The Effect of Landscape Patterns on the Accuracy of Land Cover Map from Multi-Resolution Remote Sensing Data Classification

The effects of landscape patterns on the accuracy of the remote sensing data classification was statistically analyzed by using the simulated multi-resolution remote sensing data with given landscape patterns The partial least squares regression was used to quantifying the relationship between the 22 landscape indices of class level and patch level, derived from the simulated multi-resolution and the classification accuracy Results from the PLS regression model suggest that eight landscape indices and resolution have negative effect on classification accuracy, fourteen have positive effect. An understanding of the relationships between landscape pattern, scale, and the classification accuracy will advance methods for remote sensing classification and choice of optimal resolution.