Efficient segmentation of urban areas by the VIBI

Abstract

Urban populations are expanding rapidly and so are cities. Remote sensing offers a convenient means of monitoring this expansion as it covers a period of 40 years in the case of the LANDSAT satellite. In some parts of the globe, this is probably the only viable means of monitoring due to the lack of other types of data. In order to monitor expansion, first, urban land has to be separated from other land-cover types. Although this can be done by standard classification processes, it is much more efficient to establish an urban index (UI) analogous to the widely used normalized difference vegetation index (NDVI) for vegetation. Existing efforts to establish such a UI are reviewed and compared in a common context. Following this, a novel, more efficient UI is introduced. The calculation of the new index is straightforward, based on combining the NDVI with the normalized difference built-up index. The results are promising as the index can efficiently segment urban areas, even in the presence of excessive bare land. The proposed method is evaluated on two test sites selected in different LANDSAT scenes. The new index is valid only for sensors with the same bands as those of LANDSAT.