Comparison of Smartphone App and digital hemispherical photography for Estimating Leaf Area Index
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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.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.
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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 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 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 DHP 5.92 27.47 398617 99.93 >0.006(大间隙) LAISmart 16.54 69.81 302 0.17 DHP 15.62 72.53 294 0.07 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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