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DTSTART;TZID=America/Los_Angeles:20241101T090000
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CREATED:20241023T162515Z
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UID:10000266-1730451600-1730455200@ameriflux-new.hyperarts.com
SUMMARY:[FLUXNET-ECN Workshop] AI/Machine Learning for Eddy Covariance Data
DESCRIPTION:We are excited to announce an upcoming FLUXNET-ECN Seminar/Workshop\, a community event co-sponsored by the FLUXNET Early Career Network\, AmeriFlux Management Project (AMP)\, and members of the FLUXNET communities. The workshop focuses on AI and Machine Learning Applications for Eddy Covariance Data. Two featured speakers are Dr. Pamela Weisenhorn and Dr. Benjamin Stocker. \nThis seminar will explore the integration of advanced artificial intelligence (AI) and machine learning (ML) techniques into the analysis of eddy covariance (EC) data. It will also include tutorials based on https://stineb.github.io/ml4ec_workshop/\, which Dr. Stocker developed. A friendly reminder is to walk through the tutorial before the seminar for better learning experiences.  \nRegister for this webinar: https://lbnl.zoom.us/meeting/register/tJckf–uqD8sGtdDYcOVNMqbAkoY9znu4bV_\nDate: Nov.1\, 2024\nTime: 9 AM Pacific Time\, 11 AM US Central Time\, 5 PM Central European Time   \nContact us at:  fluxnet-ecn-owner@fluxdata.org \nHope to see you there! \nBest\,\nXiangmin (Sam) Sun and Bailey Murphy\,\nOn behalf of the FLUXNET-ECN organizing committee
URL:https://ameriflux-new.hyperarts.com/event/fluxnet-ecn-workshop-ai-machine-learning-for-eddy-covariance-data/
LOCATION:virtual
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DTSTART;TZID=America/Los_Angeles:20241107T080000
DTEND;TZID=America/Los_Angeles:20241107T090000
DTSTAMP:20260406T223139
CREATED:20241022T214158Z
LAST-MODIFIED:20241022T214158Z
UID:10000265-1730966400-1730970000@ameriflux-new.hyperarts.com
SUMMARY:Urban Flux Webinar: the Indianapolis Flux Experiment
DESCRIPTION:We are pleased to announce the second webinar of our Urban Flux Community of Practice webinar series\, entitled “The experimental design of the Indianapolis Flux Experiment eddy-covariance flux network.” by Dr. Kenneth J. Davis. This webinar is scheduled to take place on Thursday\, November 7\, 2024\, from 11:00 am to 12:00 pm EST\, 10:00 to 11:00 am CST\, 9:00 to 10:00 am MST\, 8:00 to 9:00 am PST. \nPlease find attached the flyer of this event. \nWebinar Details: \n\nTitle: The experimental design of the Indianapolis Flux Experiment eddy-covariance flux network.\nPresenter: Dr. Kenneth J. Davis\nDate: Thursday\, November 7\, 2024\nTime: 11:00 am to 12:00 pm EST\, 10:00 to 11:00 pm CST\, 9:00 to 10:00 am MST\, 8:00 to 9:00 am PST\n\nAbstract: \nThe National Institute for Standards and Technology (NIST) urban greenhouse gas (GHG) testbeds program has supported research to quantify urban GHG emissions for more than a decade. Most of that research has focused on the joint development of both atmospheric GHG inversions to derive city-wide GHG emissions estimates and research-grade urban GHG emissions inventories. The Indianapolis Flux Experiment (INFLUX) has been working to explore the use of eddy covariance flux measurements for understanding urban GHG budgets. This presentation will review the experimental design of the INFLUX eddy covariance flux measurement network and present examples of how this flux network has advanced our understanding of GHG fluxes in the city of Indianapolis. \nPlease use the following registration link to secure your spot for this webinar: \nhttps://asu.zoom.us/meeting/register/tZMkc-mspzooG9Fj1vruO_9X86wqIAaC0ZX7 \nAfter registering\, you will receive a confirmation email containing information about joining the meeting. \nWe encourage you to share this invitation with colleagues who might be interested in attending this webinar. Feel free to reach out if you have any questions regarding the event or the registration process. \nThank you for your attention\, and we look forward to your participation in this exciting webinar. \nBest regards\, \nUrban Flux Community of Practice
URL:https://ameriflux-new.hyperarts.com/event/urban-flux-webinar-the-indianapolis-flux-experiment/
LOCATION:https://ameriflux-new.hyperarts.com/event/urban-flux-webinar-the-indianapolis-flux-experiment/
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DTSTART;TZID=America/Los_Angeles:20241120T090000
DTEND;TZID=America/Los_Angeles:20241120T103000
DTSTAMP:20260406T223139
CREATED:20241023T162522Z
LAST-MODIFIED:20241023T162522Z
UID:10000267-1732093200-1732098600@ameriflux-new.hyperarts.com
SUMMARY:FLUXNET-ECN Workshop: Knowledge-Guided Machine Learning for Estimating Carbon Fluxes using Eddy Covariance Data: Seminar and Tutorial
DESCRIPTION:We are excited to announce an upcoming FLUXNET-ECN Seminar/Workshop\, a community event co-sponsored by the FLUXNET Early Career Network\, AmeriFlux Management Project (AMP)\, and members of the FLUXNET communities. The workshop focuses on Knowledge-Guided Machine Learning (KGML) for Estimating Carbon Fluxes using Eddy Covariance Data: Seminar and Tutorial. Our invited speaker is Dr. Licheng Liu at the University of Minnesota. \nThis seminar will explore methods to open the ‘black box’ of machine learning by integrating scientific knowledge from mechanism-based models into advanced machine learning frameworks\, known as Knowledge-Guided Machine Learning (KGML). The focus will be on utilizing eddy covariance data for accurate\, efficient\, and interpretable simulations of carbon cycles.  \nTutorials will be provided based on the Nature Communications paper led by Dr. Liu (https://www.nature.com/articles/s41467-023-43860-5)\, along with its associated code. Participants are encouraged to review the paper and try the ‘five_steps_training’ code before the seminar. \nShort Bio:\nDr. Licheng Liu is a senior research scientist leading the KGML division in the AI-CLIMATE Institute at the University of Minnesota. Dr. Liu’s research centers on enhancing our understanding of greenhouse gas (GHG) sources and sinks in agricultural and natural ecosystems\, to explain their roles in climate change and provide actionable insights for mitigation strategies\, by integrating advanced analytical tools such as process-based models and KGML\, multi-source data from modern sensing techniques\, and AI-accelerated optimization algorithms in decision making (https://bbe.umn.edu/people/licheng-liu).  \nRegister for this webinar: https://lbnl.zoom.us/meeting/register/tJAldOugqj4uHNTMDM0L0Hll4E0fRVaEZrJQ
URL:https://ameriflux-new.hyperarts.com/event/fluxnet-ecn-workshop-knowledge-guided-machine-learning-for-estimating-carbon-fluxes-using-eddy-covariance-data-seminar-and-tutorial/
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