Skip to main content
Classification accuracy for stratification with remotely sensed data
Tools are developed that help specify the classification accuracy required from remotely sensed data. These tools are applied during the planning stage of a sample survey that will use poststratification, prestratification with proportional allocation, or double sampling for stratification. Accuracy standards are developed in terms of an “error matrix,” which is familiar to remote sensing specialists. In addition, guidance is provided to determine when new remotely sensed classifications are needed to maintain acceptable levels of statistical precision with stratification.
forest inventory and monitoring
Czaplewski, Raymond L.; Patterson, Paul L. 2003. Classification accuracy for stratification with remotely sensed data. Forest Science. 49(3): 402-408