Every month we feature one project or paper from members of Climate AI Nordics. New features also go out in our newsletter: join us to receive it, or browse the newsletter archive.
This month’s Climate AI Nordics featured paper is “TopoFlow: topography-aware pollutant Flow learning for high-resolution air quality prediction”. This work introduces a...
Read moreWikimpacts 1.0 is an open-access global database of extreme climate event impacts built by extracting structured data from Wikipedia using large language...
Read moreBoquilaHUB is an open-source desktop application that makes state-of-the-art AI for biodiversity accessible without complex setup or coding. It enables researchers to...
Read moreWhen deploying reinforcement learning-based systems for adaptive control of distributed energy systems often ignore physical limits, such as battery discharge limits, thermal...
Read moreClimate risk is not evenly distributed within cities. Motivated by this, the DEPRIMAP project develops AI and satellite data to identify where...
Read moreWe propose a new open-set recognition dataset, Open-Insect, and evaluate 38 algorithms for new species detection on geographical open-set splits with varying...
Read moreThe new Climate AI Nordics Featured Paper is “Global fields of daily accumulation-mode particle number concentrations using in situ observations, reanalysis data,...
Read moreThe new Climate AI Nordics Featured Paper is “ForestFormer3D: Unified 3D Forest Segmentation from LiDAR”. This work introduces a transformer-based framework for...
Read moreThis study presents an AI-driven inversion framework that uses a deep-learning emulator of a radiative transfer model to estimate snow albedo and...
Read moreThis paper presents a method to continuously detect urban changes in high-resolution satellite image time series (SITS). Traditional urban change detection models...
Read moreThe featured paper this month shows how Bayesian optimisation can support climate change mitigation by tackling optimisation problems in renewable energy and...
Read moreThis paper explores the potential for using neural networks to model atmospheric particle formation. The neural network-based model, tasked here to predict...
Read moreThis study investigates changes in agroforestry tree cover across India between 2010 and 2022 using high-resolution satellite imagery (RapidEye and PlanetScope) and...
Read moreThe AukLab project on Stora Karlsö enhances its AI-driven monitoring of Common Guillemots by adding continuous acoustic recording to its existing camera...
Read moreThis perspective paper discusses several reasons why it is crucial to look at the impact of machine learning (ML) using systems thinking,...
Read moreRead about an exciting project involving both artificial intelligence and an artificial rock shelf!
Read moreThe new Climate AI Nordics Featured Paper is “Deep learning-enhanced detection of road culverts in high-resolution digital elevation models: Improving stream network...
Read moreThe new Climate AI Nordics Featured Paper is “ONEKANA: Modelling Thermal Inequalities in African Cities” by Sabine Vanhuysse and colleagues. This research...
Read moreIn Featured Preprints, preprints from affiliated researchers are summarized and featured at Climate AI Nordics. This one features "Continuous Ensemble Weather Forecasting...
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