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http://ir.lib.seu.ac.lk/handle/123456789/5601
Title: | UGV application for modelling and forecasting the tidal fluctuation: with reference to coastal strip from Nintavur to Addalaichenai areas of Ampara district, Sri Lanka |
Authors: | Nijamir, Kafoor Thennakoon, T. M. S. P. Herath, H. M. Jayani Rupi |
Keywords: | TFM UGV Forecast Coastal environment RC GPS DEM |
Issue Date: | Jun-2021 |
Publisher: | Faculty of Arts and Culture, South Eastern University of Sri Lanka, University Park, Oluvil. |
Citation: | Kalam, International Research Journal, Faculty of Arts and Culture,14(1), 2021. pp. 23-36. |
Abstract: | Modelling tidal fluctuation with Unmanned Ground Vehicle (UGV) is a groundbreaking idea with an innovative approach which can be applicable to forecast and assess the inundation of coastal lands because of the tidal fluctuations in coastal environment. Albeit the aerial images are utilized for the same purpose, it is an initial step to collect random GPS points of the locations where the aerial survey is not accessible and challengeable. Therefore, this study is to create Tidal Fluctuation Model (TFM) with the remotely-controlled UGV using customized GPS tool which was employed along the study area. The waypoints were automatically collected while the UGV was running along study area. Then, having extracted the elevations from the collected GPS points, contours were created and consequently, Digital Elevation Model (DEM) was generated using Arc GIS 10.4 software. Finally, the prediction was done to show the inundation along the study area relative to the Sea water rise in the ranges viz. 0.5m, 01m, 1.5m, and 02m. Based on the forecasting, the future marine infrastructure developments and other human activities could be proceeded in a sustainable manner considering the inundation and fluctuation ranges. Also, the UGV can further be switched as Robot with the embedding system which could definitely be operated from the long distance to collect the real-time and more accurate data in future. |
URI: | http://ir.lib.seu.ac.lk/handle/123456789/5601 |
ISSN: | 1391-6815 |
Appears in Collections: | Volume 14 Issue 1 |
Files in This Item:
File | Description | Size | Format | |
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3. K2021 (23-36).pdf | 1.05 MB | Adobe PDF | View/Open |
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