The Effect of Four New Multispectral Bands of Worldview2 on Improving Urban Land Cover Classification

Conventional VHR imagery provides four multispectral (MS) bands. Built-up and traffic areas, however, are spectrally too similar to be distinguished using exclusively the spectral information of VHR imagery. The recently available WorldView2 (WV2) imagery introduces four new MS bands in addition to the four standard MS bands. This rich amount of spectral information together with the very high spatial resolution of WV2 imagery provides the potential for more robust and accurate discrimination between impervious land cover types. This paper aims to explore the contribution of the four newly added MS bands of WV2 imagery to increasing the class-pair separability of urban impervious land covers and consequently classification accuracy. For this, several object-based spectral and textural features of two data sets are extracted. The first data set consist of four standard MS bands, while the second one includes all eight MS bands of WV2. Then, a class-pair separability analysis is conducted to assess the contribution of new bands in discriminating different classes. Finally, the image is classified using each set of data separately. The effect of four new bands on land cover classification is evaluated by accuracy assessment of the results. Results demonstrate that the new four bands of WV increase the overall accuracy by 21.5 %. However, it is found that these new four bands will not have a significant effect on classification accuracy if additional textural and, specially, spectral feature of segmented image are utilized in the classification process.