Using an unsupervised approach of Probabilistic Neural Network (PNN) for land use classification from multitemporal satellite images

摘要

The aim of this work is to develop an unsupervised approach based on Probabilistic Neural Network (PNN) for land use classification. A time series of high spatial resolution acquired by LANDSAT and SPOT images has been used to firstly generate the profiles of Normalized Difference Vegetation Index (NDVI) and then used for the classification procedure.