The application of high spatial resolution remote sensing image for vegetation type recognition in Dagou Valley

This paper present a detail processing procedure about SPOT5 image applied for vegetation type recognition, and determines the capacity of high spatial resolution satellite image data to discriminate vegetation type in a complex ecosystem. A high spatial resolution SPOT5 image, captured in April 2005, and coincident field data covering the Dagou valley, was used in this analysis. Image geometric rectification and image fusion are then introduced to take prepare for classification. Subsequently, a maximum likelihood classification algorithm was applied to the SPOT5 image data to map the vegetation classes. Field validation and accuracy assessment are crucial to ensure the reliability of classification results. The strategy of field work and the resulting accuracy evaluations were presented, and yielded the high classification accuracy (overall accuracy=83.86%, Kappa=80.23%). The result showed that the information on vegetation types can be mapped effectively from high spatial resolution satellite image data.