Quality of terrestrial data derived from UAV photogrammetry: A case study of Hetao irrigation district in northern China
Keywords:
UAVs, GIS, DEM, irrigation area, photogrammetry, accuracy evaluationAbstract
Most crops in northern China are irrigated, but the topography affects the water use, soil erosion, runoff and yields. Technologies for collecting high-resolution topographic data are essential for adequately assessing these effects. Ground surveys and techniques of light detection and ranging have good accuracy, but data acquisition can be time-consuming and expensive for large catchments. Recent rapid technological development has provided new, flexible, high-resolution methods for collecting topographic data, such as photogrammetry using unmanned aerial vehicles (UAVs). The accuracy of UAV photogrammetry for generating high-resolution Digital Elevation Model (DEM) and for determining the width of irrigation channels, however, has not been assessed. A fixed-wing UAV was used for collecting high-resolution (0.15 m) topographic data for the Hetao irrigation district, the third largest irrigation district in China. 112 ground checkpoints (GCPs) were surveyed by using a real-time kinematic global positioning system to evaluate the accuracy of the DEMs and channel widths. A comparison of manually measured channel widths with the widths derived from the DEMs indicated that the DEM-derived widths had vertical and horizontal root mean square errors of 13.0 and 7.9 cm, respectively. UAV photogrammetric data can thus be used for land surveying, digital mapping, calculating channel capacity, monitoring crops, and predicting yields, with the advantages of economy, speed and ease. Keywords: UAVs, GIS, DEM, irrigation area, photogrammetry, accuracy evaluation DOI: 10.25165/j.ijabe.20181103.3012 Citation: Zhang H M, Yang J T, Baartman J E M, Li S Q, Jin B, Han W T. Quality of terrestrial data derived from UAV photogrammetry: A case study of Hetao irrigation district in northern China. Int J Agric & Biol Eng, 2018; 11(3): 171–177.References
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[2] Zhang H, Yang Q, Li R, Liu Q, Moore D, He P, Ritsema C J, Geissen V. Extension of a GIS procedure for calculating the RUSLE equation LS factor. Computers & Geosciences, 2013; 52: 177–188.
[3] Su C, Feng C, Wang X, Huang Z, Zhang X. An efficient algorithm for assignment of flow direction over flat surfaces in raster DEMs based on distance transform. Earth Science Informatics, 2016; 9(2): 225–233.
[4] Zhou G, Sun Z, Fu S. An efficient variant of the priority-flood algorithm for filling depressions in raster digital elevation models. Computers & Geosciences: Part A, 2016; 90: 87–96.
[5] Persendt F C, Gomez C. Assessment of drainage network extractions in a low-relief area of the Cuvelai Basin (Namibia) from multiple sources: LiDAR, topographic maps, and digital aerial orthophotographs. Geomorphology, 2016: 260: 32–50.
[6] Zhang H, Yao Z, Yang Q, Li S, Baartman J E M, Gai L, Yao M, Yang X, Ritsema C J, Geissen V. An integrated algorithm to evaluate flow direction and flow accumulation in flat regions of hydrologically corrected DEMs. Catena, 2017: 151: 174–181.
[7] Martinez-Agirre A, Alvarez-Mozos J, Gimenez R. Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter. Soil & Tillage Research, 2016; 161: 19–30.
[8] Gomes T L, Magalhaes S V G, Andrade M V A, Franklin W R, Pena G C. Efficiently computing the drainage network on massive terrains using external memory flooding process. Geoinformatica, 2015; 19(4): 671-692.
[9] Pajares G. Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs). Photogrammetric Engineering and Remote Sensing, 2015; 81(4): 281–329.
[10] Ouedraogo M M, Degre A, Debouche C, Lisein J. The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds. Geomorphology, 2014; 214: 339–355.
[11] Yang Q K, McVicar T R, Van Niel T G, Hutchinsond M F, Li L T, Zhang X P. Improving terrain representation of a digital elevation model by reducing source data errors and optimising interpolation algorithm parameters: an example in the Loess Plateau, China . International Journal of Applied Eart Observation and Geoinformation (JAG), 2007; 9(3): 235–246.
[12] Eltner A, Baumgart P. Accuracy constraints of terrestrial Lidar data for soil erosion measurement: Application to a Mediterranean field plot. Geomorphology, 2015; 245: 243–254.
[13] Everaerts J, Lewyckyj N, Fransaer D. Pegasus: design of a stratospheric long endurance UAV system for remote sensing. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: Part B, 2004; 35–39.
[14] Bin Abdullah K. Use of water and land for food security and environmental sustainability. Irrigation and Drainage, 2006; 55(3): 219–222.
[15] Tarolli P. High-resolution topography for understanding Earth surface processes: Opportunities and challenges. Geomorphology, 2014; 216: 295–312.
[16] Huang Y B, Thomson S J, Brand H J, Reddy K N. Development and evaluation of low-altitude remote sensing systems for crop production management. International Journal of Agricultural and Biological Engineering, 2016; 9(4): 1–11.
[17] Xu X, Huang G, Qu Z, Pereira L S. Assessing the groundwater dynamics and impacts of water saving in the Hetao Irrigation District, Yellow River basin. Agricultural Water Management, 2010; 98(2): 301–313.
[18] Akgul M, Demir M, Ozturk T, Topatan H, Budak Y E. Investigation of recreational vehicles maneuverability on forest roads by computer-aided driving analysis. Baltic Journal of Road and Bridge Engineering, 2016, 11(2): 111–119.
[19] Xue X Y, Tu K, Qin W C, Lan Y B, Zhang H H. Drift and deposition of ultra-low altitude and low volume application in paddy field. International Journal of Agricultural and Biological Engineering, 2014; 7(4): 23–28.
[20] Reinhold S, Belinskiy A, Korobov D. Caucasia top-down: Remote sensing data for survey in a high altitude mountain landscape. Quaternary International, 2016; 402: 46–60.
[21] Achille C, Adami A, Chiarini S, Cremonesi S, Fassi F, Fregonese L, Taffurelli L. UAV-based photogrammetry and integrated technologies for architectural applications-methodological strategies for the after-quake survey of vertical structures in Mantua (Italy). Sensors, 2015; 15(7): 15520–15539.
[22] Neugirg F, Stark M, Kaiser A, Vlacilova M, Della Seta M, Vergari F, et al. Erosion processes in calanchi in the Upper Orcia Valley, Southern Tuscany, Italy based on multitemporal high-resolution terrestrial LiDAR and UAV surveys. Geomorphology, 2016; 269: 8–22.
[23] Zhou H L, Kong H, Wei L, Creighton D, Nahavandi S. Efficient Road Detection and Tracking for Unmanned Aerial Vehicle. IEEE Transactions on Intelligent Transportation Systems, 2015; 16(1): 297–309.
[24] Zhou Z X, Gong J, Guo M Y. Image-based 3D reconstruction for posthurricane residential building damage assessment. Journal of Computing in Civil Engineering, 2016; 30(2): 14.
[25] Krsak B, Blistan P, Paulikova A, Puskarova P, Kovanic L, Palkova J, et al. Use of low-cost UAV photogrammetry to analyze the accuracy of a digital elevation model in a case study. Measurement, 2016; 91: 276–287.
[26] Jaud M, Passot S, Le Bivic R, Delacourt C, Grandjean P, Le Dantec N. Assessing the accuracy of high resolution digital surface models computed by PhotoScan® and MicMac® in sub-optimal survey conditions. Remote Sensing, 2016; 8(6): 18.
[27] Ishiguro S, Yamano H, Oguma H. Evaluation of DSMs generated from multi-temporal aerial photographs using emerging structure from motion-multi-view stereo technology. Geomorphology, 2016; 268: 64–71.
[28] Yang T, Xu C Y, Shao Q X, Chen X, Lu G H, Hao Z C. Temporal and spatial patterns of low-flow changes in the Yellow River in the last half century. Stochastic Environmental Research and Risk Assessment, 2010; 24(2): 297–309.
[29] Yu R, Liu T, Xu Y, Zhu C, Zhang Q, Qu Z, Liu X, Li C. Analysis of salinization dynamics by remote sensing in Hetao Irrigation District of North China. Agricultural Water Management, 2010; 97(12): 1952–1960.
[30] Barrette J, August P, Golet F. Accuracy assessment of wetland boundary delineation using aerial photography and digital orthophotography. Photogrammetric Engineering and Remote Sensing, 2000, 66 (4): 409–416.
[31] Ruzgienė B, Berteška T, Gečyte S, Jakubauskienė E, Aksamitauskas V Č. The surface modelling based on UAV Photogrammetry and qualitative estimation. Measurement, 2015; 73: 619–627.
[32] Royo P, Pastor E, Barrado C, Santamaria E, Lopez J, Prats X, Lema J M. Autopilot abstraction and standardization for seamless integration of unmanned aircraft system applications. Journal of Aerospace Computing Information and Communication, 2011; 8(7): 197–223.
[33] Agisoft L. Agisoft PhotoScan user manual. Professional edition, version 0.9. 0: AgiSoft LLC (Pub), Calgary, CA. 2013.
[34] Gan-Mor S, Clark R L, Upchurch B L. Implement lateral position accuracy under RTK-GPS tractor guidance. Computers and Electronics in Agriculture, 2007; 59(1-2): 31–38.
[35] Wechsler S P. Uncertainties associated with digital elevation models for hydrologic applications: A review. Hydrology and Earth System Sciences, 2007; 11(4): 1481–1500.
[36] Caruso V. Standards for digital elevation models. American Society for Photogrammetry and Remote Sensing (ASPRS) and American Congress on Surveying and Mapping (ACSM) annual convention proceedings, 1987; pp.159–166.
[37] Chai T, Draxler R R. Root mean square error (RMSE) or mean absolute error (MAE)?–Arguments against avoiding RMSE in the literature. Geoscientific Model Development, 2014; 7(3): 1247–1250.
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Published
2018-06-01
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Zhang, H., Yang, J., Baartman, J. E., Li, S., Jin, B., Han, W., … Geissen, V. (2018). Quality of terrestrial data derived from UAV photogrammetry: A case study of Hetao irrigation district in northern China. International Journal of Agricultural and Biological Engineering, 11(3), 171–177. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/3012
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Information Technology, Sensors and Control Systems
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