1 research outputs found
A hybrid approach to land cover classification from multi spectral images
This work is part of a wider project whose general objective is to develop
a methodology for the automatic classification, based on CORINE landcover
(CLC) classes, of high resolution multispectral IKONOS images. The
specific objective of this paper is to describe a new methodology for producing
really exploitable results from automatic classification algorithms. Input data
are basically constituted by multispectral images, integrated with textural and
contextual measures. The output is constituted by an image with each pixel assigned
to one out of 15 classes at the second level of the CLC legend or let unclassified
(somehow a better solution than a classification error), plus a stability
map that helps users to separate the regions classified with high accuracy from
those whose classification result should be verified before being use