JDR Vol.16 No.3 pp. 371-380
doi: 10.20965/jdr.2021.p0371


Applicability of High-Resolution Geospatial Data Obtained by UAV Photogrammetry to Develop Drainage System Models for Pluvial Flood Analysis

Kyuhyun Park*,†, Yoshihiro Shibuo*, Junichi Katayama***, Shinji Baba***, and Hiroaki Furumai**

*Department of Urban Engineering, Graduate School of Engineering, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Corresponding author

**Research Center for Water Environment Technology, School of Engineering, The University of Tokyo, Tokyo, Japan

***Ishigaki Company, Ltd., Tokyo, Japan

September 30, 2020
February 5, 2021
April 1, 2021
pluvial flooding, UAV photogrammetry, high-resolution geospatial data survey, open channel shape survey, suburban area

Integrated flood models have been previously developed to simulate diverse inundation situations and combined with models of storm surges and river floods. However, drainage systems, ground elevation, and surface information of human settlements have only been digitized in large cities. Digitization of surface information is essential for developing a drainage system model for pluvial flood analysis. Occasionally, suburban drainage areas exhibit various complex land-use conditions, including residential and green areas, agricultural land with drainage, and irrigation channels. Herein, UAV photogrammetry was applied to obtain high-resolution geospatial data associated with small-scale flood-prone areas whose elevation, land-use, and waterway networks have not been elucidated sufficiently. The resolution of elevation and land-use data ranged from 2.61–5.22 cm/mesh. The measurement accuracy of the width and depth of the open channels was high, and the errors were mostly within 10%. A drainage system model was developed using data on open channel, elevation, and land-use.

Cite this article as:
Kyuhyun Park, Yoshihiro Shibuo, Junichi Katayama, Shinji Baba, and Hiroaki Furumai, “Applicability of High-Resolution Geospatial Data Obtained by UAV Photogrammetry to Develop Drainage System Models for Pluvial Flood Analysis,” J. Disaster Res., Vol.16, No.3, pp. 371-380, 2021.
Data files:
  1. [1] Z. W. Kundzewicz, “Flood risk and climate change: global and regional perspectives,” Hydrological Sciences J., Vol.59, No.1, pp. 1-28, 2014.
  2. [2] H. Li, S. Wei, C. Cheng, J. Liou, Y. Chen, and K. Yeh, “Applying Risk Analysis to the Disaster Impact of Extreme Typhoon Events Under Climate Change,” J. Disaster Res., Vol.10, No.3, pp. 513-526, 2015.
  3. [3] H. Ozdemir, C. C. Sampson, G. A. M. de Almeida, and P. D. Bates, “Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data,” Hydrol Earth System Science, Vol.17, pp. 4015-4030, 2013.
  4. [4] G. A. M. de Almeida, P. Bates, and H. Ozdemir, “Modelling urban floods at submetre resolution: challenges or opportunities for flood risk management?,” J. of Flood Risk Management, Vol.11, pp. S855-S865, 2016.
  5. [5] S. Amirebrahimi, A. Rajabifard, P. Mendis, and T. Ngo, “A framework for a microscale flood damage assessment and visualization for a building using BIM–GIS integration,” Int. J. of Digital Earth, Vol.9, No.4, pp. 363-386, 2015.
  6. [6] J. L. Dyer, R. J. Moorhead, and L. Hathcock, “Identification and Analysis of Microscale Hydrologic Flood Impacts Using Unmanned Aerial Systems,” Remote Sensing, Vol.12, No.10, Article No.1549, 2020.
  7. [7] H. Sanuki, Y. Shibuo, S. Lee, K. Yoshimura, Y. Tajima, and H. Furumai, “Inundation forecast simulation in urbanized coastal low-lying areas considering multiple flood causing factors,” Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering), Vol.72, No.2, pp. I_517-I_522, 2016 (in Japanese).
  8. [8] V. V. Klemas, “Coastal and environmental remote sensing from unmanned aerial vehicles,” J. of Coastal Research, Vol.31, No.5, pp. 1260-1267, 2015.
  9. [9] A. M. Lechner, A. Fletcher, K. Johansen, and P. Erskine, “Characterising upland swamps using object-based classification methods and hyper-spatial resolution imagery derived from an unmanned aerial vehicle,” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.I-4, pp. 1-6, 2012.
  10. [10] B. Kršák, P. Blišt’an, A. Pauliková, P. Puškárová, L’. Kovanič, J. Palková, and V. Zelizňaková, “Use of low-cost UAV photogrammetry to analyze the accuracy of a digital elevation model in a case study,” Measurement, Vol.91, pp. 276-287, 2016.
  11. [11] “Elevation survey report on Geospatial Information Authority of Japan,” (in Japanese) [accessed October 16, 2019]
  12. [12] D. Niehoff, U. Fritsch, and A. Bronstert, “Land-use impacts on storm-runoff generation: scenarios of land-use change and simulation of hydrological response in a meso-scale catchment in SW-Germany,” J. of Hydrology, Vol.267, pp. 80-93, 2002.
  13. [13] F. López-Granados, J. Torres-Sánchez, A. L. De Castro, A. Serrano-Pérez, F. Mesas-Carrascosa, and J. Peña, “Object-based early monitoring of a grass weed in a grass crop using high resolution UAV imagery,” Agronomy for Sustainable Development, Vol.36, Article No.67, 2016.
  14. [14] Q. Feng, J. Liu, and J. Gong, “Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier – A Case of Yuyao, China,” Water, Vol.7, pp. 1437-1455, 2015.
  15. [15] J. K. S. Villanueva and A. C. Blanco, “Optimization of ground control point (GCP) configuration for unmanned aerial vehicle (UAV) survey using structure from motion (SfM),” The Int. Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.XLII-4/W12, 2019.
  16. [16] Y. Furukawa and J. Ponce, “Accurate, Dense, and Robust Multi-View Stereopsis. Pattern Analysis and Machine Intelligence,” IEEE Trans. on Communications, Vol.32, No.8, pp. 1362-1376, 2019.
  17. [17] S. Yamauchi, K. Ogata, K. Suzuki, and T. Kawashima, “Development of an Accurate Video Shooting Method Using Multiple Drones Automatically Flying over Onuma Quasi-National Park,” J. Robot. Mechatron., Vol.30, No.3, pp. 436-442, 2018.
  18. [18] A. Lucieer, S. M. de Jong, and D. Turner, “Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography,” Progress in Physical Geography, Vol.38, No.1, pp. 97-116, 2014.
  19. [19] M. W. Ewertowski, A. M. Tomczyk, D. J. A. Evans, D. H. Roberts, and W. Ewertowski, “Operational Framework for Rapid, Very-high Resolution Mapping of Glacial Geomorphology Using Low-cost Unmanned Aerial Vehicles and Structure-from-Motion Approach,” Remote Sensing, Vol.11, No.1, pp. 8586-8609, 2019.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 13, 2021