YANG Xiguang, YU Ying, FAN Wenyi. Analysis of Scale Difference Between Forest Canopy and Background Reflectances[J]. Geomatics and Information Science of Wuhan University, 2020, 45(4): 511-516. DOI: 10.13203/j.whugis20180254
Citation: YANG Xiguang, YU Ying, FAN Wenyi. Analysis of Scale Difference Between Forest Canopy and Background Reflectances[J]. Geomatics and Information Science of Wuhan University, 2020, 45(4): 511-516. DOI: 10.13203/j.whugis20180254

Analysis of Scale Difference Between Forest Canopy and Background Reflectances

Funds: 

The National Natural Science Foundation of China 31870621

The National Natural Science Foundation of China 31500519

The National Natural Science Foundation of China 31500518

More Information
  • Author Bio:

    YANG Xiguang, PhD, associate professor, specializes in the theories and methods of remote sensing and GIS. yangxiguang21@163.com

  • Corresponding author:

    FAN Wenyi, PhD, professor.fanwy@163.com

  • Received Date: January 21, 2019
  • Published Date: April 04, 2020
  • As an important part of forest ecosystem, forest understory plays an important role in maintaining plant diversity and stability of forest ecosystem. However, the scale difference between canopy reflectance and forest background reflectance is not clear, which is very limited in the study of forest understory by using single-angle optical remote sensing data. In this study, the relationship between forest background reflectance and canopy reflectance under different forest structure was analyzed by using geometric optical model 4-scale. The results show that the scale difference between forest background reflectance and canopy reflectance varies with the forest structure, and cannot be eliminated by vegetation index calculation. There is a significant linear relationship between forest background reflectance and forest canopy reflectance. The linear relationship varies with the wavelength and forest structure. And the model parameters of this linear relationship are highly related with leaf area index (LAI). Coefficients of determination at 680 nm and 865 nm are 0.881, 0.834 3, 0.890 6 and 0.880 3, respectively. This work provides a reference for the study of weakening or eliminating the scale difference between forest canopy and background reflectances.
  • [1]
    Shugart H H, Saatchi S, Hall F G. Importance of Structure and Its Measurement in Quantifying Function of Forest Ecosystems[J]. Journal of Geophysical Research Biogeosciences, 2015, 115(G2):333-345 doi: 10.1029/2009JG000993
    [2]
    焦桐, 刘荣高, 刘洋, 等.林下植被遥感反演研究进展[J].地球信息科学学报, 2014, 16(4):602-608 http://d.old.wanfangdata.com.cn/Periodical/dqxxkx201404013

    Jiao Tong, Liu Ronggao, Liu Yang, et al. The Progress of Forest Understory Retrieval from Remote Sensing[J]. Journal of Geo-Information Science, 2014, 16(4):602-608 http://d.old.wanfangdata.com.cn/Periodical/dqxxkx201404013
    [3]
    周会萍, 牛德奎, 张继红, 等.湿地松人工林群落林下植被物种多样性研究[J].江西农业大学学报, 2006, 28(1):78-83 doi: 10.3969/j.issn.1000-2286.2006.01.016

    Zhou Huiping, Niu Dekui, Zhang Jihong, et al. Studies on the Species Diversity in Undergrowth Vegetation of Artificial P. elliottii Forest Communities[J]. Acta Agriculturae Universitatis Jiangxiensis, 2006, 28(1):78-83 doi: 10.3969/j.issn.1000-2286.2006.01.016
    [4]
    Hart S A, Chen H Y H. Understory Vegetation Dynamics of North American Boreal Forests[J]. Critical Reviews in Plant Sciences, 2006, 25(4):381-397 doi: 10.1080/07352680600819286
    [5]
    朱喜, 何志斌, 杜军, 等.林下植被组成和功能研究进展[J].世界林业研究, 2014, 27(5):24-30 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=sjlyyj201405005

    Zhu Xi, He Zhibin, Du Jun, et al. Function and Composition of Understory Vegetation:Recent Advances and Trends[J]. World Forestry Research, 2014, 27(5):24-30 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=sjlyyj201405005
    [6]
    D'Amato A W, Orwig D A, Foster D R. Understory Vegetation in Old-growth and Second-growth Tsuga Canadensis Forests in Western Massachusetts[J]. Forest Ecology and Management, 2009, 257(3):1043-1052 doi: 10.1016/j.foreco.2008.11.003
    [7]
    Pisek J, Chen J M. Mapping Forest Background Reflectivity over North America with Multi-angle Imaging SpectroRadiometer(MISR)Data[J]. Remote Sensing of Environment, 2009, 113(11):2412-2423 doi: 10.1016/j.rse.2009.07.003
    [8]
    Jiao T, Liu R, Liu Y, et al. Mapping Global Seasonal Forest Background Reflectivity with Multiangle Imaging Spectroradiometer Data[J]. Journal of Geophysical Research:Biogeosciences, 2014, 119(6):1063-1077 doi: 10.1002/2013JG002493
    [9]
    Wing B M, Ritchie M W, Boston K, et al. Prediction of Understory Vegetation Cover with Airborne LiDAR in an Interior Ponderosa Pine Forest[J]. Remote Sensing of Environment, 2012, 124(9):730-741 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=c38a52d0244940c500921556221606e4
    [10]
    Korpela I S. Mapping of Understory Lichens with Airborne Discrete-return LiDAR Data[J]. Remote Sensing of Environment, 2008, 112(10):3891-3897 doi: 10.1016/j.rse.2008.06.007
    [11]
    Yang X, Yu Y, Fan W. Chlorophyll Content Retrieval from Hyperspectral Remote Sensing Imagery[J]. Environmental Monitoring & Assessment, 2015, 187(7):1-13 http://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ023953957/
    [12]
    Chen J M, Leblanc S G. A Four-scale Bidirectional Reflectance Model Based on Canopy Architecture[J]. IEEE Transactions on Geoscience & Remote Sensing, 1997, 35(5):1316-1337 doi: 10.1109/36.628798
    [13]
    杨曦光, 于颖, 黄海军, 等.森林冠层氮含量遥感估算[J].红外与毫米波学报, 2012, 31(6):536-543 http://d.old.wanfangdata.com.cn/Periodical/hwyhmb201206011

    Yang Xiguang, Yu Ying, Huang Haijun, et al. Estimation of Forest Canopy Nitrogen Content Based on Remote Sensing[J]. Journal of Infrared & Millimeter Waves, 2012, 31(6):536-543 http://d.old.wanfangdata.com.cn/Periodical/hwyhmb201206011
    [14]
    于颖, 宋张亮, 范文义, 等.植被冠层光谱和叶片光谱的尺度转换[J].武汉大学学报·信息科学版, 2018, 43(10):1560-1565, 1573 http://ch.whu.edu.cn/CN/Y2018/V43/I10/1560

    Yu Ying, Song Zhangliang, Fan Wenyi, et al. Scale Conversion from Canopy Spectra to Leaf Spectra[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10):1560-1565, 1573 http://ch.whu.edu.cn/CN/Y2018/V43/I10/1560
    [15]
    叶泽田, 顾行发, 刘先林, 等.遥感模拟图像应用于不同传感器光谱性能分析[J].武汉大学学报·信息科学版, 1999, 24(4):295-299 http://ch.whu.edu.cn/CN/Y1999/V24/I4/295

    Ye Zetian, Gu Xingfa, Liu Xianlin, et al. Analysis of Spectral Characteristics Among Different Sensors by Use of Simulated RS Images[J]. Geomatics and Information Science of Wuhan University, 1999, 24(4):295-299 http://ch.whu.edu.cn/CN/Y1999/V24/I4/295
  • Related Articles

    [1]MA Jingzhen, SUN Qun, WEN Bowei, ZHOU Zhao, LU Chuanwei, LÜ Zheng, SUN Shijie. A Hybrid Multi-feature Road Network Selection Method Based on Trajectory Data[J]. Geomatics and Information Science of Wuhan University, 2022, 47(7): 1009-1016. DOI: 10.13203/j.whugis20190480
    [2]YANG Hao, HE Zongyi, CHEN Huayang, ZHOU Zhuanxiang, FAN Yong. A Method for Automatic Generalization of Urban Settlements Considering Road Network[J]. Geomatics and Information Science of Wuhan University, 2018, 43(6): 965-970. DOI: 10.13203/j.whugis20160094
    [3]CAO Weiwei, ZHANG Hong, HE Jing, LAN Tian. Road Selection Considering Structural and Geometric Properties[J]. Geomatics and Information Science of Wuhan University, 2017, 42(4): 520-524. DOI: 10.13203/j.whugis20140862
    [4]YANG Lin, WAN Bo, WANG Run, ZUO Zejun, AN Xiaoya. Matching Road Network Based on the Structural Relationship Constraint of Hierarchical Strokes[J]. Geomatics and Information Science of Wuhan University, 2015, 40(12): 1661-1668. DOI: 10.13203/j.whugis20140295
    [5]tianjin g, renchan g, wangyihen g, xiongfu q uan, leiyin g zhe. imp rovementofself-best-fitstrate gyforstrokebuildin g[J]. Geomatics and Information Science of Wuhan University, 2015, 40(9): 1209-1214. DOI: 10.13203/j .whu g is20140455
    [6]LIU Hailong, QIAN Haizhong, WANG Xiao, HE Haiwei. Road Networks Global Matching Method Using Analytical Hierarchy Process[J]. Geomatics and Information Science of Wuhan University, 2015, 40(5): 644-651. DOI: 10.13203/j.whugis20130350
    [7]TIAN Jing, HE Qingsong, YAN Fen. Formalization and New Algorithm of stroke Generation in Road Networks[J]. Geomatics and Information Science of Wuhan University, 2014, 39(5): 556-560. DOI: 10.13203/j.whugis20120127
    [8]TIAN Jing, WU Dang, ZHAN Yifei. Degree Correlation of Urban Street Networks[J]. Geomatics and Information Science of Wuhan University, 2014, 39(3): 332-334. DOI: 10.13203/j.whugis20120675
    [9]CHEN Jun, HU Yungang, ZHAO Renliang, LI Zhilin. Road Data Updating Based on Map Generalization[J]. Geomatics and Information Science of Wuhan University, 2007, 32(11): 1022-1027.
    [10]HUANG Shuqiang, SUN Chengzhi, FU Zhongliang. License Plate Binarization Algorithm Based on the Features of Characters' Strokes[J]. Geomatics and Information Science of Wuhan University, 2003, 28(1): 71-73,79.
  • Cited by

    Periodical cited type(9)

    1. 赵天明,孙群,马京振,张付兵,温伯威. 融合路段和stroke特征的道路自动选取方法. 地球信息科学学报. 2024(12): 2673-2685 .
    2. 郭漩,钱海忠,王骁,刘俊楠,任琰,赵钰哲,陈国庆. 多源道路智能选取的本体知识推理方法. 测绘学报. 2022(02): 279-289 .
    3. 马京振,孙群,温伯威,周炤,陆川伟,吕峥,孙士杰. 结合轨迹数据的混合多特征道路网选取方法. 武汉大学学报(信息科学版). 2022(07): 1009-1016 .
    4. 朱余德,杨敏,晏雄锋. 利用图卷积神经网络的道路网选取方法. 北京测绘. 2022(11): 1455-1459 .
    5. 韩远,王中辉,徐智邦,余贝贝. 结合引力场理论的道路自动选取方法. 测绘科学. 2021(01): 189-195 .
    6. 韩远,王中辉,禄小敏. POI辅助下的道路选取. 测绘科学. 2021(04): 165-171 .
    7. 陈晓东,余劲松弟. 顾及语义关联信息的道路选取方法. 海南大学学报(自然科学版). 2021(03): 227-234 .
    8. 王晓妍. 土地利用图中线状要素综合的质量评价. 测绘通报. 2020(04): 116-120 .
    9. 冯云,朱素华,孙益清,王金鑫. 郑州轨道交通5号线开通对城市交通格局的影响. 城市勘测. 2020(04): 54-58 .

    Other cited types(11)

Catalog

    Article views PDF downloads Cited by(20)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return