DSM-based identification of changes in highly dynamic urban agglomerations

Abstract

Rapidly urbanizing areas are challenged by a lack of information on urban growth in many parts of the earth. As the speed of building construction often exceeds traditional surveying methods, remote sensing can serve as a valuable input for the monitoring of urbanization processes. This study investigates changes in DaNang, Vietnam, between 2015 and 2017 identified based on photogrammetric analysis of surface elevations retrieved from Pléiades very high-resolution imagery. In contrast to traditional post-classification change detection approaches, we propose a time-efficient method solely based on digital surface model differencing to identify newly constructed buildings as well as demolitions. It is therefore easy to apply and suitable for the continuation of outdated base data available to local authorities. High importance is addressed to the vertical matching of both surface models to avoid misdetections. After differencing these surface elevations, thresholds based on field measurements are applied to identify areas of change. A total of 10,800 changes were detected between 2015 and 2017, of which 8,531 were to newly constructed buildings. The study proves that changes in rapidly urbanizing agglomerations can be reliably identified by a simple and transparent approach by using elevation changes and expert-based knowledge on floor numbers and building heights.