智能手机App与数字半球摄影测量叶面积指数对比研究

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doi:10.12202/j.0476-0301.2021232

洪楚翘,
屈永华^,

必威最新登录地址遥感科学国家重点实验室，必威最新登录地址地理科学学部遥感与工程研究院，北京市陆表遥感数据产品工程技术研究中心，100875，北京

基金项目:国家自然科学基金资助项目(41671333，42192581)；国家重点研发计划资助项目(2016YFC0500103)

详细信息

通讯作者:
屈永华(1972-)，男，博士，副教授. 研究方向：定量遥感. E-mail:qyh@bnu.edu.cn

中图分类号:TP391.4
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- 文章访问数:162
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- PDF下载量:29
- 被引次数:0
出版历程
- 收稿日期:2021-09-17
- 录用日期:2021-09-17
- 网络出版日期:2022-06-14
- 刊出日期:2023-02-01

Comparison of Smartphone App and digital hemispherical photography for Estimating Leaf Area Index

HONG Chuqiao,
QU Yonghua^,

State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Science and Engineering, Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, 100875, Beijing, China

摘要

摘要:基于自主开发的智能手机App（LAISmart）对针阔混交林、阔叶林和农作物3种植被类型的叶面积指数（leaf area index, LAI）进行测量，并以数字半球摄影（digital hemispherical photography，DHP）的测量结果作为参考值进行对比分析．结果表明，虽然LAISmart与DHP的LAI值总体上具有高度一致性（ R ²=0.95，RMSE=0.68），但是，LAISmart的性能受到植被叶片密集程度的影响．研究发现：LAI>3.9时，LAISmart的测量结果会明显低于DHP的测量结果；智能手机成像传感器的自动曝光模式，是引起LAISmart在测量LAI高值区域估值偏低的重要影响因素；当对LAI高值区域的LAISmart图像进行降低曝光度处理后，LAISmart和DHP的测量结果偏差得到进一步降低，且LAISmart测量结果的精度可以提高49%左右．此外，LAISmart的较窄视场角几乎不会对其测量结果产生影响，若能在调节智能手机曝光度的条件下使用LAISmart，则具有更高效率和更低成本优势的LAISmart可以成为替代DHP的有效方法．
- 叶面积指数/
- 智能手机/
- 数字半球摄影/
- 曝光
Abstract:Leaf area index (LAI) is a structural parameter that describes distribution characteristics of vegetation leaves in canopy．LAI can affect redistribution of solar radiation, photosynthesis capacity of vegetation and microclimate in vegetation growth environment. Therefore, obtaining LAI in ground measurements is of great significance to understand growth status of vegetation．Digital hemispherical photography (DHP) has been widely adopted due to its simplicity and low cost．In recent years, smartphone-based LAI measurement methods have been extensively used．However, in-depth comparison and verification between smartphone and DHP methods have not been done．Performance of smartphone for measuring LAI needs to be validated and its potential to replace DHP needs to be explored．In this paper we measured coniferous-broadleaved mixed forest, broadleaved forest and crop by self-developed smartphone APP (LAISmart)．These DHP measurements were used as reference for comparative studies．LAI values derived from LAISmart were found highly consistent with DHP ( R ²=0.95, RMSE=0.68), but performance of LAISmart was affected by density of vegetation leaves．When LAI was > 3.9 , LAISmart significantly underestimated measurements of DHP．Auto-exposure mode of smartphone imaging sensor was an important factor for LAISmart underestimations in LAI in high-value areas．When exposure of LAISmart images in LAI high-value areas are reduced, deviation between LAISmart and DHP was reduced, accuracy of LAISmart was improved by 49%．Narrow sensor field of view (FOV) of LAISmart has little effect on measurement results．These data suggest that LAISmart, with higher efficiency and lower costs, can be an alternative to DHP．
- leaf area index (LAI)/
- smartphone/
- digital hemispherical photography (DHP)/
- exposure

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图 1试验区分布及样方采样方法

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图 5LAISmart与DHP的LAI值之间的散点

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图 2LAISmart和DHP获取植被冠层图像的示意

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图 3图像间隙斑块标准化面积计算示意

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图 4LAISmart和DHP阔叶林图像的间隙斑块标准化面积频率分布

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图 6在X=3.9左右两侧测量点中，LAISmart与DHP的LAI偏差频率

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图 7在X=3.9右侧测量点中，降低曝光度后的LAISmart与DHP的LAI偏差频率

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图 8当I_LA>3.9时，降低曝光度前后的LAISmart与DHP的间隙率差值（LAISmart-DHP）频率

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图 9高密度覆盖植被中阔叶林降低曝光度前后的LAISmart图像示例

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图 10LAISmart和DHP在3种植被类型图像中大间隙斑块标准化面积的频率分布

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表 1试验区概况及获取的数据集详情

数据集	省份	植被类型	植被名称	样方数量	经度/（°）	纬度/（°）	拍摄日期
G1	福建省	针阔混交林	相思树(Acacia confusa)和马尾松(Pinus massoniana)	35	118.110	24.504	2020-03-08—04-26
G2	内蒙古自治区	阔叶林	胡杨(Populus euphratica)	8	101.135	41.990	2020-07-13—07-24
G3	甘肃省	农作物	玉米(Zea mays)	18	100.376	38.858	2020-07-17—07-22
G4	重庆市	阔叶林	桂树(Osmanthus fragrans)	16	106.315	29.756	2020-10-18—10-19

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表 22种DHP设备详情及获取的数据集

DHP设备	数字单反相机型号	鱼眼镜头型号	视场角/（°）	图像分辨率	获取的数据集
第1种	Canon EOS 6D	Samyang 8mm f/3.5	180	5472×3648	G1、G2、G3
第2种	Canon EOS 40D	Canon EF 15mm f/2.8	120	2886×1880	G4

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表 3LAISmart和DHP阔叶林图像中大小间隙斑块标准化面积与个数

间隙斑块标准化面积分类	仪器	斑块标准化面积	面积比例 /%	斑块个数	个数比例 /%
<0.006（小间隙）	LAISmart	7.15	30.19	174636	99.83
<0.006（小间隙）	DHP	5.92	27.47	398617	99.93
>0.006（大间隙）	LAISmart	16.54	69.81	302	0.17
>0.006（大间隙）	DHP	15.62	72.53	294	0.07

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表 4LAISmart和DHP在各个相对应区间内总面积的配对t检验结果

植被类型	H	P	CI_2.5	CI_97.5
针阔混交林	0	0.666	−0.008	0.013
阔叶林	0	0.726	−0.008	0.012
农作物	0	0.541	−0.004	0.008

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参考文献 (39)

[1]	CHEN J M,BLACK T A. Defining leaf area index for non-flat leaves[J]. Plant,Cell & Environment,1992,15(4):421
[2]	NEINAVAZ E,SKIDMORE A K,DARVISHZADEH R,et al. Retrieval of leaf area index in different plant species using thermal hyperspectral data[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2016,119:390doi:10.1016/j.isprsjprs.2016.07.001
[3]	YANG X B,WANG C,PAN F F,et al. Retrieving leaf area index in discontinuous forest using ICESat/GLAS full-waveform data based on gap fraction model[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2019,148:54doi:10.1016/j.isprsjprs.2018.12.010
[4]	YAN G J,HU R H,LUO J H,et al. Review of indirect optical measurements of leaf area index:recent advances,challenges,and perspectives[J]. Agricultural and Forest Meteorology,2019,265:390doi:10.1016/j.agrformet.2018.11.033
[5]	WEISS M,BARET F,SMITH G J,et al. Review of methods for in situ leaf area index (LAI) determination:part II. estimation of LAI,errors and sampling[J]. Agricultural and Forest Meteorology,2004,121(1):37
[6]	QU Y H,HAN W C,FU L Z,et al. LAINet:a wireless sensor network for coniferous forest leaf area index measurement:design,algorithm and validation[J]. Computers and Electronics in Agriculture,2014,108:200doi:10.1016/j.compag.2014.08.003
[7]	牛小桃,樊军,王胜,等. 利用鱼眼摄像机测量植被叶面积指数动态变化[J]. 应用生态学报,2018,29(10):3183
[8]	阎广建,胡容海,罗京辉,等. 叶面积指数间接测量方法[J]. 遥感学报,2016,20(5):958
[9]	JONCKHEERE I,FLECK S,NACKAERTS K,et al. Review of methods forin situleaf area index determination part I. theories,sensors and hemispherical photography[J]. Agricultural and Forest Meteorology,2004,121(1/2):19
[10]	CHIANUCCI F,CUTINI A. Digital hemispherical photography for estimating forest canopy properties:current controversies and opportunities[J]. iForest-Biogeosciences and Forestry,2012,5(6):290
[11]	FANG H L,BARET F,PLUMMER S,et al. An overview of global leaf area index (LAI):methods,products,validation,and applications[J]. Reviews of Geophysics,2019,57(3):739doi:10.1029/2018RG000608
[12]	OLIVAS P C,OBERBAUER S F,CLARK D B,et al. Comparison of direct and indirect methods for assessing leaf area index across a tropical rain forest landscape[J]. Agricultural and Forest Meteorology,2013,177:110doi:10.1016/j.agrformet.2013.04.010
[13]	姚丹丹,雷相东,余黎,等. 云冷杉针阔混交林叶面积指数的空间异质性[J]. 生态学报,2015,35(1):71
[14]	FANG H L,YE Y C,LIU W W,et al. Continuous estimation of canopy leaf area index (LAI) and clumping index over broadleaf crop fields:an investigation of the PASTIS-57 instrument and smartphone applications[J]. Agricultural and Forest Meteorology,2018,253/254:48doi:10.1016/j.agrformet.2018.02.003
[15]	LIU C W,KANG S Z,LI F S,et al. Canopy leaf area index for apple tree using hemispherical photography in arid region[J]. Scientia Horticulturae,2013,164:610doi:10.1016/j.scienta.2013.10.009
[16]	GILARDELLI C,ORLANDO F,MOVEDI E,et al. Quantifying the accuracy of Digital Hemispherical Photography for leaf area index estimates on broad-leaved tree species[J]. Sensors,2018,18(4):9
[17]	FANG H L,LI W J,WEI S S,et al. Seasonal variation of leaf area index (LAI) over paddy rice fields in NE China:intercomparison of destructive sampling,LAI-2200,Digital Hemispherical Photography (DHP),and accupar methods[J]. Agricultural and Forest Meteorology,2014,198:126
[18]	WANG J X,XIONG Q C,LIN Q N,et al. Feasibility of using mobile phone to estimate forest leaf area index:a case study in Yunnan Pine[J]. Remote Sensing Letters,2018,9(2):180doi:10.1080/2150704X.2017.1399470
[19]	RUDIC T E,MCCULLOCH L A,CUSHMAN K. Comparison of smartphone and drone lidar methods for characterizing spatial variation in PAI in a tropical forest[J]. Remote Sensing,2020,12(11):1765doi:10.3390/rs12111765
[20]	PATRIGNANI A,OCHSNER T E. Canopeo:a powerful new tool for measuring fractional green canopy cover[J]. Agronomy Journal,2015,107(6):2312doi:10.2134/agronj15.0150
[21]	TICHý L. Field test of canopy cover estimation by hemispherical photographs taken with a smartphone[J]. Journal of Vegetation Science,2016,27(2):427doi:10.1111/jvs.12350
[22]	CONFALONIERI R,FOI M,CASA R,et al. Development of an App for estimating leaf area index using a smartphone. trueness and precision determination and comparison with other indirect methods[J]. Computers and Electronics in Agriculture,2013,96:67doi:10.1016/j.compag.2013.04.019
[23]	DE BEI R,FUENTES S,GILLIHAM M,et al. VitiCanopy:a free computer App to estimate canopy vigor and porosity for grapevine[J]. Sensors,2016,16(4):585doi:10.3390/s16040585
[24]	BAUER J, SIEGMANN B, JARMER T, et al. Smart fLAIr: a smartphone application for fast LAI retrieval using ambient light sensors[C]// 2016 IEEE Sensors Applications Symposium (SAS). Catania, Italy: IEEE Press, 2016: 1-6
[25]	QU Y H,MENG J H,WAN H W,et al. Preliminary study on integrated wireless smart terminals for leaf area index measurement[J]. Computers and Electronics in Agriculture,2016,129:56doi:10.1016/j.compag.2016.09.011
[26]	ORLANDO F,MOVEDI E,PALEARI L,et al. Estimating leaf area index in tree species using the pocket LAI smart App[J]. Applied Vegetation Science,2015,18(4):716doi:10.1111/avsc.12181
[27]	ORLANDO F,MOVEDI E,CODUTO D,et al. Estimating leaf area index (LAI) in vineyards using the pocket LAI smart-App[J]. Sensors,2016,16(12):2004doi:10.3390/s16122004
[28]	CAMPOS-TABERNER M,GARCíA-HARO F J,CONFALONIERI R,et al. Multitemporal monitoring of plant area index in the valencia rice district with pocket LAI[J]. Remote Sensing,2016,8(3):202doi:10.3390/rs8030202
[29]	QU Y H,WANG J L,SONG J,et al. Potential and limits of retrieving conifer leaf area index using smartphone-based method[J]. Forests,2017,8(6):217doi:10.3390/f8060217
[30]	CASA R, UPRETI D, PELOSI F. Measurement and estimation of leaf area index (LAI) using commercial instruments and smartphone-based systems[C]//IOP conference series: earth and environmental science. Ancona, Italy: IOP Publishing Ltd, 2019: 012006
[31]	OTSU N. A threshold selection method from gray-level Histograms[J]. IEEE Transactions on Systems,Man,and Cybernetics,1979,9(1):62doi:10.1109/TSMC.1979.4310076
[32]	NILSON T. A theoretical analysis of the frequency of gaps in plant stands[J]. Agricultural Meteorology,1971,8:25doi:10.1016/0002-1571(71)90092-6
[33]	GOUDRIAAN J. The bare bones of leaf-angle distribution in radiation models for canopy photosynthesis and energy exchange[J]. Agricultural and Forest Meteorology,1988,43(2):155doi:10.1016/0168-1923(88)90089-5
[34]	苑振皓. 曝光对半球摄影法测量叶面积指数及其季节变化的影响[D]. 哈尔滨: 东北林业大学, 2019
[35]	WEISS M, BARET F. CAN_EYE V6. 4.91 user manual [EB/OL]. (2017-10-10)[2021-04-18]. https://www6.paca.inrae.fr/can-eye/ content/ download/3052/30819/version/4/file/CAN_EYE_User_Manual.pdf
[36]	MACFARLANE C,RYU Y,OGDEN G N,et al. Digital canopy photography:exposed and in the raw[J]. Agricultural and Forest Meteorology,2014,197:244doi:10.1016/j.agrformet.2014.05.014
[37]	ZHU X,SKIDMORE A K,WANG T J,et al. Improving leaf area index (LAI) estimation by correcting for clumping and woody effects using terrestrial laser scanning[J]. Agricultural and Forest Meteorology,2018,263:276doi:10.1016/j.agrformet.2018.08.026
[38]	ZHANG Y,CHEN J M,MILLER J R. Determining digital hemispherical photograph exposure for leaf area index estimation[J]. Agricultural and Forest Meteorology,2005,133(1):166
[39]	BECKSCHAFER P,SEIDEL D,KLEINN C,et al. On the exposure of hemispherical photographs in forests[J]. iForest - Biogeosciences and Forestry,2013,6(4):228doi:10.3832/ifor0957-006