土壤侵蚀形态演化数字摄影观测系统设计与实验
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摘要
为解决目前在连续降雨条件下尚无有效的观测技术与手段从时空两个维度对土壤侵蚀过程进行观测的问题,设计了一种基于无线组网技术的数字近景摄影观测系统。该系统通过对连续降雨条件下不同时间节点的土壤侵蚀坡面进行数字影像的瞬时采集、雨滴噪声去除、点云匹配、三维重建等手段,实现对土壤侵蚀坡面形态演化过程的动态监测。该系统的测量精度可达到亚毫米级,最小测量误差为0. 006 2 mm;凹槽尺寸测量值与实测值之间最大相对误差为-2. 968 3%。土壤侵蚀坡面观测实证表明,土壤流失量估算平均相对误差为-1. 73%,单次观测精度最高可达99. 26%,时间观测分辨率可达到分钟级别,空间分辨率达到2 mm。该系统能够准确获取土壤侵蚀坡面形态变化的精细信息,可为土壤侵蚀过程研究提供新的方法和技术手段。
Observing soil erosion process at fine spatial and temporal scale is of great significance to the study of soil erosion mechanism. A digital close range photogrammetric observation system based on wireless networking technique was explored and established. The evolution of soil surface topography was dynamically monitored by instantaneous image acquisition at different time intervals during ongoing rainfall. Noises on the images such as raindrops was removed by K-means clustering,digital point clouds were calculated and digital elevation model( DEM) was then generated. The results showed that the measurement precision of the established system could reach a sub-millimeter level,and the minimum measurement error was 0. 006 2 mm. The maximum relative error between the measured value and the actual value was -2. 968 3%. According to the experimental observations,the average relative error of soil loss was -1. 73%,and the accuracy of single observation was up to 99. 26%. The established digital photogrammetric observation system could accurately calculate the digital point cloud from the underlying surface with 1 min time interval and 2 mm spatial resolution. The observation methods explored provided a reliable way to monitor soil erosion processes,especially under rainfall conditions,which was of great importance in understanding soil erosion mechanisms.
Observing soil erosion process at fine spatial and temporal scale is of great significance to the study of soil erosion mechanism. A digital close range photogrammetric observation system based on wireless networking technique was explored and established. The evolution of soil surface topography was dynamically monitored by instantaneous image acquisition at different time intervals during ongoing rainfall. Noises on the images such as raindrops was removed by K-means clustering,digital point clouds were calculated and digital elevation model( DEM) was then generated. The results showed that the measurement precision of the established system could reach a sub-millimeter level,and the minimum measurement error was 0. 006 2 mm. The maximum relative error between the measured value and the actual value was -2. 968 3%. According to the experimental observations,the average relative error of soil loss was -1. 73%,and the accuracy of single observation was up to 99. 26%. The established digital photogrammetric observation system could accurately calculate the digital point cloud from the underlying surface with 1 min time interval and 2 mm spatial resolution. The observation methods explored provided a reliable way to monitor soil erosion processes,especially under rainfall conditions,which was of great importance in understanding soil erosion mechanisms.
引文
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[23] NOUWAKPO S K,HUANG C H. A simplified close-range photogrammetric technique for soil erosion assessment[J]. Soil Science Society of America Journal,2012,76(1):70.
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[2]李景玉,张楠,王荣彬.黄河流域土壤侵蚀产沙模型研究进展[J].地理科学进展,2006,25(2):103-111.LI Jingyu,ZHANG Nan,WANG Rongbin. Soil erosion and sedimentation model in the Yellow River Basin:state-of-the-artreview[J]. Progress in Geography,2006,25(2):103-111.(in Chinese)
[3]郑粉莉,徐锡蒙,覃超.沟蚀过程研究进展[J/OL].农业机械学报,2016,47(8):48-59,116.ZHENG Fenli,XU Ximeng,QIN Chao. A review of gully erosion process research[J/OL]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(8):48-59,116. http:∥www. j-csam. org/jcsam/ch/reader/view_abstract. aspx? flag=1&file_no=20160808&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2016. 08. 008.(in Chinese)
[4]史培军,刘宝元,张科利,等.土壤侵蚀过程与模型研究[J].资源科学,1999(5):11-20.SHI Peijun,LIU Baoyuan,ZHANG Keli,et al. Soil erosion process and model studies[J]. Resources Science,1999(5):11-20.(in Chinese)
[5]郑粉莉.细沟侵蚀量测算方法的探讨[J].水土保持通报,1989,9(4):41-45,49.ZHENG Fenli. A research on method of measuring rill erosion amount[J]. Bulletin of Soil and Water Conservation,1989,9(4):41-45,49.(in Chinese)
[6]霍云云,吴淑芳,冯浩,等.基于三维激光扫描仪的坡面细沟侵蚀动态过程研究[J].中国水土保持科学,2011,9(2):32-37.HUO Yunyun,WU Shufang,FENG Hao,et al. Dynamic process of slope rill erosion based on three-dimensional laser scanner[J]. Science of Soil and Water Conservation,2011,9(2):32-37.(in Chinese)
[7]张鹏,郑粉莉,王彬,等.高精度GPS,三维激光扫描和测针板三种测量技术监测沟蚀过程的对比研究[J].水土保持通报,2008,28(5):11-15.ZHANG Peng,ZHENG Fenli,WANG Bin,et al. Comparative study of monitoring gully erosion morphology change process by using high precision GPS,Leica HDS 3000 laser scanner and needle board method[J]. Bulletin of Soil and Water Conservation,2008,28(5):11-15.(in Chinese)
[8]杨建英,祁有祥,赵廷宁,等.基于侵蚀针和近景摄影测量的侵蚀速率测定方法试验研究[J].北京林业大学学报,2010,32(3):90-94.YANG Jianying,QI Youxiang,ZHAO Tingning,et al. Measuring soil erosion rate using digital close range photogrammetry and erosion pin techniques[J]. Journal of Beijing Forestry University,2010,32(3):90-94.(in Chinese)
[9]唐泽军,雷廷武,张晴雯,等.稀土元素(REE)示踪土壤侵蚀动态过程的降雨模拟试验研究[J].农业工程学报,2006,22(3):32-35.TANG Zejun,LEI Tingwu,ZHANG Qingwen,et al. Rain simulation of dynamic soil erosion processes with rare earth element tracers[J]. Transactions of the CSAE,2006,22(3):32-35.(in Chinese)
[10]雷廷武,赵军,袁建平,等.利用γ射线透射法测量径流含沙量及算法[J].农业工程学报,2002,18(1):18-21.LEI Tingwu,ZHAO Jun,YUAN Jianping,et al. Determining sediment concentrat ion in runoff flow withγray attenuation and the related theoretical algorithm[J]. Transactions of the CSAE,2002,18(1):18-21.(in Chinese)
[11] KUIPERS H. A relief meter for soil cultivation studies[J]. Netherlands Journal of Agricultural Science,1957,5(4):255-262.
[12]唐翔宇,杨浩,赵其国,等.137Cs示踪技术在土壤侵蚀估算中的应用研究进展[J].地球科学进展,2000,15(5):576-582.TANG Xiangyu,YANG Hao,ZHAO Qiguo,et al. Review of progresses in application of137Cs tracer technique to the estimate of soil erosion[J]. Advance in Eerth Sciences,2000,15(5):576-582.(in Chinese)
[13]郑粉莉,唐克丽,白红英.标准小区和大型坡面径流场径流泥沙监测方法分析[J].人民黄河,1994,17(7):19-22.ZHENG Fenli,TANG Keli,BAI Hongying. Analysis of monitoring methods of runoff and sediment in standard plot and large sloping runoff fields[J]. Yellow River,1994,17(7):19-22.(in Chinese)
[14]林善志,喻娇.三维激光扫描仪在地形测绘中的应用[J].资源信息与工程,2018,33(3):124-125.LIN Shanzhi,YU Jiao. Application of 3D laser scanner in topographic surveying and mapping[J]. Resource Information and Engineering,2018,33(3):124-125.(in Chinese)
[15]代传超.地质灾害高精度GPS监测关键技术分析[J].有色金属文摘,2016,31(1):129-130.DAI Chuanchao. Analysis of key techniques of high precision GPS monitoring of geological hazards[J]. Nonferrous Metals Abstract,2016,31(1):129-130.(in Chinese)
[16] WELCH R,JORDAN T,THOMAS A. A photogrammetric technique for measuring soil erosion[J]. Journal of Soil and Water Conservation,1984,39(3):191-194.
[17] EITEL J U H,WILLIAMS C J,VIERLING L A,et al. Suitability of terrestrial laser scanning for studying surface roughness effects on concentrated flow erosion processes in rangelands[J]. Catena,2011,87(3):398-407.
[18]张姣,郑粉莉,温磊磊,等.利用三维激光扫描技术动态监测沟蚀发育过程的方法研究[J].水土保持通报,2012,31(6):89-94.ZHANG Jiao,ZHENG Fenli,WEN Leilei,et al. Methodology of dynamic monitoring of gully erosion process using 3D laser scanning technology[J]. Bulletin of Soil and Water Conservation,2012,31(6):89-94.(in Chinese)
[19] ZRIBI M,CIARLETTI V,TACONET O,et al. Characterisation of the soil structure and microwave backscattering based on numerical three-dimensional surface representation:analysis with a fractional Brownian model[J]. Remote Sensing of Environment,2000,72(2):159-169.
[20] TACONET O,CIARLETTI V. Estimating soil roughness indices on a ridge-and-furrow surface using stereo photogrammetry[J]. Soil&Tillage Research,2007,93(1):64-76.
[21] BLAES X,DEFOURNY P. Characterizing bidimensional roughness of agricultural soil surfaces for sar modeling[J]. IEEE Transactions on Geoscience and Remote Sensing,2008,46(12):4050-4061.
[22] ABD ELBASIT M A M,ANYOJI H,YASUDA H,et al. Potential of low cost close-range photogrammetry system in soil microtopography quantification[J]. Hydrological Processes,2009,23(10):1408-1417.
[23] NOUWAKPO S K,HUANG C H. A simplified close-range photogrammetric technique for soil erosion assessment[J]. Soil Science Society of America Journal,2012,76(1):70.
[24] RIEKE-ZAPP D H,NEARING M A. Digital close range photogrammetry for measurement of soil erosion[J]. The Photogrammetric Record,2005,20(109):69-87.
[25] HENG B C P,CHANDLER J H,ARMSTRONG A. Applying close range digital photogrammetry in soil erosion studies[J].Photogrammetric Record,2010,25(131):240-265.
[26] AGUILAR M A,AGUILAR F J,AGERA F,et al. The evaluation of close-range photogrammetry for the modelling of mouldboard plough surfaces[J]. Biosystems Engineering,2005,90(4):397-407.
[27] GUO M H,SHI H J,ZHAO J,et al. Digital close range photogrammetry for the study of rill development at flume scale[J].Catena,2016,143:265-274.
[28]李启源,王明常,王凤艳,等.用于普通相机标定的三维控制架测量方法[J].测绘科学,2017,42(5):113-117.LI Qiyuan,WANG Mingchang,WANG Fengyan,et al. 3D control frame measuring method for ordinary camera calibration[J]. Science of Surveying and Mapping,2017,42(5):113-117.(in Chinese)
[29]张洪龙,陈涛,庄培钦,等.基于立体视觉的水下三维测量系统研究[J].集成技术,2018,7(3):1-14.ZHANG Honglong,CHEN Tao,ZHUANG Peiqin,et al. A binocular stereo vision system for underwater 3D measurement[J].Journal of Integration Technology,2018,7(3):1-14.(in Chinese)
[30]李莉. Open CV耦合改进张正友算法的相机标定算法[J].轻工机械,2015,33(4):60-63.LI Li. Camera calibration algorithm based on Open CV and improved Zhang Zhengyou algorithm[J]. Light Industry Machinery,2015,33(4):60-63.(in Chinese)
[31] WANG K J,QI X X,LIU H D,et al. Deep belief network based K-means cluster approach for short-term wind power forecasting[J]. Energy,2018,165:840-852.
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