Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation
Yıl: 2022 Cilt: 7 Sayı: 2 Sayfa Aralığı: 161 - 173 Metin Dili: İngilizce DOI: 10.26833/ijeg.940997 İndeks Tarihi: 31-08-2022
Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation
Öz: Inverse Distance Weighted (IDW) based interpolation method is also widely used in earth science studies. In the classical IDW method, the directional distribution of the reference points around the point to be estimated within the critical circle and the slope differences are not taken into consideration. On the other hand, in the IDW-based method developed by Shepard, the ratio of the distances of the reference points within the critical circle to the critical circle radius (r), the anisotropy and the slope differences are taken into consideration. In this study, the results of the classical IDW method and Shepard method were compared to increase the accuracy of interpolation produced from UAV data. A software has been developed to make these comparisons in more detail. The classical IDW and Shepard based interpolation methods used in this software takes into consideration the anisotropy, the slope differences and the ratio of the distances to the critical circle radius. In this study, UAV flights were performed in three different study areas with different topographic features and 3D point cloud data were obtained in order to make detailed analyzes. Using developed software, data from three different study areas have been tested and the results from different Shepard interpolation models have been discussed. The major contribution of this paper is in evaluation of various IDW options when applied to UAV point data. As a result, especially in geodetic studies form UAV data, it was observed that the results improved with 11% to 37% by using the Shepard method with the suitable power parameter value considering the directional distribution of the reference points in the critical circle and the slope differences.
Anahtar Kelime: Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
- Agüera-Vega F, Agüera-Puntas M, Mancini F, Martínez-Carricondo P & Carvajal-Ramírez F (2019). Effects of Structure from Motion Data density, interpolation method and grid size on micro topography Digital Terrain Model accuracy. Preprints doi: 10.20944/preprints 201908.0283.v1.
- Arun P V (2013). A comparative analysis of different DEM interpolation methods. The Egyptian Journal of Remote Sensing and Space Science, 16(2), 133-139.
- Bater C W & Coops N C (2009). Evaluating error associated with lidar-derived DEM interpolation. Computers & Geosciences, 35(2), 289-300.
- Brimicombe A (2009). GIS, environmental modeling and engineering. CRC Press
- Chen F W & Liu C W (2012). Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan. Paddy and Water Environment, 10(3), 209-222.
- Das M, Hazra A, Sarkar A, Bhattacharya S & Banik P (2017). Comparison of spatial interpolation methods for estimation of weekly rainfall in West Bengal, India. Mausam, 68(1), 41-50.
- Envir. Sys. Res. Inst.: How IDW Works (2020). https://desktop.arcgis.com/en/arcmap/10.3/tools/3d-analyst-toolbox/how-idw-orks.htm . Accessed 04 February 2020
- Ferreira I O, Rodrigues D D, Santos G R D, & Rosa L M F (2017). In bathymetric surfaces: IDW or Kriging? Boletim de Ciências Geodésicas, 23(3), 493-508.
- Guo Q, Li W, Yu H & Alvarez O (2010). Effects of topographic variability and lidar sampling density on several DEM interpolation methods. Photogrammetric Engineering & Remote Sensing, 76(6), 701-712.
- Graham A N, Coops N C, Tompalski P, Plowright A & Wilcox M (2020). Effect of ground surface interpolation methods on the accuracy of forest attribute modelling using unmanned aerial systems-based digital aerial photogrammetry. International Journal of Remote Sensing, 41(9), 3287-3306.
- Habib A, Khoshelham K, Akdim N, Labbassi K & Menenti M (2018). Impact of spatial resolution, interpolation and filtering algorithms on DEM accuracy for geomorphometric research: a case study from Sahel-Doukkala, Morocco. Modeling Earth Systems and Environment, 4(4), 1537-1554.
- Ikechukwu M N, Ebinne E, Idorenyin U & Raphael N I (2017). Accuracy assessment and comparative analysis of IDW, spline and kriging in spatial interpolation of landform (Topography): An experimental study. Journal of Geographic Information System, 9(03), 354.
- Ismail Z, Abdul Khanan M F, Omar F Z, Abdul Rahman M Z & Mohd Salleh M R (2016). EVALUATING ERROR OF LIDAR DERIVED DEM INTERPOLATION FOR VEGETATION AREA. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 42.
- Liao Y, Li D & Zhang N, 2018.” Comparison of interpolation models for estimating heavy metals in soils under various spatial characteristics and sampling methods”. Transactions in GIS, 22(2), 409-434.
- Lu G Y & Wong D W (2008). An adaptive inverse-distance weighting spatial interpolation technique. Computers & geosciences, 34(9), 1044-1055.
- Meng Y, Cave M & Zhang C (2019). Comparison of methods for addressing the point-to-area data transformation to make data suitable for environmental, health and socio-economic studies. Science of The Total Environment, 689, 797-807.
- Michael S (2020). GRASS Development Team: GRASS GIS 7.6.2 dev Reference Manual. https://grass.osgeo.org/grass76/manuals/v.surf.idw.html. Accessed 04 February 2020
- Mohamed K S, Sajikumar K K, Ragesh N, Ambrose T V, Jayasankar J, Said Koya K P & Sasikumar G (2018). Relating abundance of purpleback flying squid Sthenoteuthis oualaniensis (Cephalopoda: Ommastrephidae) to environmental parameters using GIS and GAM in south-eastern Arabian Sea. Journal of Natural History, 52(29-30), 1869-1882.
- Paul R, Brindha K, Gowrisankar G, Tan M L & Singh M K (2019). Identification of hydrogeochemical processes controlling groundwater quality in Tripura, Northeast India using evaluation indices, GIS, and multivariate statistical methods. Environmental Earth Sciences, 78(15), 1-16.
- Sarkar S, Parihar S M & Dutta A (2016). Fuzzy risk assessment modelling of East Kolkata Wetland Area: A remote sensing and GIS based approach. Environmental modelling & software, 75, 105-118.
- Setianto A S & Triandini T T (2013). Comparison of kriging and inverse distance weighted (IDW) interpolation methods in lineament extraction and analysis. Journal of Southeast Asian Applied Geology, 5(1), 21-29.
- Shepard D (1968). A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference (pp. 517-524).
- Stafford JV (2013) Precision agriculture’13. Wageningen Academic Publishers
- Tran Q B & Nguyen T T (2008). Assessment of the influence of interpolation techniques on the accuracy of digital elevation model. VNU Journal of Science. Earth Sciences 24, 176-183.
- Wang G & Huang L (2012). 3D geological modeling for mineral resource assessment of the Tongshan Cu deposit, Heilongjiang Province, China. Geoscience Frontiers, 3(4), 483-491.
- Welch M C, Kwan P W & Sajeev A S M (2014). Applying GIS and high-performance agent-based simulation for managing an Old-World Screwworm fly invasion of Australia. Acta tropica, 138, 82-93.
- 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.
- Zhou M, Guan H, Li C, Teng G & Ma L (2017). An improved IDW method for linear array 3D imaging sensor. In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 3397-3400). IEEE.
- Url-1 <https://support.PIX4d.com/hc/en-us/articles/202558889-Accuracy-of-PIX4Doutputs >, date of access: 2020
| APA | HASTAOGLU K, gogsu s, GÜL Y (2022). Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. , 161 - 173. 10.26833/ijeg.940997 |
| Chicago | HASTAOGLU KEMAL OZGÜR,gogsu sinan,GÜL YAVUZ Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. (2022): 161 - 173. 10.26833/ijeg.940997 |
| MLA | HASTAOGLU KEMAL OZGÜR,gogsu sinan,GÜL YAVUZ Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. , 2022, ss.161 - 173. 10.26833/ijeg.940997 |
| AMA | HASTAOGLU K,gogsu s,GÜL Y Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. . 2022; 161 - 173. 10.26833/ijeg.940997 |
| Vancouver | HASTAOGLU K,gogsu s,GÜL Y Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. . 2022; 161 - 173. 10.26833/ijeg.940997 |
| IEEE | HASTAOGLU K,gogsu s,GÜL Y "Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation." , ss.161 - 173, 2022. 10.26833/ijeg.940997 |
| ISNAD | HASTAOGLU, KEMAL OZGÜR vd. "Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation". (2022), 161-173. https://doi.org/10.26833/ijeg.940997 |
| APA | HASTAOGLU K, gogsu s, GÜL Y (2022). Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. International Journal of Engineering and Geosciences, 7(2), 161 - 173. 10.26833/ijeg.940997 |
| Chicago | HASTAOGLU KEMAL OZGÜR,gogsu sinan,GÜL YAVUZ Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. International Journal of Engineering and Geosciences 7, no.2 (2022): 161 - 173. 10.26833/ijeg.940997 |
| MLA | HASTAOGLU KEMAL OZGÜR,gogsu sinan,GÜL YAVUZ Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. International Journal of Engineering and Geosciences, vol.7, no.2, 2022, ss.161 - 173. 10.26833/ijeg.940997 |
| AMA | HASTAOGLU K,gogsu s,GÜL Y Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. International Journal of Engineering and Geosciences. 2022; 7(2): 161 - 173. 10.26833/ijeg.940997 |
| Vancouver | HASTAOGLU K,gogsu s,GÜL Y Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation. International Journal of Engineering and Geosciences. 2022; 7(2): 161 - 173. 10.26833/ijeg.940997 |
| IEEE | HASTAOGLU K,gogsu s,GÜL Y "Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation." International Journal of Engineering and Geosciences, 7, ss.161 - 173, 2022. 10.26833/ijeg.940997 |
| ISNAD | HASTAOGLU, KEMAL OZGÜR vd. "Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation". International Journal of Engineering and Geosciences 7/2 (2022), 161-173. https://doi.org/10.26833/ijeg.940997 |
