Our second interpretation of crowd-sourcing is relevant to events such as wildfires, when a single observation of the presence of a fire is strengthened by additional observations from the same or nearby points. Recent work on Twitter reports during emergencies focuses on this interpretation, giving greater weight to a spatial clustering of similar reports than to a single report. In such cases one might devise metrics of quality based on the number of independent but consistent reports.