An application of multiple space nearest neighbor classifier in land cover classification

Abstract

This work presents a case study in land cover classification using ms-NN, an extension of k-NN classification algorithm. The case study focuses on an area in the Brazilian Amazon region, with data obtained from LANDSAT5 satellite Thematic Mapper (TM) sensor and Advanced Land Observing System satellite (ALOS) Phase Array L-Band Synthetic Aperture Radar (PALSAR), using Fine Beam Dual. The results obtained with ms-NN are compared with k-NN and Support Vector Machine algorithms, considering the use of a single training set, a Monte Carlo procedure for testing and an extensive number of parameterizations for the classification methods. Considering only the best results for each classifier, ms-NN obtained better results than the other methods.Index Termsland cover classification, multiple space nearest neighbor, classification algorithm, SAR and optical data classification.