Using LiDAR data to measure the 3D green biomass of Beijing urban forest in China.
Using LiDAR data to measure the 3D green biomass of Beijing urban forest in China.
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DOI：
10.1371/journal.pone.0075920
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Zhang S
中科院分区：
文献类型：
--
作者：
He C;Convertino M;Feng Z;Zhang S
本文的目的是寻找一种新的方法来测量城市森林的三维绿色生物量，并验证其精度。在本研究中，三维绿色生物量的获取基于遥感反演模型，该模型首先对每棵立木进行地面激光扫描仪扫描，获取其点云数据，然后在数字测绘数据采集系统中打开点云图像，获得独立坐标下的高程。最后利用SPSS （Statistical Product and Service Solutions）、GIS （Geographic Information System）、RS （remote sensing）等工具以及FARO SCENE和Geomagic studio11等空间分析软件，将捕获的个体体与SPOT5（System Probatoired’observation dela Tarre）遥感图像进行关联。结果表明：北京城市森林三维绿色生物量为39912.95万m3，其中针叶林为287871万m3，阔叶林为37034.24万m3；与典型采样方式的235个野外样本数据相比，三维绿色生物量的精度在85%以上。这表明基于SPOT5图像的三维森林绿色生物量可以满足精度要求。这是对传统方法的改进，不仅为北京城市绿化指标的评价提供了依据，而且为其他城市三维绿色生物量的评价提供了一种新技术。
The purpose of the paper is to find a new approach to measure 3D green biomass of urban forest and to testify its precision. In this study, the 3D green biomass could be acquired on basis of a remote sensing inversion model in which each standing wood was first scanned by Terrestrial Laser Scanner to catch its point cloud data, then the point cloud picture was opened in a digital mapping data acquisition system to get the elevation in an independent coordinate, and at last the individual volume captured was associated with the remote sensing image in SPOT5(System Probatoired'Observation dela Tarre)by means of such tools as SPSS (Statistical Product and Service Solutions), GIS (Geographic Information System), RS (Remote Sensing) and spatial analysis software (FARO SCENE and Geomagic studio11). The results showed that the 3D green biomass of Beijing urban forest was 399.1295 million m3, of which coniferous was 28.7871 million m3 and broad-leaf was 370.3424 million m3. The accuracy of 3D green biomass was over 85%, comparison with the values from 235 field sample data in a typical sampling way. This suggested that the precision done by the 3D forest green biomass based on the image in SPOT5 could meet requirements. This represents an improvement over the conventional method because it not only provides a basis to evalue indices of Beijing urban greenings, but also introduces a new technique to assess 3D green biomass in other cities.
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影响因子：
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作者：
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通讯作者：
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