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Classification accuracy for stratification with remotely sensed data

Formally Refereed
Authors: Raymond L. Ph.D..Czaplewski, Paul L. Patterson
Year: 2003
Type: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
Source: Forest Science. 49(3): 402-408


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, forest statistics


Czaplewski, Raymond L.; Patterson, Paul L. 2003. Classification accuracy for stratification with remotely sensed data. Forest Science. 49(3): 402-408