中国农业机械化科学研究院集团有限公司 主管

北京卓众出版有限公司 主办

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

遥感多光谱成像在解析土壤成分方面研究进展

马纬 武志明 温鑫伟 余科松

马纬,武志明,温鑫伟,等.遥感多光谱成像在解析土壤成分方面研究进展[J].农业工程,2022,12(11):30-36. doi: 10.19998/j.cnki.2095-1795.2022.11.006
引用本文: 马纬,武志明,温鑫伟,等.遥感多光谱成像在解析土壤成分方面研究进展[J].农业工程,2022,12(11):30-36. doi: 10.19998/j.cnki.2095-1795.2022.11.006
MA Wei,WU Zhiming,WEN Xinwei,et al.Research progress of remote sensing multi-spectral imaging in analyzing soil composition[J].Agricultural Engineering,2022,12(11):30-36. doi: 10.19998/j.cnki.2095-1795.2022.11.006
Citation: MA Wei,WU Zhiming,WEN Xinwei,et al.Research progress of remote sensing multi-spectral imaging in analyzing soil composition[J].Agricultural Engineering,2022,12(11):30-36. doi: 10.19998/j.cnki.2095-1795.2022.11.006

遥感多光谱成像在解析土壤成分方面研究进展

doi: 10.19998/j.cnki.2095-1795.2022.11.006
基金项目: 山西省重点研发计划项目(201903D221029);省部共建有机旱作农业国家重点实验室(筹)自主研发课题(202105D121008-3-4)
详细信息
    作者简介:

    马纬,硕士生,主要从事遥感解析土壤成分信息研究 E-mail:1074903125@qq.com

    武志明,通信作者,副教授,硕士生导师,主要从事机械设计、农业航空工程和智能农机装备研究E-mail:zhim_wu@163.com

  • 中图分类号: S127

Research Progress of Remote Sensing Multi-spectral Imaging in Analyzing Soil Composition

  • 摘要:

    土壤中营养成分的变化关乎农业的生产质量,其中水分、有机质、氮、磷、钾等养分信息是土壤肥力的关键,因此获取农田土壤成分信息对农田管理有重要意义。传统土壤检测方法烦琐复杂、费时费力、效率低下,难以满足现代农业发展的需要。随着遥感技术的不断发展与成熟,基于低空尺度的农业无人机和基于高空尺度的卫星平台弥补了地面监测的空缺与不足,飞行器搭载的多光谱传感器在土壤信息的快速、无损、实时获取领域表现出巨大潜力。介绍了多光谱技术特点,概括了遥感多光谱成像技术检测土壤成分的一般步骤,重点阐述了多光谱技术在检测土壤有机质、水分、盐分等方面的研究进展,探讨了遥感多光谱技术在解析土壤成分中涉及的主要方法,最后对农业遥感多光谱成像解析土壤成分进行了思考与展望。

     

  • 图 1  常用轻小型多光谱传感器

    Figure 1.  Light and small multispectral sensors commonly used

    图 2  遥感平台解析土壤信息的一般建模过程

    Figure 2.  General modeling process for interpreting soil information by remote sensing platforms

    图 3  多光谱图像处理分析流程

    Figure 3.  General processing and analysis process of multispectral images

    表  1  常用轻小型多光谱传感器

    Table  1.   Light and small multispectral sensors commonly used

    传感器波段数波段/nm分辨率/(px×px)
    ADC lite3红、绿、近红外2048×1536
    MicroCA 6波段6490、550、680、720、800、9001280×1024
    Parrot Sequoia4550、660、735、7901280×960
    RedEdge5475、560、668、717、8401280×960
    下载: 导出CSV

    表  2  土壤主要成分及生理作用

    Table  2.   Main components and physiological effects of soil

    主要成分分类生理作用
    有机质新鲜有机质、半分解有机质、腐殖质作物养分的主要来源;增强土壤肥力,提高土壤持水性;改良土壤性质;促进土壤植物的生长发育
    矿物质沙砾、土粒和胶粒为植物提供矿质营养;影响土壤肥力
    水分固态水、汽态水、束缚水、自由水等为植物补充水分,帮助根系吸收养分;土壤有机物的分解;化学肥料的溶解
    其他盐分、空气、微生物等盐分会影响植物的光合与呼吸作用、蛋白质的合成等;土壤空气影响根系的呼吸;土壤微生物可为植物提供营养,调节植物生长
    下载: 导出CSV

    表  3  常用于光谱数据与实测数据建模的回归算法

    Table  3.   Regression algorithms commonly used for spectral data and measured data modeling

    方法土壤类别指标模型精度文献
    多元线性回归淮南土壤有机质Rc2=0.815[39]
    逐步回归法陕西旱区土壤含水率Rc2=0.815 ,Rv2=0.774[40]
    偏最小二乘法北京潮土有机质Rc2=0.586, RMSEC=0.280[41]
    支持向量机山东滨州土壤有机质Rc2=0.89,RMSEC=0.20
    RV2=0.82,RMSEV=0.24
    [42]
    卷积神经网络东北褐土有机质R2=0.82,RMSE=1.4 g/kg[43]
    极限学习机砂壤土含水率Rc2=0.825, RMSEC=10.85%
    RV2=0.750,RMSEV=13.55%
    [44]
    下载: 导出CSV
  • [1] WANG Weihua, CAI Liliang, PENG Peiyu, et al.Soil sampling spacing based on precision agriculture variable rate fertilization of pomegranate orchard[J].Communications in Soil Science and Plant Analysis, 2021, 52(19/22): 2 445-2 461.
    [2] PAN Xiaoyan,LYU Jialong,DYCK Miles,et al.Bibliometric analysis of soil nutrient research between 1992 and 2020[J].Agriculture,2021,11(3):223. doi: 10.3390/agriculture11030223
    [3] POTDAR R P, SHIROLKAR M M, VERM A J, et al.Determination of soil nutrients(NPK)using optical methods: a mini review[J].Journal of Plant Nutrition, 2021, 44(12): 1 826-1 839.
    [4] 纪景纯,赵原,邹晓娟,等.无人机遥感在农田信息监测中的应用进展[J].土壤学报,2019,56(4):773-784. doi: 10.11766/trxb201811190508

    JI Jingchun,ZHAO Yuan,ZOU Xiaojuan,et al.Advancement in application of UAV remote sensing to monitoring of farmlands[J].Acta Pedologica Sinica,2019,56(4):773-784. doi: 10.11766/trxb201811190508
    [5] 李江波, 饶秀勤, 应义斌.农产品外部品质无损检测中高光谱成像技术的应用研究进展[J].光谱学与光谱分析, 2011, 31(8): 2 021-2 026.

    LI Jiangbo, RAO Xiuqin, YING Yibin.Advance on application of hyperspectral imaging to nondestructive detection of agricultural products external quality [J].Spectroscopy and Spectral Analysis, 2011, 31(8): 2 021-2 026.
    [6] 王璐, 蔺启忠, 贾东, 等.多光谱数据定量反演土壤营养元素含量可行性分析[J].环境科学, 2007, 28(8): 1 822-1 828.

    WANG Lu, LIN Qizhong, JIA Dong, et al.Analysis on possibilites of multi-spectral data for quantitative retrieving soil nutrient element contents [J].Environmental Science, 2007, 28(8): 1 822-1 828.
    [7] 冯珊珊,梁雪映,樊风雷,等.基于无人机多光谱数据的农田土壤水分遥感监测[J].华南师范大学学报(自然科学版),2020,52(6):74-81. doi: 10.6054/j.jscnun.2020098

    FENG Shanshan,LIANG Xueying,FAN Fenglei,et al.Monitoring of farmland soil moisture based on unmanned aerial vehicle multispectral data[J].Journal of South China Normal University(Natural Science Edition),2020,52(6):74-81. doi: 10.6054/j.jscnun.2020098
    [8] 李雪萍,张飞,王小平.微分算法的艾比湖湿地自然保护区土壤有机质多光谱建模[J].光谱学与光谱分析,2019,39(2):535-542.

    LI Xueping,ZHANG Fei,WANG Xiaoping.Study on differential-based multispectral modeling of soil organic matter in Ebinur lake wetland[J].Spectroscopy and Spectral Analysis,2019,39(2):535-542.
    [9] 张智韬,魏广飞,姚志华,等.基于无人机多光谱遥感的土壤含盐量反演模型研究[J].农业机械学报,2019,50(12):151-160. doi: 10.6041/j.issn.1000-1298.2019.12.017

    ZHANG Zhitao,WEI Guangfei,YAO Zhihua,et al.Soil salt inversion model based on UAV multispectral remote sensing[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(12):151-160. doi: 10.6041/j.issn.1000-1298.2019.12.017
    [10] 李鑫星, 曹闪闪, 白雪冰, 等.多光谱技术在土壤成分含量检测中的研究进展[J].光谱学与光谱分析, 2020, 40(7): 2 042-2 047.

    LI Xinxing, CAO Shanshan, BAI Xuebing, et al.Research progress of multi-spectral technique in the determination of soil component and content [J].Spectroscopy and Spectral Analysis, 2020, 40(7): 2 042-2 047.
    [11] 孙刚,黄文江,陈鹏飞,等.轻小型无人机多光谱遥感技术应用进展[J].农业机械学报,2018,49(3):1-17. doi: 10.6041/j.issn.1000-1298.2018.03.001

    SUN Gang,HUANG Wenjiang,CHEN Pengfei,et al.Advances in UAV-based multispectral remote sensing applications[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(3):1-17. doi: 10.6041/j.issn.1000-1298.2018.03.001
    [12] 叶昱程,应义斌.多光谱图像技术在食品品质检测中的应用与发展[J].中国食品学报,2003,3(4):89-92. doi: 10.3969/j.issn.1009-7848.2003.04.021

    YE Yucheng,YING Yibin.Application and development of multispectral imaging technique in the quality detection of food[J].Journal of Chinese Institute of Food Science and Technology,2003,3(4):89-92. doi: 10.3969/j.issn.1009-7848.2003.04.021
    [13] 黄培峰,朱立学,陈家政.农业无人机遥感技术研究进展[J].机电产品开发与创新,2021,34(3):43-45. doi: 10.3969/j.issn.1002-6673.2021.03.013

    HUANG Peifeng,ZHU Lixue,CHEN Jiazheng.Research advances on agricultural UAV remote sensing technology[J].Development & Innovation of Machinery,2021,34(3):43-45. doi: 10.3969/j.issn.1002-6673.2021.03.013
    [14] WEI Guangfei,LI Yu,ZHANG Zhitao,et al.Estimation of soil salt content by combining UAV-borne multispectral sensor and machine learning algorithms[J].PeerJ,2020,8(2): e9087 .
    [15] 王众司,贾亚萍,张瑾,等.多光谱成像技术在植物学研究中的应用[J].植物学报,2021,56(4):500-508. doi: 10.11983/CBB21002

    WANG Zongsi,JIA Yaping,ZHANG Jin,et al.Multispectral imaging and its applications in plant science research[J].Bulletin of Botany,2021,56(4):500-508. doi: 10.11983/CBB21002
    [16] 李鑫星, 梁步稳, 白雪冰, 等.光谱技术在土壤水分含量检测中的研究进展[J].光谱学与光谱分析, 2020, 40(12): 3 705-3 710.

    LI Xinxing, LIANG Buweng, BAI Xuebing, et al.Research progress of spectroscopy in the detection of soil moisture content[J].Spectroscopy and Spectral Analysis, 2020, 40(12): 3 705-3 710.
    [17] 夏可.基于近地面高光谱遥感土壤基础指标光学特征及反演模型优选[D].淮南: 安徽理工大学, 2020.

    XIA Ke.Optimal selection of inversion model and optical characteristics of soil basic indicators based on near-ground hyperspectral remote sensing [D].Huainan: Anhui University of Science and Technology, 2020.
    [18] 夏楠,塔西甫拉提·特依拜,丁建丽,等.基于多光谱数据的荒漠矿区土壤有机质估算模型[J].农业工程学报,2016,32(6):263-267. doi: 10.11975/j.issn.1002-6819.2016.06.036

    XIA Nan,TASHPOLATI Teybai,DING Jianli,et al.Estimation model of soil organic matter in desert mining area based on multi-spectral image data[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(6):263-267. doi: 10.11975/j.issn.1002-6819.2016.06.036
    [19] 陈思明,邹双全,毛艳玲,等.土壤光谱重建的湿地土壤有机质含量多光谱反演[J].光谱学与光谱分析,2018,38(3):912-917.

    CHEN Siming,ZOU Shuangquan,MAO Yanling,et al.Inversion of soil organic matter content in wetland using multispectral data based on soil spectral reconstruction[J].Spectroscopy and Spectral Analysis,2018,38(3):912-917.
    [20] 刘焕军,张美薇,杨昊轩,等.多光谱遥感结合随机森林算法反演耕作土壤有机质含量[J].农业工程学报,2020,36(10):134-140. doi: 10.11975/j.issn.1002-6819.2020.10.016

    LIU Huanjun,ZHANG Meiwei,YANG Haoxuan,et al.Invertion of cultivated soil organic matter content combining multi-spectral remote sensing and random forest algorithm[J].Transactions of the Chinese Society of Agricultural Engineering,2020,36(10):134-140. doi: 10.11975/j.issn.1002-6819.2020.10.016
    [21] 邢华铭.土壤成分与特性参数光谱快速检测方法及传感技术[J].农业与技术,2017,37(23): 35,51.
    [22] 高培霞,张吴平,梁爽,等.基于温度植被干旱指数(TVDI)的土壤干湿反演[J].灌溉排水学报,2018,37(10):123-128. doi: 10.13522/j.cnki.ggps.2017.0603

    GAO Peixia,ZHANG Wuping,LIANG Shuang,et al.Retrievably calculating soil moisture based on temperature vegetation drought index of vegetative land[J].Journal of Irrigation and Drainage,2018,37(10):123-128. doi: 10.13522/j.cnki.ggps.2017.0603
    [23] 张智韬,王海峰,韩文霆,等.基于无人机多光谱遥感的土壤含水率反演研究[J].农业机械学报,2018,49(2):173-181. doi: 10.6041/j.issn.1000-1298.2018.02.023

    ZHANG Zhitao,WANG Haifeng,HAN Wenting,et al.Inversion of soil moisture content based on multispectral remote sensing of UAV[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(2):173-181. doi: 10.6041/j.issn.1000-1298.2018.02.023
    [24] 李鑫星, 朱晨光, 傅泽田, 等.基于无人机多光谱图像的土壤水分检测方法研究[J].光谱学与光谱分析, 2020, 40(4): 1 238-1 242.

    LI Xinxing, ZHU Chenguang, FU Zetian, et al.Rapid detection of soil moisture content based on UAV multispectral image [J].Spectroscopy and Spectral Analysis, 2020, 40 (4): 1 238-1 242.
    [25] 赵建辉,张晨阳,闵林,等.基于特征选择和GA-BP神经网络的多源遥感农田土壤水分反演[J].农业工程学报,2021,37(11):112-120. doi: 10.11975/j.issn.1002-6819.2021.11.013

    ZHAO Jianhui,ZHANG Chenyang,MIN Lin,et al.Retrieval for soil moisture in farmland using multi-source remote sensing data and feature with GA-BP neural network[J].Transactions of the Chinese Society of Agricultural Engineering,2021,37(11):112-120. doi: 10.11975/j.issn.1002-6819.2021.11.013
    [26] RAO B R M, SHARMA R C, RAVI SANKAR T, et al.Spectral behaviour of salt-affected soils[J].International Journal of Remote Sensing, 1995, 16(12): 2 125-2 136.
    [27] 李建国, 濮励杰, 朱明, 等.土壤盐渍化研究现状及未来研究热点[J].地理学报, 2012, 67(9): 1 233-1 245.

    LI Jianguo, PU Lijie, ZHU Ming, et al.The present situation and hot issues in the salt-affected soil research[J].Acta Geographica Sinica, 2012, 67(9): 1 233-1 245.
    [28] CSILLAG F,PÁSZTOR L,BIEHL L.Spectral band selection for the characterization of salinity status of soils[J].Remote Sensing of Environment,1993,43(3):231-242. doi: 10.1016/0034-4257(93)90068-9
    [29] 扶卿华,倪绍祥,王世新,等.土壤盐分含量的遥感反演研究[J].农业工程学报,2007,23(1):48-54. doi: 10.3321/j.issn:1002-6819.2007.01.008

    FU Qinghua,NI Shaoxiang,WANG Shixin,et al.Retrieval of soil salt content based on remote sensing[J].Transactions of the Chinese Society of Agricultural Engineering,2007,23(1):48-54. doi: 10.3321/j.issn:1002-6819.2007.01.008
    [30] 杨宁,崔文轩,张智韬,等.无人机多光谱遥感反演不同深度土壤盐分[J].农业工程学报,2020,36(22):13-21. doi: 10.11975/j.issn.1002-6819.2020.22.002

    YANG Ning,CUI Wenxuan,ZHANG Zhitao,et al.Soil salinity inversion at different depths using improved spectral index with UAV multispectral remote sensing[J].Transactions of the Chinese Society of Agricultural Engineering,2020,36(22):13-21. doi: 10.11975/j.issn.1002-6819.2020.22.002
    [31] 陈俊英,姚志华,张智韬,等.大田葵花土壤含盐量无人机遥感反演研究[J].农业机械学报,2020,51(7):178-191. doi: 10.6041/j.issn.1000-1298.2020.07.021

    CHEN Junying,YAO Zhihua,ZHANG Zhitao,et al.UAV remote sensing inversion of soil salinity in field of sunflower[J].Journal of Agricultural Machinery,2020,51(7):178-191. doi: 10.6041/j.issn.1000-1298.2020.07.021
    [32] 张娟娟.土壤养分信息的光谱估测研究[D].南京: 南京农业大学, 2009.

    ZHANG Juanjuan.Estimating soil nutrient information based on spectral analysis technology[D].Nanjing: Nanjing Agricultural University, 2009.
    [33] 贾生尧.基于光谱分析技术的土壤养分检测方法与仪器研究[D].杭州: 浙江大学, 2015.

    JIA Shengyao.Research on the detection methods and instruments of soil properties useing spectral analysis technology[D].Hangzhou: Zhejiang University, 2015.
    [34] 刘波平.近红外光谱技术在多组分检测及模式识别中的应用研究[D].南京: 南京理工大学, 2011.

    LIU Boping.Study on multi-component determination and pattern analysis using near-infrared spectra technique [D].Nanjing: Nanjing University of Science and Technology, 2011.
    [35] YANG H Q, KUANG B, MOUAZEN A M.Prediction of soil TN and TC at a farm-scale using VIS-N1R spectroscopy[J].Advanced Materials Research , 2011(225/226): 1 258-1 261.
    [36] 李雪莹, 范萍萍, 刘岩, 等.多分类器融合提取土壤养分特征波长[J].光谱学与光谱分析, 2019, 39(9): 2 862-2 867.

    LI Xueying, FAN Pingping, LIU Yan, et al.Extracting characteristic wavelength of soil nutrients based on multi-classifier fusion[J].Spectroscopy and Spectral Analysis, 2019, 39 (9): 2 862-2 867.
    [37] 李军.农业信息技术[M].北京: 科学出版社, 2010.
    [38] 汪懋华.精细农业[M].北京: 中国农业大学出版社, 2011.
    [39] 孙浩然,赵志根,赵佳星,等.珠海一号高光谱遥感的表层土壤有机质含量反演方法[J].遥感信息,2020,35(4):40-46. doi: 10.3969/j.issn.1000-3177.2020.04.007

    SUN Haoran,ZHAO Zhigen,ZHAO Jiaxing,et al.Inversion of topsoil organic matter content by hyperspectral remote sensing of Zhuhai-1[J].Remote Sensing Information,2020,35(4):40-46. doi: 10.3969/j.issn.1000-3177.2020.04.007
    [40] 杨珺博,王斌,黄嘉亮,等.无人机多光谱遥感监测冬小麦拔节期根域土壤含水率[J].节水灌溉,2019(10):6-10. doi: 10.3969/j.issn.1007-4929.2019.10.002

    YANG Junbo,WANG Bin,HUANG Jialiang,et al.Monitoring soil moisture content in root zone of winter wheat at jointing stage by multispectral remote sensing of UAV[J].Water Saving Irrigation,2019(10):6-10. doi: 10.3969/j.issn.1007-4929.2019.10.002
    [41] 王延仓,顾晓鹤,朱金山,等.利用反射光谱及模拟多光谱数据定量反演北方潮土有机质含量[J].光谱学与光谱分析,2014,34(1):201-206. doi: 10.3964/j.issn.1000-0593(2014)01-0201-06

    WANG Yancang,GU Xiaohe,ZHU Jinshan,et al.Inversion of organic matter content of the north fluvo-aquic soil based on hyperspectral and multi-spectra[J].Spectroscopy and Spectral Analysis,2014,34(1):201-206. doi: 10.3964/j.issn.1000-0593(2014)01-0201-06
    [42] 王曦, 李玉环, 王瑞燕, 等.基于无人机的冬小麦拔节期表层土壤有机质含量遥感反演[J].应用生态学报, 2020, 31(7): 2 399-2 406.

    WANG Xi, LI Yuhuan, WANG Ruiyan, et al.Remote sensing inversion of surface soil organic matter at jointing stage of winter wheat based on unmanned aerial vehicle [J].Chinese Journal of Applied Ecology, 2020, 31 (7): 2 399-2 406.
    [43] 王丽萍,刘焕军,郑树峰,等.东北农牧交错带耕地土壤有机质遥感反演研究[J].土壤,2022,54(1):184-190. doi: 10.13758/j.cnki.tr.2022.01.024

    WANG Liping,LIU Huanjun,ZHENG Shufeng,et al.Soil organic matter inversion in agro-pastoral ecotone of Northeast China[J].Soils,2022,54(1):184-190. doi: 10.13758/j.cnki.tr.2022.01.024
    [44] 谭丞轩,张智韬,许崇豪,等.无人机多光谱遥感反演各生育期玉米根域土壤含水率[J].农业工程学报,2020,36(10):63-74. doi: 10.11975/j.issn.1002-6819.2020.10.008

    TAN Chengxuan,ZHANG Zhitao,XU Chonghao,et al.Soil water content inversion model in field maize root zone based on UAV multispectral remote sensing[J].Transactions of the Chinese Society of Agricultural Engineering,2020,36(10):63-74. doi: 10.11975/j.issn.1002-6819.2020.10.008
  • 加载中
图(3) / 表(3)
计量
  • 文章访问数:  40
  • HTML全文浏览量:  16
  • PDF下载量:  8
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-07-15
  • 修回日期:  2022-10-07
  • 出版日期:  2022-11-20

目录

    /

    返回文章
    返回