Departmental Bulletin Paper 〈Original Papers〉Validating ALOS PRISM DSM-derived surface feature height: Implications for urban volume estimation

ESTOQUE, Ronald C.  ,  MURAYAMA, Yuji  ,  RANAGALAGE, Manjula  ,  HOU, Hao  ,  SUBASINGHE, Shyamantha  ,  GONG, Hao  ,  SIMWANDA, Matamyo  ,  HANDAYANI, Hepi H.  ,  ZHANG, Xinmin

13pp.13 - 22 , 2017-12-22 , University of Tsukuba, Doctoral Program in Geoenvironmental Sciences, Graduate School of Life and Environmental Sciences
Urban volume, such as urban built volume (UBV), can be used as a proxy indicator for measuring the intensity and spatial pattern of urban development, and for characterizing social structure, intensity of economic activity, levels of economic supremacy, and levels of resource consumption. Urban volume estimation requires two basic input data: (1) urban footprint (built footprint for UBV and green footprint for urban green volume (UGV)); and (2) height data for urban features (herein called surface feature height (SFH)). A digital surface model (DSM) and a digital terrain model (DTM) can be used to extract SFH, i.e., by subtracting the DTM from the DSM. Light Detection and Ranging (LiDAR) data are often used to generate DSMs and DTMs. However, the availability of LiDAR data remains limited. The recent release of ALOS World 3D topographic data provides an alternative data source for DSMs and potentially for DTMs. However, the potential of ALOS PRISM DSM for deriving SFH has not been rigorously assessed, especially at the micro level. In this study, we validated six sets of 5 m ALOS PRISM DSM-derived SFH data across six test sites (Tokyo (Japan), Beijing (China), Shanghai (China), Surabaya (Indonesia), Tsukuba (Japan), and Lusaka (Zambia)). We described the grid-based method used to derive a DTM from a DSM and how this method was applied. We then validated the derived SFH data through comparison with recorded building height (RBH) data. Across the six test sites, the root-mean-square error (RMSE) of the ALOS PRISM DSM-derived SFH data ranged from 7 m (Tsukuba) (approximately 2 building floors) to 81 m (Beijing) (approximately 27 building floors). The ALOS PRISM DSM-derived SFH data for lower buildings (e.g., RBH < 100 m) and smaller and less dense cities (Surabaya, Tsukuba and Lusaka) were more accurate than for highrise buildings (e.g. RBH > 100 m) and larger and denser cities (Tokyo, Beijing and Shanghai). Factors that may have influenced the validation results were considered, as were the implications of the findings on urban volume estimation.

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