基于产量监测系统的小麦产量图生成与空间变异性分析
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摘要
为了准确获取冬小麦农田产量空间差异性信息,提升产量监测系统的采集精度与产量空间分布图的插值精度,采用研发的收获机产量实时监测系统,从绘制准确的产量空间分布图入手,对2013—2015年的小麦产量数据进行了插值及空间变异性分析,结果表明:阈值滤波的预处理方法可以有效剔除产量异常值,还原真实田间产量分布情况。通过RMSE对比得出,普通克里金(OK)方法绘制的试验地块产量空间分布图插值精度更高,最小值为826. 70 kg/hm~2,出现在2013年OK法指数模型中,搜索策略为椭圆形、最大相邻要素5个、最小相邻要素3个、1个扇区。由半方差函数拟合曲线参数得出3年产量空间变异性信息及监测系统的最优采样间距,分别为2013年与2014年的产量空间变异完全来源于空间自相关,2013年主要表现在2～12 m的中尺度范围,2014年表现在2～5 m的中尺度范围; 2015年由随机因素引起的空间变异为25%,表现在2 m以下的小尺度范围,空间自相关引起的变异为75%,表现在2～15 m的中尺度范围;产量监测系统的采样间距应保持在2～10 m,过小或过大将受到较大随机因素或插值精度降低的影响。
Obtaining yield distribution map of farmland and analyzing the spatial difference of plot yield are important foundations for implementing precision farming. In order to accurately collect the spatial difference of yield,and at the same time,the acquisition accuracy of yield monitor system and the interpolation accuracy of the output spatial distribution map are improved. The self-developed real-time monitoring system of harvester was used. Based on accurate yield spatial distribution map,spatial variability analysis was conducted on wheat yield data from 2013 to 2015. Firstly,the results showed that the pretreatment method of threshold filtering can effectively eliminate outliers and restore the real yield distribution. Secondly,by comparing the RMSE values,it was determined that spatial distribution map of experimental plot yields drawn by the ordinary Kriging( OK) had higher interpolation accuracy. The minimum value of 826. 70 kg/hm~2 appeared in the index mode of OK method for 2013,search strategy was elliptical,the largest adjacent element was 5,the smallest adjacent element was 3 and 1 sector.Finally,the curve parameters of semi-variance function were used to obtain the spatial variability information of three seasons and optimal sampling interval of the system. The spatial variation of yield in2013 and 2014 were entirely caused by spatial autocorrelation. And that of 2013 was mainly in the mesoscale range of 2 ～ 12 m,and that of 2014 was in the mesoscale range of 2 ～ 5 m. The spatial variation caused by random factors in the 2015 was 25%,which was in the small scale range below 2 m.The spatial autocorrelation caused variation of 75%,which was in the mesoscale range of 2 ～ 15 m. The sampling interval of the system should be kept at 2 ～ 10 m. Too small or too large pitch was affected by large random factors or reduced interpolation accuracy. These results can be used to develop fine management decisions for farmland.
Obtaining yield distribution map of farmland and analyzing the spatial difference of plot yield are important foundations for implementing precision farming. In order to accurately collect the spatial difference of yield,and at the same time,the acquisition accuracy of yield monitor system and the interpolation accuracy of the output spatial distribution map are improved. The self-developed real-time monitoring system of harvester was used. Based on accurate yield spatial distribution map,spatial variability analysis was conducted on wheat yield data from 2013 to 2015. Firstly,the results showed that the pretreatment method of threshold filtering can effectively eliminate outliers and restore the real yield distribution. Secondly,by comparing the RMSE values,it was determined that spatial distribution map of experimental plot yields drawn by the ordinary Kriging( OK) had higher interpolation accuracy. The minimum value of 826. 70 kg/hm~2 appeared in the index mode of OK method for 2013,search strategy was elliptical,the largest adjacent element was 5,the smallest adjacent element was 3 and 1 sector.Finally,the curve parameters of semi-variance function were used to obtain the spatial variability information of three seasons and optimal sampling interval of the system. The spatial variation of yield in2013 and 2014 were entirely caused by spatial autocorrelation. And that of 2013 was mainly in the mesoscale range of 2 ～ 12 m,and that of 2014 was in the mesoscale range of 2 ～ 5 m. The spatial variation caused by random factors in the 2015 was 25%,which was in the small scale range below 2 m.The spatial autocorrelation caused variation of 75%,which was in the mesoscale range of 2 ～ 15 m. The sampling interval of the system should be kept at 2 ～ 10 m. Too small or too large pitch was affected by large random factors or reduced interpolation accuracy. These results can be used to develop fine management decisions for farmland.
引文
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[12]唐圣学,付滔,张雪辉.基于小波自适应阈值滤波的VMD降噪方法[J].电测与仪表,2018,55(9):10-14.TANG Shengxue,FU Tao,ZHANG Xuehui.Research of denoising method based on variational mode decomposition and wavelet adaptive threshold filter[J].Electrical Measurement&Instrumentation,2018,55(9):10-14.(in Chinese)
[13]杨正益,刘博文,任山,等.一种改进的形态-小波阈值降噪方法[J].计算机科学,2018,45(5):300-302,316.YANG Zhengyi,LIU Bowen,REN Shan,et al.Improved morphological-wavelet threshold denoising method[J].Computer Science,2018,45(5):300-302,316.(in Chinese)
[14]李新成,李民赞,王锡九,等.谷物联合收割机远程测产系统开发及降噪试验[J].农业工程学报,2014,30(2):1-8.LI Xincheng,LI Minzan,WANG Xijiu,et al.Development and denoising test of grain combine with remote yield monitoring system[J].Transactions of the CSAE,2014,30(2):1-8.(in Chinese)
[15]李新成,孙茂真,李民赞,等.谷物联合收获机自动测产系统产量模型[J].农业机械学报,2015,46(7):91-96.LI Xincheng,SUN Maozhen,LI Minzan,et al.Modeling algorithm for yield monitor dystem of gain combine harvester[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(7):91-96.(in Chinese)
[16]王桂林,向林川,孙帆.粒子群优化协同克里金法在确定山地斜坡土层厚度中的应用[J].土木建筑与环境工程,2018,40(6):60-66.WANG Guilin,XIANG Linchuan,SUN Fan.Application of cooperative Kriging method based on particle swarm optimization in estimation slope soil thickness[J].Journal of Civil,Architectural&Environmental Engineering,2018,40(6):60-66.(in Chinese)
[17]王旭,刘仁杰,孙红,等.冬小麦叶绿素含量空间分布成图方法与精度分析[J].农业机械学报,2017,48(增刊):92-97.WANG Xu,LIU Renjie,SUN Hong,et al.Mapping method and accuracy analysis on spatial distribution of winter wheat chlorophyll content[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(Supp.):92-97.(in Chinese)
[18]徐丹,刘昌华,蔡太义,等.农田土壤有机质和全氮三维空间分布特征研究[J].农业机械学报,2015,46(12):157-163.XU Dan,LIU Changhua,CAI Taiyi,et al.3D spatial distribution characteristics of soil organic matter and total nitrogen in farmland[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(12):157-163.(in Chinese)
[19]BEVINGTON J,SCUDIERO E,TEATINI P,et al.Factorial Kriging analysis leverages soil physical properties and exhaustive data to predict distinguished zones of hydraulic properties[J].Computers and Electronics in Agriculture,2019,156:426-438.
[20]MUHAMMED S E,MARCHANT BP,WEBSTER R,et al.Assessing sampling designs for determining fertilizer practice from yield data[J].Computers and Electronics in Agriculture,2017,135:163-174.
[21]刘刚.支持精细农业实践的农田空间分布信息处理的方法与试验研究[D].北京:中国农业大学,2001.LIU Gang.Approaches for processing the field spatial data and practical study for precision agriculture[D].Beijing:China Agricultural University,2001.(in Chinese)
[2]李民赞.农作物产量自动监测技术及关键设备[J].农业网络信息,2004(4):34-38.LI Minzan.The technique of yield monitor and key equipment[J].Agriculture Network Information,2004(4):34-38.(in Chinese)
[3]张漫.农田谷物产量空间分布信息采集、处理与系统集成技术研究[D].北京:中国农业大学,2003.ZHANG Man.Research on grain yield information collection,processing and system integration technology[D].Beijing:China Agricultural University,2003.(in Chinese)
[4]VAN ITTERSUM M K,CASSMAM K G,GRASSINI P,et al.Yielrd gap analysis with local to global relevance-a review[J].Field Crops Res.,2013,143:4-17.
[5]GERSTMANN H,DOKTORD,GLABERC,et al.PHASE:a geostatistical model for the Kriging-based spatial predictionof crop phenology using public phenological and climatological observations[J].Computers and Electronics in Agriculture,2016,127,726-738.
[6]BRUSA D J,BOOGAARDB H,CECCARELLIB T,et al.Geostatistical disaggregation of polygon maps of average crop yields by area-to-point Kriging[J].European Journal of Agronomy,2018,97,48-59.
[7]李新成.谷物联合收割机产量监测系统优化及远程数据系统开发[D].北京:中国农业大学,2015.LI Xincheng.Optimizations of yield monitoring system for grain combine harvester and development on remote systems[D].Beijing:China Agricultural University,2015.(in Chinese)
[8]杨维鸽.典型黑土区土壤侵蚀对土壤质量和玉米产量的影响研究[D].北京:中国科学院研究生院(教育部水土保持与生态环境研究中心),2016.YANG Weige.Investigating the impacts of soil erosion on soil quality and corn yield in the typical black soil region[D].Beijing:University of Chinese Academy of Sciences,2016.(in Chinese)
[9]LIU Renjie,ZHANG Zhenqian,ZHANG Man,et al.Performance analysis and modelling of impact-based sensor in yield monitor system[C]∥6th IFAC Conference on Bio-Robotics,2018:613-618.
[10]王薄,李民赞,张成龙,等.冲击式谷物流量传感器设计与性能试验[J].农业机械学报,2009,40(增刊):52-56.WANG Bo,LI Minzan,ZHANG Chenglong,et al.Development of grain flow sensor for yield monitor system[J].Transactions of the Chinese Society for Agricultural Machinery,2009,40(Supp.):52-56.(in Chinese)
[11]张振乾,刘仁杰,张漫,等.基于移动终端的谷物产量实时监测平台设计[J].农业机械学报,2017,48(增刊):35-39.ZHANG Zhenqian,LIU Renjie,ZHANG Man,et al.Design of real-time monitoring platform for grain yield based on mobile terminal[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(Supp.):35-39.(in Chinese)
[12]唐圣学,付滔,张雪辉.基于小波自适应阈值滤波的VMD降噪方法[J].电测与仪表,2018,55(9):10-14.TANG Shengxue,FU Tao,ZHANG Xuehui.Research of denoising method based on variational mode decomposition and wavelet adaptive threshold filter[J].Electrical Measurement&Instrumentation,2018,55(9):10-14.(in Chinese)
[13]杨正益,刘博文,任山,等.一种改进的形态-小波阈值降噪方法[J].计算机科学,2018,45(5):300-302,316.YANG Zhengyi,LIU Bowen,REN Shan,et al.Improved morphological-wavelet threshold denoising method[J].Computer Science,2018,45(5):300-302,316.(in Chinese)
[14]李新成,李民赞,王锡九,等.谷物联合收割机远程测产系统开发及降噪试验[J].农业工程学报,2014,30(2):1-8.LI Xincheng,LI Minzan,WANG Xijiu,et al.Development and denoising test of grain combine with remote yield monitoring system[J].Transactions of the CSAE,2014,30(2):1-8.(in Chinese)
[15]李新成,孙茂真,李民赞,等.谷物联合收获机自动测产系统产量模型[J].农业机械学报,2015,46(7):91-96.LI Xincheng,SUN Maozhen,LI Minzan,et al.Modeling algorithm for yield monitor dystem of gain combine harvester[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(7):91-96.(in Chinese)
[16]王桂林,向林川,孙帆.粒子群优化协同克里金法在确定山地斜坡土层厚度中的应用[J].土木建筑与环境工程,2018,40(6):60-66.WANG Guilin,XIANG Linchuan,SUN Fan.Application of cooperative Kriging method based on particle swarm optimization in estimation slope soil thickness[J].Journal of Civil,Architectural&Environmental Engineering,2018,40(6):60-66.(in Chinese)
[17]王旭,刘仁杰,孙红,等.冬小麦叶绿素含量空间分布成图方法与精度分析[J].农业机械学报,2017,48(增刊):92-97.WANG Xu,LIU Renjie,SUN Hong,et al.Mapping method and accuracy analysis on spatial distribution of winter wheat chlorophyll content[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(Supp.):92-97.(in Chinese)
[18]徐丹,刘昌华,蔡太义,等.农田土壤有机质和全氮三维空间分布特征研究[J].农业机械学报,2015,46(12):157-163.XU Dan,LIU Changhua,CAI Taiyi,et al.3D spatial distribution characteristics of soil organic matter and total nitrogen in farmland[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(12):157-163.(in Chinese)
[19]BEVINGTON J,SCUDIERO E,TEATINI P,et al.Factorial Kriging analysis leverages soil physical properties and exhaustive data to predict distinguished zones of hydraulic properties[J].Computers and Electronics in Agriculture,2019,156:426-438.
[20]MUHAMMED S E,MARCHANT BP,WEBSTER R,et al.Assessing sampling designs for determining fertilizer practice from yield data[J].Computers and Electronics in Agriculture,2017,135:163-174.
[21]刘刚.支持精细农业实践的农田空间分布信息处理的方法与试验研究[D].北京:中国农业大学,2001.LIU Gang.Approaches for processing the field spatial data and practical study for precision agriculture[D].Beijing:China Agricultural University,2001.(in Chinese)