipitation changes through unsupervised machine learning by Mooers, Griffin, Beucler, Tom, Pritchard, Mike, Mandt, Stephan

“…Abstract Despite the importance of quantifying how the spatial patterns of heavy precipitation will change with warming, we lack tools to objectively analyze…”
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Multi-Modal Learning-based Reconstruction of High-Resolution Spatial Wind Speed Fields by Zambra, Matteo, Farrugia, Nicolas, Cazau, Dorian, Gensse, Alexandre, Fablet, Ronan

“…Wind speed at sea surface is a key quantity for a variety of scientific applications and human activities. Due to the non-linearity of the phenomenon, a…”
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Identifying compound weather drivers of forest biomass loss with generative deep learning by Anand, Mohit, Bohn, Friedrich J., Camps-Valls, Gustau, Fischer, Rico, Huth, Andreas, Sweet, Lily-belle, Zscheischler, Jakob

“…Abstract Globally, forests are net carbon sinks that partly mitigates anthropogenic climate change. However, there is evidence of increasing weather-induced…”
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Aerosol optical depth disaggregation: toward global aerosol vertical profiles by Shahine Bouabid, Duncan Watson-Parris, Sofija Stefanović, Athanasios Nenes, Dino Sejdinovic

“…Aerosol-cloud interactions constitute the largest source of uncertainty in assessments of anthropogenic climate change. This uncertainty arises in part from…”
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Ideology from topic mixture statistics: inference method and example application to carbon tax public opinion by Puelma Touzel, Maximilian, Lachapelle, Erick

“…Abstract Political opposition to fiscal climate policy, such as a carbon tax, typically appeals to fiscal conservative ideology. Here, we ask to what extent…”
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A content analysis: analyzing topics of conversation under the #sustainability hashtag on Twitter by Gerber, Aydan

“…Abstract This study aimed to identify and understand the major topics of discussion under the #sustainability hashtag on Twitter (now known as “X”) and…”
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Extreme heatwave sampling and prediction with analog Markov chain and comparisons with deep learning by Miloshevich, George, Lucente, Dario, Yiou, Pascal, Bouchet, Freddy

“…We present a data-driven emulator, a stochastic weather generator (SWG), suitable for estimating probabilities of prolonged heatwaves in France and…”
Get full text