抄録
It has been shown from recent studies that conventional pixelwise supervised land-use/cover classification methods can not achieve sufficient classification accuracies for high ground resolution image data such as SPOT HRV and Landsat TM. In this paper, a new landcover/use classification algorithm in order to increase classification accuracies for high resolution images is presented.
This algorithm is based upon a two stage recognition model of landcover/use. In this model, each concept of landcover categories is defiend by the component ratio of landcover elements surrounding the corresponding pixel. The classification procedure can be divided into 3 steps ; the first step is the land cover elements recognition of each pixel using a pixelwise classifier; second step is the calculation of the component ratio of each element within local image region ; third step is the final decision for landcover categories using a minimum distance classifier.
The renults of experiments showed that this algorithm achieved about 7% improvements of classification accuracies.