Abstract
Vertical urban growth in the form of urban volume or building height is increasingly being seen as a significant indicator and constituent of the urban environment. Although high-resolution digital surface models can provide valuable information, various places lack access to such resources. The objective of this study is to explore the feasibility of using open digital surface models (DSMs), such as the AW3D30, ASTER, and SRTM datasets, for extracting digital building height models (DBHs) and comparing their accuracy. A multidirectional processing and slope-dependent filtering approach for DBH extraction was used. Yangon was chosen as the study location since it represents a rapidly developing Asian city where urban changes can be observed during the acquisition period of the aforementioned open DSM datasets (2001–2011). The effect of resolution degradation on the accuracy of the coarse AW3D30 DBH with respect to the high-resolution AW3D5 DBH was also examined. It is concluded that AW3D30 is the most suitable open DSM for DBH generation and for observing buildings taller than 9 m. Furthermore, the AW3D30 DBH, ASTER DBH, and SRTM DBH are suitable for observing vertical changes in urban structures.
Highlights
Urban areas in the 21st century are facing growing challenges from natural and man-made crises
A visual comparison showed that compared with the GeoEye digital building height models (DBHs), the AW3D5 DBH underestimated the height of single-story buildings, which were generally 3–4 m tall, but it better captured the heights of tall structures
Since such locations were not flagged by TanDEM-X’s data consistency mask, it can be assumed that this is due to the local phase unwrapping errors that result in shadows or noise [83]
Summary
Urban areas in the 21st century are facing growing challenges from natural and man-made crises. These include chronic stresses, like environmental pollution and climate change, and acute shocks, like floods and earthquakes. Urban risk assessment maps and appropriate land-use profiles are needed to increase the resilience of our cities to these disasters [1]. Digital building heights have several applications, such as modeling urban expansion [5], extracting and reconstructing buildings [6], simulating air pollution dispersion [7], estimating energy consumption [8] and solar potential [9], observing heat islands [10], flood hazard zoning [11], assessing GPS performance [12], and many others. If building heights from different time periods are available, they can provide information about policy effects on horizontal and vertical urban growth [3,4,13]
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