Geospatial Computer Vision and Machine Learning for Large-Scale Earth Observation Data

The 5Vs of big data, volume, value, variety, velocity, and veracity pose immense opportunity and challenges on implementing local and planet-wide solution from Earth observation (EO) data. EO data, residing at the center of various multidisciplinary problems, primarily obtained through satellite imagery, aerial photography, and UAV-based platforms. Understanding Earth Observation data unlocks this immense data source to address planet-scale problems with computer vision and machine learning techniques for geospatial analysis. This workshop introduces current EO data sources, problems, and image-based analysis techniques. The most recent advances in data, models, and open-source analysis ecosystem related to computer vision and deep learning for EO data will be introduced. The tutorial will expose the audience to cutting-edge geospatial foundation models applied to both archived and live satellite data for environmental and climate monitoring