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what i wish someone had told me: blog.samaltman.com/what-i-wish-so…

Happy holidays from the Global Ecology Lab! Department of Geographical Sciences BSOS @ UMD UMD Research

🗺️GEOG PhD student Zhihao Wang w/Lei Ma George Hurtt + more unveil "'Deep-ED," an AI-powered ecosystem modeling of forest carbon dynamics with better spatial resolution. Learn more: go.umd.edu/deep-ed-forest…

We're thrilled to announce DeepED, the AI-driven model for Ecosystem Demography (EDv3), part of NASA's CMS and GEDI mission. DeepED transforms ecosystem modeling, enabling advanced, scalable computations and extensive projections, marking a new epoch in global carbon monitoring.

Maryland's Climate Pollution Reduction Plan, including insights from GEOG's George Hurtt + Lei Ma + Quan Shen, outlines strategies to reduce emissions 60% by 2031 and achieve net zero by 2045, w/ MD Environment go.umd.edu/md-climate-pol…

We contributed to the modeling of the forestry and land use sector. We estimated the potential carbon sequestration benefits of various afforestation and reforestation scenarios, along with the associated uncertainties stemming from indeterminate planting locations.

I'm teaching #Bayesian methods in my #DataAnalytics course this week. To support my students, I built this custom #Python dashboard with Matplotlib. Change the prior, likelihood and observed the posterior on #GitHub @ github.com/GeostatsGuy/Py… ∀. #DataScience #Statistics

📢 Tomorrow, March 1 at 1 p.m. EST via Zoom: Learn how Brazil's Imazon uses geospatial intelligence to prevent deforestation in the Amazon, w/ @CMSouzaJr Details here ⤵️ go.umd.edu/preventing-Ama…

Excited to share our latest research on foundation models in remote sensing! We've compared them with traditional ML and deep learning models to see which really performs best for pixel-level classification. doi.org/10.48550/arXiv… Department of Geographical Sciences #remotesensing #foundationalmodel

"Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in M… arxiv.org/abs/1803.02642