Abstract
Accurate and efficient extraction of ecological irrigation canals plays a key role in realizing agricultural modernization. In view of the problem of ecological irrigation canal extraction, this paper proposes an airborne lidar extraction method based on unmanned aerial vehicle (UAV). First, the method of acquiring 3D point cloud data on the ground is derived. The filtering method of mathematical morphology is used to remove ground noise. Then, the characteristic line of the ecological irrigation canal is extracted, a new threshold selection method is put forward according to the characteristics of the ecological irrigation canal. It is helpful to further accurately extract the characteristic lines of the ecological irrigation canal. Finally, the characteristics of the three-dimensional point cloud data and the characteristics of the reflection intensity are analyzed. It is significant to distinguish the ecological irrigation canals and other disturbing terrain. Compared with the traditional extraction method (such as machine vision), the method has the advantages of high efficiency, high precision and no artificial parameters. The model of a small ecological irrigation canal was established by Matlab. It has important practical value for the later planning of ecological irrigation canals and the acceleration of agricultural modernization.
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References
Gu, C., Liu, Y., Liu, D., Li, Z., Mohamed, I., Zhang, R., Brooks, M., Chen, F.: Distribution and ecological assessment of heavy metals in irrigation channel sediments in a typical rural area of south China. Ecol. Eng. 90(90), 466–472 (2016)
Liu, Z., Chen, J., Chen, D., Li-Dong, B.I., Wang, G., Xue-Chun, L.I., Zhu, Y.: Effect monitoring and evaluation of ecological revetment on irrigation canals. China Rural Water Hydropower 8, 13–17 (2016)
Horváth, K.: Model predictive control of resonance sensitive irrigation canals. Tdx Tesis Doctorals En Xarxa (2013)
Huang, M., Dang, T., Gallichand, J., Goulet, M.: Effect of increased fertilizer applications to wheat crop on soil-water depletion in the loess plateau, china. Agric. Water Manag. 58(3), 267–278 (2003)
Li, F.M., Wang, P., Wang, J., Xu, J.Z.: Effects of irrigation before sowing and plastic film mulching on yield and water uptake of spring wheat in semiarid Loess Plateau of China. Agric. Water Manag. 67(2), 77–88 (2004)
Kaneko, S., Tanaka, K., Toyota, T., Managi, S.: Water efficiency of agricultural production in china: regional comparison from 1999 to 2002. Int. J. Agric. Resour. Gov. Ecol. 3(3), 231–251 (2004)
Wang, Z., Zerihun, D., Feyen, J.: General irrigation efficiency for field water management. Agric. Water Manag. 30(2), 123–132 (1996)
Ali, M.H., Shui, L.T., Yan, K.C., Eloubaidy, A.F., Foong, K.C.: Modeling water balance components and irrigation efficiencies in relation to water requirements for double-cropping systems. Agric. Water Manag. 46(2), 167–182 (2000)
Alexander, C., Korstjens, A.H., Hill, R.A.: Influence of micro-topography and crown characteristics on tree height estimations in tropical forests based on LiDAR canopy height models. Int. J. Appl. Earth Obs. Geoinf. 65, 105–113 (2018)
He, M., Zhao, H., Davoine, F., Cui, J., Zha, H.: Pairwise LIDAR calibration using multi-type 3D geometric features in natural scene. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1828–1835 (2013)
Song, J.H.: Assessing the possibility of land-cover classification using lidar intensity data. Int. Soc. Photogramm. Remote Sens. 34, 259–262 (2002)
Chen, P., Tan, Y.W., Liang, L.I.: Extraction of building’s feature lines based on 3-D terrestrial laser scanning. Laser J. 37(3), 9–11 (2016)
Qian, C., Lin, W., Chen, J., Li, Z., Gao, H.: Point cloud trajectory planning based on Octree and K-dimensional tree algorithm. In: Chinese Association of Automation, pp. 213–218 (2017)
Acknowledgement
The authors express gratitude for the financial support from the National Key R&D Program of China (Grant Nos. 2017YFD0701003 from 2017YFD0701000, 2016YFD0200702 from 2016YFD0200700, 2017YFC0403203 and 2016YFC0400207), the National Natural Science Foundation of China (Grant No. 51509248), the Jilin Province Key R&D Plan Project (Grant No. 20180201036SF), and the Chinese Universities Scientific Fund (Grant Nos. 2018QC128 and 2018SY007).
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Wang, G. et al. (2019). An Ecological Irrigation Canal Extraction Algorithm Based on Airborne Lidar Point Cloud Data. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_46
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DOI: https://doi.org/10.1007/978-981-13-6052-7_46
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