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Active Measurement
Motivation
- Computational limitations instead of resolution
- Distributed network of observational sensors
ML prediction to scientific insights
Bird Migration
- Weather radars to track birds. They travel at night, we cannot see them but radars are sensitive enough to see them
- Dark Ecology
- Can we extract something from the 25 year archival data?
- Extract birds from the radar data. They were not measuring birds intentionally but they can be extracted form the data
- Plot biomass density vs direction, speed, height
Challenges
- Big data
- Huge number of radars
- Resolution heterogeneity
- Remove weather contamination. It is not a problem other way around (biomass so small compared to weather that they can ignore them but it doesn’t work that way for biomass)
- MistNet. CNN for weather radar
- Produce mask from radar measurement data
- Training data?
- Dual polarization radar helped with this to label
- Rain circular birds not
- After 2013 the sensors does the classification do not need Mistnet
- Spring they move north then they come back later in the year to the south
Monte Carlo Sampling
- Improve variance by importance sampling