Urban land-cover classification based on airborne hyperspectral data and field observation

Abstract

Using a dataset from the 2013 IEEE data fusion contest, a basic study to classify urban land-cover was carried out. The spectral reflectance characteristics of surface materials were investigated from the airborne hyperspectral (HS) data acquired by CASI-1500 imager over Houston, Texas, USA. The HS data include 144 spectral bands in the visible to near-infrared (380 nm to 1050 nm) regions. A multispectral (MS) image acquired by WorldView-2 satellite was also introduced in order to compare it with the HS image. A field measurement in the Houston’s test site was carried out using a handheld spectroradiometer by the present authors. The reflectance of surface materials obtained by the measurement was also compared with the pseudo-reflectance of the HS data and they showed good agreement. Finally a principal component analysis was conducted for the HS and MS data and the result was discussed.