期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Estimation of effective plant area index for South Korean forests using LiDAR system 被引量:7
1
作者 KWAK Doo-Ahn LEE Woo-Kyun +3 位作者 KAFATOS Menas SON Yowhan CHO Hyun-Kook LEE Seung-Ho 《Science China(Life Sciences)》 SCIE CAS 2010年第7期898-908,共11页
Light Detection and Ranging(LiDAR) systems can be used to estimate both vertical and horizontal forest structure.Woody components,the leaves of trees and the understory can be described with high precision,using geo-r... Light Detection and Ranging(LiDAR) systems can be used to estimate both vertical and horizontal forest structure.Woody components,the leaves of trees and the understory can be described with high precision,using geo-registered 3D-points.Based on this concept,the Effective Plant Area Indices(PAIe) for areas of Korean Pine(Pinus koraiensis),Japanese Larch(Larix leptolepis) and Oak(Quercus spp.) were estimated by calculating the ratio of intercepted and incident LIDAR laser rays for the canopies of the three forest types.Initially,the canopy gap fraction(GLiDAR) was generated by extracting the LiDAR data reflected from the canopy surface,or inner canopy area,using k-means statistics.The LiDAR-derived PAIe was then estimated by using GLIDAR with the Beer-Lambert law.A comparison of the LiDAR-derived and field-derived PAIe revealed the coefficients of determination for Korean Pine,Japanese Larch and Oak to be 0.82,0.64 and 0.59,respectively.These differences between field-based and LIDAR-based PAIe for the different forest types were attributed to the amount of leaves and branches in the forest stands.The absence of leaves,in the case of both Larch and Oak,meant that the LiDAR pulses were only reflected from branches.The probability that the LiDAR pulses are reflected from bare branches is low as compared to the reflection from branches with a high leaf density.This is because the size of the branch is smaller than the resolution across and along the 1 meter LIDAR laser track.Therefore,a better predictive accuracy would be expected for the model if the study would be repeated in late spring when the shoots and leaves of the deciduous trees begin to appear. 展开更多
关键词 leaf area INDEX PLANT area INDEX LIDAR k-means clustering gap FRACTION beer-lambert law
原文传递
利用激光雷达数据估算韩国森林有效植被面积指数 被引量:1
2
作者 KWAK Doo-Ahn LEE Woo-Kyun +1 位作者 KAFATOS Menas CHO Hyun-Kook 《中国科学:生命科学》 CSCD 北大核心 2010年第7期678-678,共1页
雷达系统能够同时探测森林的水平结构和垂直结构,结合地面控制点还可以高精度地描绘森林中的树干、树冠及林下植被.基于此理念,通过计算雷达激光束被拦截的比例估算红松(Pinus koraiensis)、日本落叶松(Larix leptolepis)和栎类(Quercus... 雷达系统能够同时探测森林的水平结构和垂直结构,结合地面控制点还可以高精度地描绘森林中的树干、树冠及林下植被.基于此理念,通过计算雷达激光束被拦截的比例估算红松(Pinus koraiensis)、日本落叶松(Larix leptolepis)和栎类(Quercus sp.)的有效植被面积指数(PAIe).从冠层表面或冠层内部反射的雷达数据中利用k-均值聚类方法提取林隙分数(GLIDAR),根据比尔-朗伯吸收定律和GLIDAR计算PAIe.结果显示,利用雷达数据推算的红松、日本落叶松和栎类的PAIe与实际测量的PAIe之间的相关系数分别为0.82,0.64和0.59.不同树种之间雷达测量值与实测值之间相关性的差异,主要来自于叶片与枝条数量的不同.如果没有树叶,激光雷达的脉冲只能由枝条反射,然而枝条的大小往往小于激光雷达的分辨率(1m),所以与长满树叶的枝条相比,光秃的枝条反射雷达脉冲的几率非常小.因此,若在春季末期树叶出现后进行此类研究,估算的准确度将有所提高. 展开更多
关键词 叶面积指数 植被面积指数 激光雷达 K-均值聚类 林隙 比尔-朗伯吸收定律
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部