Rapid Mapping for Simple Flood Mitigation Using Commercial Drone at Way Galih Village, Lampung, Indonesia

Arif Rohman(1*), Dwi Bayu Prasetya(2)

(1) Geomatic Engineering, Institut Teknologi Sumatera (ITERA) School of Geography, University of Leeds
(2) Regional and City Planning, Institut Teknologi Sumatera (ITERA)
(*) Corresponding Author


The process to alleviate flood risk, especially flood from a river that occurs excessively in Indonesia, requires a new approach. The attempt to reduce the risk along with the development of technology is by utilising commercial drones and rapid mapping methods for mapping flood plain area. With the rapid mapping method, the flood mitigation process in the village area can be done quickly. The activity carried out was to map the location of possible flooding in the Way Galih Village and case analysis to determine the location of the biogas digester together with the village government authority. The results of the study show that the data acquisition process and aerial photo processing can be carried out within one day and the village policymaker can quickly make policies and decisions about where to place the biogas digester.


flood mitigation, rapid mapping, commercial drones, biogas.

Full Text:



Adger, W. N., Huq, S., Brown, K., Conway, D., & Hulme, M. (2003). Adaptation to climate change in the developing world. Progress in Development Studies, 3(3), 179–195. https://doi.org/10.1191/1464993403ps060oa

Aitsi-Selmi, A., Egawa, S., Sasaki, H., Wannous, C., & Murray, V. (2015). The Sendai Framework for Disaster Risk Reduction: Renewing the Global Commitment to People’s Resilience, Health, and Well-being. International Journal of Disaster Risk Science, 6(2), 164–176. https://doi.org/10.1007/s13753-015-0050-9

Assumpção, T. H., Popescu, I., Jonoski, A., & Solomatine, D. P. (2018). Citizen observations contributing to flood modelling: opportunities and challenges. Hydrology and Earth System Sciences, 22(2), 1473–1489. https://doi.org/10.5194/hess-22-1473-2018

CRED. (2015). The Human Cost of Weather Related Disaster 1995-2015. Retrieved from https://www.unisdr.org/2015/docs/climatechange/COP21_WeatherDisastersReport_2015_FINAL.pdf

Djalante, R., Holley, C., Thomalla, F., & Carnegie, M. (2013). Pathways for adaptive and integrated disaster resilience. Natural Hazards, 69(3), 2105–2135. https://doi.org/10.1007/s11069-013-0797-5

dji.com. (2017). Phantom 4. Retrieved from https://www.dji.com/uk/phantom-4/info

Feng, Q., Liu, J., & Gong, J. (2015). Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier—A Case of Yuyao, China. Water . https://doi.org/10.3390/w7041437

Giordan, D., Notti, D., Villa, A., Zucca, F., Calò, F., Pepe, A., … Allasia, P. (2018). Low cost, multiscale and multi-sensor application for flooded area mapping. Natural Hazards and Earth System Sciences, 18(5), 1493–1516. https://doi.org/10.5194/nhess-18-1493-2018

Griffin, G. F. (2014). The Use of Unmanned Aerial Vehicles for Disaster Management. GEOMATICA, 68(4), 265–281. https://doi.org/10.5623/cig2014-402

Smith, L. C. (1998). Satellite remote sensing of river inundation area, stage, and discharge: a review. Hydrological Processes, 11(10), 1427–1439. https://doi.org/10.1002/(SICI)1099-1085(199708)11:10<1427::AID-HYP473>3.0.CO;2-S

Tampubolon, W., & Reinhardt, W. (2015). Uav Data Processing for Rapid Mapping Activities. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-3/W3. Retrieved from https://www.unibw.de/geoinformatik/mitarbeiter/pdf-dateien-tampubolon/isprsarchives-xl-3-w3-371-2015.pdf

UNISDR. (2004). Living With Risk: A Global Review of Disaster Reduction Initiative. (Terry & Jegg, Eds.) (1st ed.). United Nations. https://doi.org/ISBN 92-1-101064-0

UNISDR. (2012). Number of Climate-related DIsaster Around the World (1980-2011). Retrieved from https://www.preventionweb.net/files/20120613_ClimateDisaster1980-2011.pdf

Wahlström, M. (2015). New Sendai Framework Strengthens Focus on Reducing Disaster Risk. International Journal of Disaster Risk Science, 6(2), 200–201. https://doi.org/10.1007/s13753-015-0057-2

Article Metrics

Abstract view(s): 1107 time(s)
HTML: 754 time(s) PDF: 662 time(s)


  • There are currently no refbacks.