Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep ...

Learn how to use Jupyter Notebooks for interactive data analysis and visualization. Why is this important? Jupyter Notebooks allow for interactive data exploration, code execution, and visualization ...

Welcome to CS 309. This is an intensive research course that spans one year. Our program aims to produce original research that we can publish. Here are our core beliefs: We believe in self-directed ...

Artificial intelligence is rapidly transforming many sectors of the economy, and engineering is not immune. AI applied to the environmental engineering space, especially with geospatial analysis and ...

License: The code in this repository is licensed under the Apache License, Version 2.0. Digital Earth Africa data is licensed under the Creative Commons by Attribution 4.0 license. Contact: If you ...

Abstract: Jupyter notebooks have become central in data science, integrating code, text and output in a flexible environment. With the rise of machine learning (ML), notebooks are increasingly used ...

This Futures Lab series uses big data and geospatial analysis to uncover how authoritarian states and non-state actors carryout gray zone operations, and explores how innovative analytic methods can ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

Abstract: Ground Penetrating Radar (GPR) data processing is often performed using proprietary, GUI-based software that lacks flexibility for automation, customization, specialization, and integration ...