Training Data Errors
A Workshop on “Quantifying Error in Training Data for Mapping and Monitoring the Earth System” was held on January 8-9, 2019 at Clark University, with support from Omidyar Network’s Property Rights Initiative, now PlaceFund. The goals of the workshop were to:
- Summarize the current state of knowledge on the quantification of training data errors and its impacts on machine learning-based methods for generating Earth Observation maps.
- Identify potential sources of error in new training data streams;
- Use case studies to quantify how training data errors impact the usability of downstream maps;
- Define best practices for quantifying and reporting i) training data error and ii) its contribution to overall map error.
The primary workshop outcome will be a peer-review paper (see pre-print here). This site provides additional links to presentations and other resources resulting from the workshop.