THE CAPABILITIES OF UNMANNED AERIAL VEHICLE FOR SLOPE CLASSIFICATION

Mokhtar, N. M.; Darwin, N.; Ariff, M. F. M.; Majid, Z.; Idris, K. M.

Slope classification mapping is an important component of land suitability analysis for preventing landslides. This study aim to investigate the capabilities and application of Unmanned Aerial Vehicle (UAV) platform for slope classification. The objectives of this study such as investigating the capabilities of UAV for slope classification, generating Digital Elevation Model (DEM) and orthophoto from the image acquired and assessing the accuracy of DEM and orthophoto produced for slope classification. In this study, the aerial image was acquired using UAV at 60 m and 40 m altitude will then generates the DEM and orthophoto used to produce the slope map and classify the slope. The UAV data was validated with the check points observed from ground survey using GPS to obtain the Root Mean Square Error (RMSE) values. The RMSE value for UAV derived DEM at 60 m altitude is ±0.234 m and ±0.604 m for X and Y respectively. The average RMSE is ±0.279 m. The average RMSE value obtained from LiDAR derived DEM in previous research is ±0.616 m. The RMSE value for UAV derived DEM at 40 m altitude is ±0.596 m and ±0.405 for X and Y respectively. The average RMSE is ±0.334 m. The average RMSE value obtained from LiDAR derived DEM in previous research is ±0.450 m. In conclusion, it shows that the RMSE value obtained from UAV derived DEM is smaller than the RMSE value obtained from LiDAR derived DEM. Hence, UAV is capable for the generation of slope map and slope classification.

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Zitierform:

Mokhtar, N. M. / Darwin, N. / Ariff, M. F. M. / et al: THE CAPABILITIES OF UNMANNED AERIAL VEHICLE FOR SLOPE CLASSIFICATION. 2019. Copernicus Publications.

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Rechteinhaber: N. M. Mokhtar et al.

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