Please wait a minute...
img img
高级检索
地球科学进展  2009, Vol. 24 Issue (7): 793-802    DOI: 10.11867/j.issn.1001-8166.2009.07.0793
地面观测方案     
行播作物地面方向性测量的视场不确定性分析
陈玲,阎广建*,李静,余莹洁
北京师范大学地理学与遥感科学学院,北京师范大学/中国科学院遥感应用研究所遥感科学国家重点实验室,北京   100875
Footprint Uncertainty Analysis for Ground-based Multiangular Measurement of Row Crops
Chen Ling, Yan Guangjian, Li Jing, Yu Yingjie
State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing  100875, China
 全文: PDF(2108 KB)  
摘要:

行播作物以其独特的几何结构介于离散与连续植被之间。地面测量此类地物的双向反射系数(Bidirectional Reflectance Factor,BRF)特征,不可回避视场变化所引起的不确定性问题。在Kimes垄行结构模型中加入等效视场的概念,对视场进行分解,从而建立了一个行结构多角度地面测量的视场不确定性分析模型,为定量分析视场变化所引起的BRF测量误差提供了可能。利用该模型较为全面地模拟分析了视场变化对视场内四组分比例及冠层BRF的影响。结果表明:①BRF误差基本独立于植被—土壤光谱对比度。②误差与观测天顶角之间的关系复杂,前向观测表现得尤为明显。③垂直观测视场满1个垄周期后,四组分比例及冠层BRF的误差可保持较小且稳定的状态;满2个垄周期,误差达到局部最小值(局部指垂直视场含2.5个垄周期以下,不排除视场更大,误差更小的可能性)。④垂直视场若仅含0.5个垄周期,BRF误差最大值一般可高达67.8%,最小值亦可达38.7%;满1个垄周期后,BRF误差极大值降至20%以下,极小值可控制在6%以内。其中视场为1个整周期,误差范围为6%~12%;2个整周期,误差范围为0.6%~3.9%。⑤垂直视场大小为1~2个垄周期之间的非整周期,四组分比例及冠层BRF误差总体上均稍高于1个整周期,故建议在实际测量过程中,测量高度若无法满足垂直视场为2个垄周期,可优先考虑1个整周期的情况。还通过非线性最优化函数将2个模型分别与黑河实验玉米地方向性观测实测数据进行拟合,得出的结果与模拟分析的结论一致,即在垂直视场内包含2个垄周期以上的生长初期,方向性测量无需考虑视场效应;若垂直视场内不足一个垄周期(生长中期),则有必要考虑视场的不确定性。
  

关键词: 行结构视场不确定性分析模型冠层BRF垄周期误差    
Abstract:

Row crop can be classified between homogeneous and heterogeneous canopy due to its own special geometric characteristics. The footprint uncertainty problem of this kind of canopy should not be neglected in the field directional measurement. This study introduces an equivalent footprint of sensor's field of view into the original Kimes model and develops a footprint uncertainty analysis model for multiangular in situ measurements of row crops through disassembling the equivalent footprint. Both the influences of footprint uncertainty on the four component proportions (i.e. the proportion of sunlit and shaded vegetation, and sunlit and shaded soil) and canopy BRF have been analyzed: ①BRF error is nearly independent of the spectral contrast between vegetation and soil. ②The relationship between BRF error and view zenith angle is very complicated with the forward observation worse than the backward.③Both the errors of four component proportions and canopy BRF keep relatively small and steady after the nadir footprint reaches more than 1 row period. When the nadir footprint is 2 row periods, both the errors arrive at local minimum. Here the ‘local’ means the error might be smaller when the nadir footprint contains more than 2.5 row periods which is beyond the discussion of this study. ④The relative mean error range of BRF is 38.7%~67.8% when the nadir footprint contains only half row period. This range changes into 6%~12% and 0.6%~3.9% when the nadir footprint contains 1 and 2 row periods respectively.⑤Errors are somewhat higher when the nadir footprint contains non-integral period which is between 1 and 2 row periods than it contains just 1 period. So considering the one period situation before the nadir footprint reached 2 periods in the field experiment is the suggestion. This study also compares the proposed and the original Kimes model to the field directional observation of corn canopy in the Heihe River basin based on a multivariate constrained nonlinear optimization technique. The results are consistent with the simulation conclusions above, which include that the footprint uncertainty problem can be ignored when the nadir footprint reached more than 2 row periods and it′s necessary to consider the problem if the nadir footprint contains less than 1 period.

Key words: Row crop    Footprint uncertainty analysis model    Canopy BRF    Row period    Error
收稿日期: 2009-02-04 出版日期: 2009-07-10
:  P407   
基金资助:

国家重点基础研究发展计划项目“陆表生态环境要素主被动遥感协同反演理论与方法”(编号:2007CB714402);中国科学院西部行动计划(二期)项目“黑河流域遥感—地面观测同步试验与综合模拟平台建设”(编号:KZCX2-XB2-09);新世纪优秀人才支持计划联合资助.

通讯作者: 阎广建(1972-), 男,山西应县人,教授,主要从事多角度遥感、热红外遥感建模及反演以及尺度转换等方面研究.     E-mail: gjyan@bnu.edu.cn
作者简介: 陈玲(1982-),女,安徽黄山人,博士生,主要从事定量遥感方面研究. E-mail:chenling8247@126.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
陈玲
阎广建

引用本文:

陈玲,阎广建,李静,余莹洁. 行播作物地面方向性测量的视场不确定性分析[J]. 地球科学进展, 2009, 24(7): 793-802.

Chen Ling, Yan Guangjian, Li Jing, Yu Yingjie. Footprint Uncertainty Analysis for Ground-based Multiangular Measurement of Row Crops. Advances in Earth Science, 2009, 24(7): 793-802.

链接本文:

http://www.adearth.ac.cn/CN/10.11867/j.issn.1001-8166.2009.07.0793        http://www.adearth.ac.cn/CN/Y2009/V24/I7/793

[1] Sandmeier S R. Acquisition of bidirectional reflectance factor data with field goniometers[J].Remote Sensing of Environment, 2000, 73(3): 257-269.
[2] Schopfer J, Dangel S, Kneubuhler M, et al. The improved dual-view field goniometer system FIGOS[J].Sensors, 2008, 8: 5 120-5 140.
[3] Coburn C A, Peddle D R. A low-cost field and laboratory goniometer system for estimating hyperspectral bidirectional reflectance[J].Canadian Journal of Remote Sensing,2006, 32(3): 244-253.
[4] Bourgeois C S, Ohmura A, Schroff K. IAC ETH Goniospectrometer a tool for hyperspectral HDRF measurements[J].Journal of Atmospheric and Oceanic Technology,2006, 23: 573-583.
[5] Bruegge C J, Helmlinger M C, Conel J E, et al. PARABOLA III: A sphere scanning radiometer for field determination of surface anistropic reflectance functions[J].Remote Sensing Reviews,2000, 19: 75-94.
[6] Sandmeier S R, Itten K I. A field goniometer system for acquisition of hyperspectral BRDF data[J].IEEE Transactions on GeoScience and Remote Sensing,1999, 37(2): 978-986.
[7] Kimes D S. Remote sensing of row crop structure and component temperatures using directional radiometric temperatures and inversion techniques[J].Remote Sensing of Environment,1983, 13(1): 33-55.
[8] Lagouarde J P, Kerr Y H, Brunet Y. An experimental study of angular effects on surface temperature for various plant canopies and bare soils[J].Agricultural and Forest Meteorology,1995, 77(3/4): 167-190.
[9] Yu Tao, Gu Xingfa, Tian Guoliang, et al. Analyzing the errors caused by FOV effect on the ground observation of directional brightness temperature over a row structured canopy[J].Journal of Remote Sensing,2004, 8(5): 443-450.[余涛,顾行发,田国良,等.垄行作物玉米方向亮温野外测量中视场角影响的简单分析[J]. 遥感学报, 2004, 8(5): 443-450.]
[10] Li Li, Qiao Yanli, Gu Xingfa, et al. Field of view effect on the remote sensing field radiometric measurements[J].Journal of Remote Sensing,2006, 10(5): 676-682.[李丽, 乔延利, 顾行发,等.遥感地面辐射观测中的视场效应问题研究[J]. 遥感学报,2006, 10(5): 676-682.]
[11] Jackson R D, Reginato R J, Jr Pinter P J, et al. Plant canopy information extraction from composite scene reflectance of row crops[J].Applied Optics,1979, 18(22): 3 775-3 782.
[12] Verbrugghe M, Cierniewski J. Effects of Sun and view geometries on cotton bidirectional reflectance test of a geometrical model[J].Remote Sensing of Environment,1995, 54(3): 189-197.
[13] Chen Liangfu, Liu Qinhuo, Fan Wenjie, et al. A bi-directional gap model for simulating the directional thermal radiance of row crops[J].Science in China(Series D),2002, 32(4): 290-298.[陈良富, 柳钦火, 范闻捷,等.行播作物热辐射方向性孔隙率模型[J]. 中国科学:D辑,2002, 32(4): 290-298.]
[14] Yan Guangjian, Jiang Lingmei, Wang Jindi, et al. Thermal bidirectional gap probability model for row crop canopies and validation[J].Science in China(Series D), 2002, 32(10): 857-863.[阎广建, 蒋玲梅, 王锦地,等.行播作物热辐射双向间隙率模型及验证[J]. 中国科学:D辑, 2002, 32(10): 857-863.]
[15] Yu Tao, Gu Xingfa, Tian Guoliang, et al. Modeling directional brightness temperature over a maize canopy in row structure[J].Journal of Remote Sensing,2006, 10(1): 15-20.[余涛, 顾行发,田国良,等.垄行结构玉米冠层方向亮温模型研究[J]. 遥感学报,2006, 10(1):15-20.]
[16] Du Yongming. A study of seasonal variation and models of directional thermal radiance over row-planted winter wheat canopy[D].Beijing: Graduate University of Chinese Academy of Science, 2006.[杜永明. 冬小麦冠层方向性热辐射的季相变化和模型研究[D].北京:中国科学院研究生院, 2006.]

[1] 凌飞龙,李增元,陈尔学,何祺胜. 青海云杉林叶面积指数半球摄影测量方法研究[J]. 地球科学进展, 2009, 24(7): 803-809.