Development of Flood Drain Direction using Mobile GIS and Spatial Interpolation Techniques in Municipality of Khon Kaen, Thailand
DOI:
https://doi.org/10.14456/nujst.2022.22Keywords:
Mobile GIS, Inverse distance weight, Ordinary Kriging, Flood drain direction, Municipality of Khon KaenAbstract
In this paper, techniques for interpolation of spatial elevation from elevation data by using mobile GIS field survey for flood drain direction mapping have been developed which can be served as a guideline for remote sensing and GIS operations to improve the efficiency of flood disaster monitoring and management in the municipality of Khon Kaen, Thailand. In order to estimate the interpolation of spatial elevation for flood direction, five GIS data were used such as satellite imagery, hydrology, road, boundary and elevation. The paper presents the flood drain direction mapping by using DEM data from IDW interpolation technique. The result was shown the flood water direction from Nong Khot lake and flow to Bueng Kaen Nakhon lake and the last flow to Bueng Thung Sang lake, respectively.
References
Ableson, F. (2013). jQuery Mobile and JSON, Learn how to Create Mobile Web Applications Powered by jQuery Mobile. Retrieved from https://www.ibm.com/developerworks/xml/tutorials/x-jquerymobilejsontut/index.html
Achilleos, G. A. (2011). The Inverse Distance Weighted interpolation method and error propagation mechanism – creating DEM from an analogue topographical map. Journal of Spatial Science, 56(2), 283-304.
Choosumrong, S., Raghavan, V., Jeefoo, P., & Vaddadi, N. (2016). Development of Service Orinted Web-GIS Platform for Monitoring and Evaluation using FOSS4G. International Journal of Geoinformatics, 12(3), 67-77.
DMSG, (2001). The Use of Earth Observing Satellites for Hazard Support: Assessments & Scenarios. USA: Final Report, Department of Commerce.
Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford: Oxford University Press.
Haq, M., Akhtar, M., Muhammad, S., Paras, S., & Rahmatullah, J. (2012). Techniques of Remote Sensing and GIS for flood monitoring and damage assessment: A case study of Sindh province, Pakistan. The Egyptian Journal of Remote Sensing and Space Sciences, 15, 135-141.
Hilldale, R. C., & Raff, D. (2008). Assessing the Ability of Airborne LiDAR to Map River Bathymetry. Earth Surface Process and Landforms, 33(5), 773-783.
Kinzel, P. J., Wright, C. W., Nelson, J. M., & Burman, A. R. (2007). Evaluation of an Experimental LiDAR for Surveying a Shallow, Braided, Sand-Bedded River. Journal of Hydraulic Engineering, 133(7), 838-842.
Kourgiala, N., & Karatzas, G. (2011). Flood management and a GIS modelling method to assess flood-hazard areas – a case study. Hydrological Sciences Journal, 56(2), 212-224.
Ly, S., Charles, C., & Degre, A. (2013). Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale. Biotechnology, Agronomy and Society and Environment, 17(2), 392-406.
Merwade, V. M., Maidment, D. R., & Goff, J. A. (2006). Anisotropic Considerations while Interpolating River Channel Bathymetry. Journal of Hydrology, 331(3), 731-741.
Ozkan, S. P., & Tarhan, C. (2015). Detection of Flood Hazard in Urban Areas Using GIS: Izmir Case. Procedia Technology, 22, 373-381.
Pavlova, A. I. (2017). Analysis of Elevation Interpolation Methods for Creating Digital Elevation Models. Optoelectronics, Instrumentation and Data Processing, 53(2), 86-94.
Phillip, G. M., & Watson, D. F. (1982). A precise Method for Determining Contoured Surfaces. The APPEA Journal, 22(1), 205-212.
Wu, C. Y., Mossa, J., Mao, L., & Almulla, M. (2019). Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi River. Annals of GIS, 25(2), 133-151.
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