Combined GPS Reflected Signal and Visual Imagery for Unsupervised Clustering and Terrain Classification

Abstract

Use of the Global Positioning System (GPS) L-band (1.57542 GHz) surface-reflected signal for remote sensing is a relatively recent development. In the current study, GPS satellite reflected-signal surface reflectivity, computed along the spectral point ground track across an agricultural area, is combined with 1m x 1m orthorectified, grayscale imagery to form a 2-dimensional (2D) space where unsupervised data clustering and classification is performed. Unlike intensity-only (1D) clustering and classification of the visual data, the moisture-sensitive GPS reflected signal allows water features to be readily differentiated from heavy vegetation and cultivated fields. To our knowledge, this study is the first use of the reflected GPS signal in combination with visual imagery for remotely sensed terrain data clustering and classification.