| 基于ICESat-GLAS波形估测平均树高的研究 |
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| 引用本文： | 刘美爽,邢艳秋,吴红波,尤号田.基于ICESat-GLAS波形估测平均树高的研究[J].林业科学研究,2014,27(3):309-315. |
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| 作者姓名： | 刘美爽 邢艳秋 吴红波 尤号田 |
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| 作者单位： | 东北林业大学 工程技术学院, 黑龙江 哈尔滨 150040;东北林业大学 工程技术学院, 黑龙江 哈尔滨 150040;东北林业大学 森林作业与环境研究中心, 黑龙江 哈尔滨 150040;中国林业科学研究院 资源信息研究所, 北京 100091;东北林业大学 森林作业与环境研究中心, 黑龙江 哈尔滨 150040;东北林业大学 森林作业与环境研究中心, 黑龙江 哈尔滨 150040 |
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| 基金项目： | 中央高校创新团队与重大项目培育资金项目（DL12EB07）；国家自然科学基金资助项目（41171274）；国家863计划重点项目（2011AA120405）；中国博士后科学基金（2011M500036） |
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| 摘 要： | 以吉林省汪清林业局经营区域为例,基于星载激光雷达ICESat-GLAS回波参数,构建了平均树高回归模型,预估精度为84.05%;利用反距离加权法,对ICESat-GLAS光斑平均树高估测值进行差值运算,得到初始CHM(Canopy Height Model),实现了平均树高空间连续分布制图;再利用坡度校正和3×3移动窗口差分滤波平滑初始CHM,得到研究区平均树高修正CHM,预估精度达到91.52%。研究结果表明,坡度校正和移动窗口差分滤波方法能有效削弱坡度影响,剔除异常点,提高平均树高估测精度。
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| 关 键 词： | 激光雷达 ICESat-GLAS 波形 平均树高 CHM |
| 收稿时间： | 2013/7/18 0:00:00 |
Study on Mean Forest Canopy Height Estimation Based on ICESat-GLAS Waveforms |
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| LIU Mei-shuang,XING Yan-qiu,WU Hong-bo and YOU Hao-tian.Study on Mean Forest Canopy Height Estimation Based on ICESat-GLAS Waveforms[J].Forest Research,2014,27(3):309-315. |
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| Authors: | LIU Mei-shuang XING Yan-qiu WU Hong-bo and YOU Hao-tian |
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| Institution: | College of Engineering and Technology, Northeast Forestry University, Harbin 150040, Heilongjiang, China;College of Engineering and Technology, Northeast Forestry University, Harbin 150040, Heilongjiang, China;Center for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, Heilongjiang, China;Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China;Center for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, Heilongjiang, China;Center for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, Heilongjiang, China |
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| Abstract: | Taking Wangqing Forestry Bureau of Jilin Province as the study area, a regression model for mean forest canopy height was established using ICESat-GLAS (the Ice, Cloud, and Land Elevation-Geoscience Laser Altimeter System) waveform metrics, with the predicted accuracy of 84.05%. By the method of inverse distance weighted (IDW), the interpolation calculation for ICESat-GLAS estimated mean forest canopy height was carried out and the preliminary CHM (Canopy Height Model) was achieved accordingly with continuous spatial distribution. The adjusted CHM was produced by corrected and smoothed preliminary CHM using slopes and differential filter (with 3×3 windows) respectively, and the predicted accuracy was up to 91.52%. The study results indicated that the method of slope correction and differential filter was able to reduce the influence of slope and remove the outliers effectively for CHM, and improve the predicted accuracy consequently. |
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| Keywords: | LiDAR ICESat-GLAS waveforms mean canopy height CHM |
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