| 基于激光雷达的大兴安岭典型森林生物量制图技术研究 |
| |
| 引用本文： | 穆喜云,张秋良,刘清旺,庞勇,胡凯龙. 基于激光雷达的大兴安岭典型森林生物量制图技术研究[J]. 遥感技术与应用, 2015, 30(2): 220-225. DOI: 10.11873/j.issn.1004|0323.2015.2.0220 |
| |
| 作者姓名： | 穆喜云 张秋良 刘清旺 庞勇 胡凯龙 |
| |
| 作者单位： | (1.内蒙古农业大学林学院,内蒙古 呼和浩特010018;;2.中国林业科学研究院资源信息研究所,北京100091;;3.中国矿业大学(北京)地球科学与测绘工程学院,北京100083) |
| |
| 基金项目： | 国家科技支撑计划子课题“激光雷达和高光谱成像仪林业示范应用及其软件研发”(2012BAH34B0203);国家863计划子课题,“全球林业定量遥感专题产品生产体系(二)”(2013AA12A302);国家自然科学基金青年科学基金项目“机载激光雷达探测森林冠层高度的机理模型研究”(41201334);“十二五”国家科技计划子课题“内蒙古大兴安岭过伐林可持续经营技术研究与示范”(2012BAD22B0204) |
| |
| 摘 要： | 森林生物量作为森林生态系统基本的数量表征,表明了森林的经营水平和开发利用价值,并能反映其与环境在物质循环和能量流动方面的复杂关系。同时,森林生物量也是林业问题和生态问题研究的基础。以内蒙古大兴安岭国家野外生态站为研究区域,通过对机载激光雷达(LiDAR)点云数据的预处理,利用计算机编程提取LiDAR点云数据的结构参数,以植被分位数高度变量与密度变量为自变量,结合地面调查数据,建立生物量与LiDAR结构参数的回归模型(决定系数为0.69,均方根误差为0.34)。运用IDL编程对LiDAR点云块数据进行运算并生成分辨率为20m×20m的栅格图像,拼接后得到整个区域的地上生物量分布图,对生成的地上生物量分布图进行验证的R2为0.78,RMSE为23.09t/hm2,平均估测精度达83%。
|
| 关 键 词： | 机载激光雷达 遥感 生物量制图 回归模型 |
A Study on Typical Forest Biomass Mapping Technology of Great Khingan Using Airborne Laser Scanner Data |
| |
| Mu Xiyun,Zhang Qiuliang,Liu Qingwang,Pang Yong,Hu Kailong. A Study on Typical Forest Biomass Mapping Technology of Great Khingan Using Airborne Laser Scanner Data[J]. Remote Sensing Technology and Application, 2015, 30(2): 220-225. DOI: 10.11873/j.issn.1004|0323.2015.2.0220 |
| |
| Authors: | Mu Xiyun Zhang Qiuliang Liu Qingwang Pang Yong Hu Kailong |
| |
| Affiliation: | (1.Forestry College of Inner Mongolia Agricultural University,Hohhot 010018,China;2.Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China;;3.China University of Mining & Technology,Beijing 100083,China) |
| |
| Abstract: | Forest biomass as the most basic characterization of forest ecological system shows the management and the development level and reflects the complex relationship between material circulation and energy flow.Forest biomass is the basis for the research of the forestry and ecological research.Taking the Great Khingan state ecosysterm research station in Inner Mongolia as the study area,this study used airborne LiDAR point cloud data,combining computer programming to extract structure parameter of LiDAR point cloud data.Including the percentile height and the vegetation density as variables,combining with the field data to generate the regression model.Stepwise was used for variable selection and the maximum coefficient determination (R2) was 0.69,the RMSE was 0.34.Using IDL programming algorithm of LiDAR point cloud data to generate the resolution for raster images of 20×20 m2,and acquired the biomass map of the whole study area,the average estimating accuracy was 83%. |
| |
| Keywords: | Airborne LiDAR Remote sensing Biomass mapping Regression model |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《遥感技术与应用》浏览原始摘要信息 |
|
点击此处可从《遥感技术与应用》下载免费的PDF全文 |
|
