Scientia Agricultura Sinica ›› 2012, Vol. 45 ›› Issue (17): 3486-3496.doi: 10.3864/j.issn.0578-1752.2012.17.004

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

Retrieving LAI of Winter Wheat Based on Sensitive Vegetation ndex by the Segmentation Method

 LI  Xin-Chuan, XU  Xin-Gang, BAO  Yan-Song, HUANG  Wen-Jiang, LUO  Ju-Hua, DONG  Ying-Ying, SONG  Xiao-Yu, WANG  Ji-Hua   

  1. 1.南京信息工程大学气象灾害省部共建教育部重点实验室，南京210044
    2.南京信息工程大学大气物理学院，南京210044
    3.北京农业信息技术研究中心，北京 100097
    4.中国科学院对地观测与数字地球中心，北京 100190
  • Received:2012-02-15 Online:2012-09-01 Published:2012-09-01

PDF

1473

Cited

18

Abstract: 【Objective】The method of inversion leaf area index (LAI) using a single vegetation index (VI) is influenced by different degrees of saturability and soil background. This paper proposed a method choosing sensitive vegetation index by the segmentation method to form optimal VI combination, and to improve the accuracy of LAI inversion.【Method】In this study the ACRM radiation transmission model was used to simulate data, and the ground measured spectrum data were obtained. The study analyzed soil sensitivity and saturability about the common vegetation index to determine the segment point of LAI, and chose the best vegetation index based on segment point of LAI to form a combination VI for achieving the final inversion of the LAI. This method was also used in the regional winter wheat LAI inversion application with the Landsat5 TM data. 【Result】The analysis showed that, LAI = 3 was the more appropriate segment point, and the use of vegetation index segment combination OSAVI (LAI ≤3) + TGDVI (LAI＞3) partly overcame soil factors and the saturation problems. The joint inversion results were significantly superior to the single vegetation index retrieval accuracy.【Conclusion】LAI was effectively inversed with the higher accuracy by choosing the best vegetation index through the segmentation method.

Key words: winter wheat, leaf area index (LAI), vegetation index, segmentation inversion, remote sensing

[1]Chen J M, Black T A. Defining leaf area index for non-flat leaves. Plant, Cell and Environment, 1992, 15(4): 421-429.

[2]王纪华, 赵春江, 黄文江. 农业定量遥感基础与应用. 北京: 科学出版社, 2008.

Wang J H, Zhao C J, Huang W J. Basis and Application of Agricultural Quantitative Remote Sensing. Beijing: Science Press, 2010. (in Chinese)

[3]张佳华, 张国平, 王培娟. 植被遥感. 北京: 科学出版社, 2010.

Zhang J H, Zhang G P, Wang P J. Vegetation and Ecological Remote Sensing. Beijing: Science Press, 2010. (in Chinese)

[4]李映雪, 朱 艳, 戴廷波, 田永超, 曹卫星. 小麦叶面积指数与冠层反射光谱的定量关系. 应用生态学报,2006, 17(8): 1443-1447.

Li Y X, Zhu Y, Dai Y B, Tian Y C, Cao W X. Quantitative relationships between leaf area index and canopy reflectance spectra of wheat. Journal of Applied Ecology, 2006, 17(8): 1443-1447. (in Chinese)

[5]陈雪洋, 蒙继华, 杜 鑫, 张飞飞, 张 淼, 吴炳方. 基于环境星CCD数据的冬小麦叶面积指数遥感监测模型研究. 国土资源遥感, 2010, 84(2): 55-62.

Chen X Y, Meng X H, Du X, Zhang F F, Zhang M, Wu B F. The monitoring of the winter wheat leaf area index based on HJ-1 CCD date. Remote Sensing for Land & Resource, 2010, 84(2): 55-62. (in Chinese)

[6]刘占宇, 黄敬峰, 王福民, 王 渊. 估算水稻叶面积指数的调节型归一化植被指数. 中国农业科学, 2008, 41(10): 3350-3356.

Liu Z Y, Hang J F, Wang F M, Wang Y. Adjusted-normalized difference vegetation index for estimating leaf area index of rice. Scientia Agriculture Sinica, 2008, 41(10): 3350-3356. (in Chinese)

[7]赵英时. 遥感应用分析原理与方法. 北京: 科学出版社, 2003.

Zhao Y S. The Principle and Method of Analysis of Remote Sensing Application. Beijing: Science Press, 2003. (in Chinese)

[8]田庆久, 闵祥军. 植被指数研究进展. 地球科学进展, 1998, 13(4): 327-333.

Tian Q J, Min X J. Advances in study on vegetation indices. Advance in Earth Science, 1998, 13(4): 327-333. (in Chinese)

[9]Houborg R, Boegh E. Mapping leaf chlorophyll and leaf area index using inverse and forword canopy reflectance modeling and SPOT reflectance data. Remote Sensing of Environment, 2008, 112(1): 186-202.

[10]Martinez-Beltran C, Jochum M A, Osann Calera A, Melia J. Multisensor comparison of NDVI for a semi-arid environment in Spain. International Journal of Remote Sensing, 2009, 30(5):1355-1384.

[11]Meroni M, Colombo R, Panigada C. Inversion of a radiative transfer model with hyperspectral observations for LAI mapping in poplar plantations. Remote Sensing of Environment, 2004, 92(2):195-206.

[12]Kaufman Y J, Tanre D. Atmospherically resistant vegetation index (ARVI) for EOS-MODIS. IEEE Transaction on Geoscience and Remote Sensing, 1992, 30(2):261-270.

[13]Richardson A J, Wiegand C L. Distinguishing vegetation from soil background information. Photogrammetry Enginerring & Remote Sensing, 1977, 43(12): 1541-1552.

[14]Liu H Q, Huete A R. A feedback based modification of the NDVI to minimize canopy background and atmosphere noise. IEEE Transaction on Geoscience and Remote Sensing, 1995, 33(2):457-465.

[15]Gitelson A A, Kaufman Y J, Merzlyak M N. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment, 1996, 58(3): 289-298.

[16]Gong P, Pu R, Biging G, Larrieu M R. Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(6): 1355-1362.

[17]Qi J, Chehbouni A L, Huete A R, Kerr Y H, Sorooshian S. A modified soil adjusted vegetation index(MSAVI). Remote Sensing of Environment, 1994, 48(2):119-126.

[18]Chen J M. Evaluation of vegetation indices and modi?ed simple ratio for boreal applications. Canadian Journal of Remote Sensing, 1996, 22(3): 229-242.

[19]Rouse J W, Haas R H, Schell J A, Deering D W. Monitoring vegetation systems in the great plain with ERTS. Proceedings of the 3rd ERTS Symposium, 1973, 1: 48-62.

[20]Goel N S, Quin W. In?uences of canopy architecture on relationships between various vegetation indexes and LAI and FPAR: a computer simulation. Remote Sensing of Environment, 1994, 10(4):309-347.

[21]Rondeaux G, Steven M, Baret F. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, 1996, 55(2): 95-107.

[22]Roujean J L, Breon F M. Estimating PAR absorbed by vegetation from bidirectional re?ectance measurements. Remote Sensing of Environment, 1995, 51(3): 375- 384.

[23]Jordan C F. Derivation of leaf area index from quality of light on the forest floor. Ecology, 1969, 50: 663-666.

[24]Huete A R. A soil adjusted vegetation index SAVI. Remote Sensing of Environment, 1988, 25(3):295-309.

[25]唐世浩, 朱启疆, 王锦地, 周宇宇, 赵 峰. 三波段梯度差植被指数的理论基础及其应用. 中国科学: D辑,2003,33(11): 1094-1102.

Tang S H, Zhu Q J, Wang J D, Zhou Y Y, Zhao F. Theoretical bases and application of three gradient difference vegetation index. Science in China: Series D, 2003, 33(11): 1094-1102. (in Chinese)

[26]Broge N H, Leblanc E. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment, 2001, 76(2): 156-172.

[27]Kuusk A. Two-layer canopy reflectance model ACRM User Guide, 2007, Version 07.

[28]姜志伟, 陈仲新, 任建强. 基于ACRM辐射传输模型的植被叶面积指数遥感反演. 中国农业资源与区划, 2011, 32(1): 57-63.

Jiang Z W, Chen Z X, Ren J Q. The inversion of vegetation leaf area index based on the canopy radiative transfer meodel ACRM. Chinese Journal of Agricultural Resources and Regional Planning, 2011, 32(1): 57-63. (in Chinese)

[29]Bicheron P, Leroy M. A method of biophysical parameter retrieval at global scale by inversion of a vegetation reflectance model. Remote Sensing of Environment, 1999, 67(3):251-266.

[30]冯 晓, 郑国清, 乔 淑, 胡 峰, 马中杰. 基于冠层反射光谱的夏玉米 LAI 估算模型研究. 玉米科学, 2008, 16(6):86-89.

Feng X, Zheng G Q, Qian S, Hu F, Ma Z J. Estimation models of summer maize LAI based on canopy reflectance spectral. Journal of Maize Sciences, 2008, 16(6):86-89. (in Chinese)

[31]Wang F M, Huang J F, Tang Y L, Wang X Z. New vegetation index and its application in estimating leaf area index of rice. Rice Science, 2007, 14(3) : 195-203.

[32]董莹莹, 王纪华, 李存军, 杨贵军, 宋晓宇, 顾晓鹤, 黄文江. 基于数据分割与主成分分析的LAI遥感估算. 红外与毫米波学报, 2011,20(2): 124-130.

Dong Y Y, Wang J H, Li C J, Yang G J, Song X Y, Gu X H, Huang W J. Estimating leaf area index from remote sensing data: based on data segmentation and principal component analysis. Journal of Infrared and Millimeter Waves, 2011, 20(2): 124-130. (in Chinese)

[33]柏军华, 李少昆, 王克如, 张小均, 肖春华, 隋学艳. 棉花叶面积指数冠层反射率光谱响应及其反演. 中国农业科学, 2007, 40(1): 63-69.

Bai J H, Li S K, Wang K R, Zhang X J, Xiao C H, Sui X Y. The response of canopy reflectance spectrum for the cotton LAI and LAI inversion. Scientia Agriculture Sinica, 2007, 40(1): 63-69. (in Chines)
[1] ZHU Qi, JIA ZhenPeng, Tahir SHAH, XU ChenSheng, LI ZhiQi, LÜ HuiShuai, ZHU PengChao, WEI XiaoMin, HUANG DongLin, SUN YanNi, CAO WeiDong, GAO YaJun, WANG ZhaoHui, ZHANG DaBin. Green Manure Crops Combined with Enhanced-Efficiency Products Reduced Greenhouse Gas Emissions and Carbon Footprints in Dryland Wheat Fields [J]. Scientia Agricultura Sinica, 2026, 59(7): 1507-1522.
[2] QIAN Jin, LI YingXue, WU Fang, ZOU XiaoChen. Improved Leaf Phosphorus Content Estimation of Winter Wheat Using Ensemble Hyperspectral Dimensionality Reduction Method [J]. Scientia Agricultura Sinica, 2026, 59(4): 781-792.
[3] KONG Yuan, CUI ShaSha, LI Mei, LI Jian, YANG SiYu, FANG Feng, LIU ShuaiShuai, LIU MingPing, ZENG Yan, GAO XingXiang, BAI LianYang. Spatiotemporal Distribution Dynamics of Five Grass Weed Species Including Lolium multiflorum in Winter Wheat Fields of the Huang- Huai-Hai Region [J]. Scientia Agricultura Sinica, 2026, 59(4): 807-823.
[4] XIAN QingLin, XIAO JianKe, GAO AQing, GAO LiChuang, LIU Yang. Effects of Planting Patterns Combined with Soil Moisture Measurement and Supplementary Irrigation on the Yield and Water Use Efficiency of Winter Wheat [J]. Scientia Agricultura Sinica, 2026, 59(3): 589-601.
[5] LÜ XuDong, SUN ShiYuan, LI YaNan, LIU YuLong, WANG YanQun, FU Xin, ZHANG JiaYing, NING Peng, PENG ZhengPing. Effects of Intelligent Mechanized Layered Fertilization on Root-Soil Nutrient Distribution and Yield in Wheat Fields [J]. Scientia Agricultura Sinica, 2026, 59(1): 129-146.
[6] TANG HuaJun, WU WenBin, YU QiangYi, SHI Yun, DUAN YuLin, LI WenJuan, QIAN JianPing, SONG Qian, XIA Lang, LI HuiBin, SU BaoFeng, FAN BeiLei, HU Qiong, YE JianQiu, ZHANG Shuai. Developing a Lightweight Multimodal Model for Cropland Remote Sensing Monitoring [J]. Scientia Agricultura Sinica, 2026, 59(1): 78-89.
[7] PU LiXia, ZHANG JiaRui, YE JianPing, HUANG XiuLan, FAN GaoQiong, YANG HongKun. The Combined Effects of 16, 17-Dihydro Gibberellin A5 and Straw Mulching on Tillering and Grain Yield of Dryland Wheat [J]. Scientia Agricultura Sinica, 2025, 58(9): 1735-1748.
[8] SHI Fan, LI WenGuang, YI ShuSheng, YANG Na, CHEN YuMeng, ZHENG Wei, ZHANG XueChen, LI ZiYan, ZHAI BingNian. The Variation Characteristics of Soil Organic Carbon Fractions Under the Combined Application of Organic and Inorganic Fertilizers [J]. Scientia Agricultura Sinica, 2025, 58(4): 719-732.
[9] FANG KangRui, DING ShiJie, CHEN YuShan, YANG BingGeng, GUO TengFei, XU XinPeng, ZHAO ShiCheng, WANG XiuBin, HUANG ShaoMin, QIU ShaoJun, HE Ping, ZHOU Wei. In-Season Release Rate of Nitrogen and Phosphorus in Manure Fertilizers During the Wheat Season in Typical Fluvo-Aquic Soil Under the Combined Application of Chemical and Manure Fertilizers [J]. Scientia Agricultura Sinica, 2025, 58(24): 5234-5246.
[10] LIANG Xue, JIANG Yan, WEI ChangZhou, XUE Bing, LI FangFang, CUI YiRui, ZHANG XiaRan. Research on Soil Moisture Diagnosis Model of Maize Farmland Based on Remote Sensing of Unmanned Aerial Vehicles [J]. Scientia Agricultura Sinica, 2025, 58(23): 4979-4992.
[11] HU Jie, MA HaiRong, LUO ZhiQing, CHEN PingTing, ZHENG MingXue, GUAN Bo, XU BaoDong, SONG Qian. Spatiotemporal Analysis of Cropland Cropping Intensity in Hubei Province from 2000 to 2021 by Integrating Multi-Scale Remote Sensing Imagery [J]. Scientia Agricultura Sinica, 2025, 58(22): 4638-4655.
[12] LEI MingKuo, ZHA Yan, WANG Li, CHENG Gang, WEN CaiYun, YIN ZuoTang, LU Miao. Spatial Prediction of Deep Soil Salinization Based on Layered Modeling Using UAV Imagery [J]. Scientia Agricultura Sinica, 2025, 58(20): 4070-4084.
[13] SHE YingJun, ZHOU ZiZhe, WU Ming, GUO Wei, SHI ChangJian, HU Chao, LI Ping. Effects of Groundwater Depth and Nitrogen Application on the Distribution of Soil Water and Salt and the Nutrient Absorption and Utilization of Winter Wheat [J]. Scientia Agricultura Sinica, 2025, 58(20): 4285-4304.
[14] SHAO MingChao, AN JingWei, LIU BoRui, WU JianShuang, ZHANG Qi, YAO Xia, CHENG Tao, JIANG ChongYa, CAO WeiXing, ZHENG HengBiao, ZHU Yan. Comprehensive Assessment of Wheat Seedling Growth Status Based on Multimodal Data [J]. Scientia Agricultura Sinica, 2025, 58(19): 3857-3871.
[15] WANG RongRong, XU NingLu, HUANG XiuLi, ZHAO KaiNan, HUANG Ming, WANG HeZheng, FU GuoZhan, WU JinZhi, LI YouJun. Effects of One-Off Irrigation and Nitrogen Fertilizer Management on Grain Yield and Quality in Dryland Wheat [J]. Scientia Agricultura Sinica, 2025, 58(1): 43-57.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备09089781号-30
Copyright 2018 © Editorial office of Scientia Agricultura Sinica
Tel: 86-010-82106279    E-mail: zgnykx@mail.caas.net.cn
Supported by Beijing Magtech Co.Ltd