Abstract
Sustainable development makes light detection and ranging (LiDAR) as an accurate technology in providing the accurate data sources for deriving digital terrain model (DTM) and digital elevation model (DEM). This study is focusing on accuracy assessment of generated LiDAR DEM based on different interpolation techniques in GIS environment. In the beginning, LiDAR point clouds were used to generate DEM surface based upon three different interpolation methods: (i) inverse distance weighting (IDW), (ii) Kriging and (iii) Spline. Next, 31 ground control points (GCP) from global positioning system (GPS) observation were used to perform accuracy assessment of LiDAR DEM that generate through IDW, Kriging and Spline interpolation techniques. As result, LiDAR data used in this study met the requirement of LiDAR accuracy with root mean square error (RMSE) below 0.3m. The finding reveals that the overall RMSE (x, y) for IDW, Kriging and Spline methods is between 0.0124 and 0.1120 m. Besides, the RMSE (z) for Kriging stated the smallest value of 0.2135 m, followed by Spline with values of 0.2141 m. Concurrently, IDW techniques gave the highest RMSE (z) value with 0.2276 m. In conclusion, Kriging interpolation technique has been proved as the best methods which gave the highest accuracy of LiDAR-derived DEM compared to other interpolation methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Amante CJ (2012) Accuracy of interpolated bathymetric digital elevation models. Geography Graduate Theses & Di
Asal FF (2016) Evaluating the effects of reductions in lidar data on the visual and statistical characteristics of the created digital elevation models, pp 12–19, 2016. https://doi.org/10.5194/isprsannals-III-2-91-2016
Ashraf I, Hur S, Park Y (2017) An investigation of interpolation techniques to generate 2D intensity image from LIDAR data 3536(c). https://doi.org/10.1109/ACCESS.2017.2699686
Bater CW, Coops NC (2009) Evaluating error associated with lidar-derived DEM interpolation. Comput Geosci 35:289–300. https://doi.org/10.1016/j.cageo.2008.09.001
Brovelli MA, Cannata M (2004) LIDAR data filtering and DTM interpolation within GRASS 8(2):155–174
Darboux F, Huang C (2003) An instantaneous-profile laser scanner to measure soil surface microtopography. Soil Sci Soc Am J 67(1):92. https://doi.org/10.2136/sssaj2003.9200
Faux RN, Buffington JM, Whitley MG, Lanigan SH, Roper BB (2009) Use of airborne near-infrared LiDAR for determining channel cross-section characteristics and monitoring aquatic habitat in Pacific northwest rivers: a preliminary analysis. In: PNAMP special publication: remote sensing applications for aquatic resource monitoring. Pacific Northwest Aquatic Monitoring partnership, Cook, WA, pp 43–60
Gallay M, Lloyd CD, McKinley J, Barry L (2013) Assessing modern ground survey methods and airborne laser scanning for digital terrain modelling: a case study from the Lake District, England. Comput Geosci 216–227. https://doi.org/10.1016/j.cageo.2012.08.015
Garófano-Gómez V, Martínez-Capel F, Peredo-Parada M, Marín EJO, Mas RM, Costa RMS, Pinar-Arenas JL (2011) Assessing hydromorphological and floristic patterns along a regulated Mediterranean river: The Serpis River (Spain). Limnetica 30(2):307–328. https://doi.org/10.1002/rra
Guo Q, Li W, Yu H, Alvarez O (2010) Effects of topographic variability and lidar sampling density on several DEM interpolation methods. Photogramm Eng Remote Sens 76(6):701–712. https://doi.org/10.14358/PERS.76.6.701
Hodgson ME, Jensen J, Raber G, Tullis J, Davis BA, Thompson G, Schuckman K (2005) An evaluation of lidar-derived elevation and terrain slope in leaf-off conditions. Photogramm Eng Remote Sens 71(7):817–823. https://doi.org/10.14358/pers.71.7.817
Idris R, Latif ZA, Jaafar J, Rani NM, Yunus F (2012) Quantitative assessment of LiDAR dataset for topographic maps revision. In: International conference on system engineering and technology (ICSET 2012), pp 1–4. https://doi.org/10.1109/icsengt.2012.6339288
Ikechukwu MN, Ebinne E, Idorenyin U, Raphael NI (2017) Accuracy assessment and comparative analysis of IDW, Spline and Kriging in Spatial interpolation of landform (topography): an experimental study. J Geogr Inf Syst 9:354–371. https://doi.org/10.4236/jgis.2017.93022
Ismail Z, Jaafar J (2013) DEM derived from photogrammetric generated DSM using morphological filter. In: Proceedings—2013 IEEE 4th control and system graduate research colloquium, ICSGRC 2013, pp 103–106. https://doi.org/10.1109/ICSGRC.2013.6653284
Ismail Z, Khanan MFA, Omar FZ, Rahman MZA, Salleh MRM (2016) Evaluating error of lidar derived dem interpolation for vegetation area, XLII(October):3–5. https://doi.org/10.5194/isprs-archives-XLII-4-W1-141-2016
Liu X, Zhang Z (2007) The effect of LiDAR data density on DEM accuracy. In: International congress on modelling and simulation (MODSIM07), pp 1363–1369. http://eprints.usq.edu.au/3781
Montealegre AL, Lamelas MT, De La Riva J (2015) A comparison of open—source LiDAR filtering algorithms in a mediterranean forest environment. IEEE J Sel Top Appl Earth Obs Remote Sens 8(8):4072–4085. https://doi.org/10.1109/JSTARS.2015.2436974
Rizeei HM, Pradhan B (2018) Extraction and accuracy assessment of DTMs derived from remotely sensed and field surveying approaches in GIS framework. In: IOP conference series: earth and environmental science, vol 169
Stereńczak K, Ciesielski M, Bałazy R, Zawiła-Niedźwiecki T (2016) Comparison of various algorithms for DTM interpolation from LIDAR data in dense mountain forests. Eur J Remote Sens 49:599–621. https://doi.org/10.5721/EuJRS20164932
Szypuła B (2016) Geomorphometric comparison of DEMs built by different interpolation methods. Landf Anal 32:45–58. https://doi.org/10.12657/landfana.032.004
Tan Q, Xu X (2014) comparative analysis of spatial interpolation methods. Sens Transducers 165:155–163
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Saraf, N.M., Kamarolzaman, K.N., Saad, N.M., Khalid, N., Abdul Rasam, A.R., Othman, A.N. (2020). Data Verification of LiDAR-Derived DEM from Different Interpolation Techniques. In: Alias, N., Yusof, R. (eds) Charting the Sustainable Future of ASEAN in Science and Technology . Springer, Singapore. https://doi.org/10.1007/978-981-15-3434-8_31
Download citation
DOI: https://doi.org/10.1007/978-981-15-3434-8_31
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-3433-1
Online ISBN: 978-981-15-3434-8
eBook Packages: Social SciencesSocial Sciences (R0)