Kalman filter to update forest cover estimates

Abstract

The Kalman filter is a statistical estimator that combines a time-series of independent estimates, using a prediction model that describes expected changes in the state of a system over time. An expensive inventory can be updated using model predictions that are adjusted with more recent, but less expensive and precise, monitoring data. The concepts of the Kalman filter are explained with a simple, hypothetical example of estimating percentage of forest cover over time, using remote sensing and field plots from a forest inventory.

Parent Publication

• State-of-the-art methodology of forest inventory: a symposium proceedings.

Citation

Czaplewski, Raymond L. 1990. Kalman filter to update forest cover estimates. In: LaBau, Vernon J.; Cunia, Tiberius, technical editors. State-of-the-art methodology of forest inventory: a symposium proceedings. Gen. Tech. Rep. PNW-GTR-263. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 457-465.