Use of Remote Sensing to Monitor Urbanization of Hanoi City Center
要旨This study developed a method for monitoring urban growth in Hanoi city center using multi-temporal Landsat and ASTER image data for the period 1975 to 2003. A conventional maximum likelihood method was used to classify the surface information in the images. However, validation of the results revealed that a mixed-pixel (mixel) problem significantly reduced the accuracy of the results. In addition, this study applied a vegetation-soil-water (VSW) index to investigate urban change over the same period. However, the use of a VSW index to detect urban change was also associated with several technical problems. We therefore developed a new integrated approach involving a combination of conventional image classification and the VSW index. The final results demonstrated that the new approach was capable of reliably detecting changes in urban land use, with an overall accuracy of approximately 80% for urban area detection upon validation. The findings of this study are likely to contribute meaningfully supporting practical initiatives for monitoring urban change by the city's decision-makers.