3 papers
cs.LG2026
Fusing Multi- and Hyperspectral Satellite Data for Harmful Algal Bloom Monitoring with Self-Supervised and Hierarchical Deep Learning
Nicholas LaHaye, Kelly M. Luis, Michelle M. Gierach
We present a self-supervised machine learning framework for detecting and mapping the severity and speciation of harmful algal blooms (HABs) using multi-sensor satellite data. By f…
cs.LG2025
Harnessing Self-Supervised Deep Learning and Geostationary Remote Sensing for Advancing Wildfire and Associated Air Quality Monitoring: Improved Smoke and Fire Front Masking using GOES and TEMPO Radiance Data
Nicholas LaHaye, Thilanka Munashinge, Hugo Lee +4
This work demonstrates the possibilities for improving wildfire and air quality management in the western United States by leveraging the unprecedented hourly data from NASA's TEMP…
cs.CV2025
The View From Space: Navigating Instrumentation Differences with EOFMs
Ryan P. Demilt, Nicholas LaHaye, Karis Tenneson
Earth Observation Foundation Models (EOFMs) have exploded in prevalence as tools for processing the massive volumes of remotely sensed and other earth observation data, and for del…