Climate & Environment
SDSC is dedicated to advancing climate and environmental data science. Our team contributes to innovation through projects focused on climate pattern analysis, deep learning for biodiversity detection, enhanced avalanche forecasting and much more.
Projects
BioAIRad
In Progress
Biodiversity monitoring of the AIrspace with Radars
Climate & Environment
CleaRIS
In Progress
Cleantech Recommendation and Intelligence System
Climate & Environment
Energy & Sustainability
SPI-GreenFjord
In Progress
Climate & Environment
SPI-PAMIR
In Progress
Climate & Environment
Fore[st]cast
In Progress
Nowcast and predict forest condition
Climate & Environment
COPE
In Progress
COnstraints on near-term warming ProjEctions via distributionally robust statistical and machine learning
Climate & Environment
BioDetect
Completed
Deep Learning for Biodiversity Detection and Classification
Climate & Environment
HighFEM
In Progress
High Frequency Earthquake Modelling
Climate & Environment
Inter-Detect
In Progress
Quantifying Plant-Pollinator Interactions Using Computer Vision
Climate & Environment
CHEMSPEC
Completed
Cost-effective chemical speciation monitoring of particulate matter air pollution
Climate & Environment
Chemistry
DNAi
Completed
High throughput eDNA processing using artificial intelligence for ecosystem monitoring
Climate & Environment
PHENO-MINE
Completed
Pheno-Mine: Extracting dynamic ideotypes from seasonal image time series of wheat taken in the field
Climate & Environment
DATSSFLOW
Completed
Data Science and Mass Movement Seismology: Towards the Next Generation of Debris Flow Warning
Climate & Environment
DIMPEO
Completed
Detecting drought impacts on forests in earth observation data
Climate & Environment
SPEED2ZERO
In Progress
Sustainable pathways towards net zero Switzerland
Climate & Environment
EAGLE
In Progress
Enhanced understanding of Alpine mass movements Gathered through machine LEarning
Climate & Environment
ADOPT
In Progress
AI for Detecting Ocean Plastic Pollution with Tracking
Climate & Environment
WATRES
Completed
A Data-Driven approach to estimate WATershed RESponses
Climate & Environment
DeepDown
Completed
Multivariate climate downscaling using deep learning models
Climate & Environment
EXPECTmine
Completed
Mining Toxicity and High Resolution Mass Spectrometry Data for Linking Exposures to Effects
Climate & Environment
CLIMIS4AVAL
Completed
Real-time cleansing of snow and weather data for operational avalanche forecasting
Climate & Environment
AURORA
In Progress
From air pollution sources to mortality
Climate & Environment
DeepCloud
Completed
A data-driven sub-grid parametrization for complex terrain
Climate & Environment
MLTox
Completed
Enhancing toxicological testing through machine learning
Climate & Environment
ArcticNAP
Completed
Arctic climate change: Exploring the Natural Aerosol baseline for improved model Predictions
Climate & Environment
N2O-SSA
In Progress
Combining measurements, modeling and machine learning to improve N2O accounting for sustainable agricultural development in sub-Saharan Africa
Climate & Environment
MACH-Flow
Completed
Machine learning for Swiss river flow estimation
Climate & Environment
4Real
Real-time urban pluvial flood forecasting
Climate & Environment
EXPECT
Completed
EXtending the PrEdiCTability of the Atmosphere over Europe
Climate & Environment
TAPEDA
Completed
Towards Automated Post-Earthquake Damage Assessment
Climate & Environment
DEAPSnow
Completed
Improving snow avalanche forecasting by data-driven automated predictions
Climate & Environment
DATALAKES
Completed
Heterogeneous data platform for operational modelling and forecasting of Swiss lakes
Climate & Environment
CarboSense4D
Completed
Four-dimensional mapping of carbon dioxide using low-cost sensors, atmospheric transport simulations and machine learning
Climate & Environment
DASH
Completed
DAta Science-informed attribution of changes in the Hydrological cycle
Climate & Environment
ACE-DATA
Completed
Delivering Added-value To Antarctica
Climate & Environment
SPEEDMIND
Completed
Improving species biodiversity analyses and citizen science feedback through machine learning
Climate & Environment
Digital Society
Case studies
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