Correction of land-cover area estimates from low spatial resolution remotely sensed data

A two stage modeling strategy improves area estimates by correcting coarse-resolution measurements of class proportions. Stage I models use measurements of landscape spatial properties to estimate the slope and intercept of proportion transition relationships. A stage II model uses a regression estimator to predict true class proportions based on measured coarse-scale proportions, and the slope and intercept estimates from the stage I models. Model development and testing on a calibration site is followed by testing and inversion for a validation site. A probabilistic sampling strategy allows statistical assessment of the models and results