王海宾,彭道黎,范应龙,李伟涛,张超.基于辅助信息的森林蓄积量空间模拟[J].农业机械学报,2016,47(6):283-289.
Wang Haibin,Peng Daoli,Fan Yinglong,Li Weitao,Zhang Chao.Spatial Modeling of Forest Stock Volume Based on Auxiliary Information[J].Transactions of the Chinese Society for Agricultural Machinery,2016,47(6):283-289.
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基于辅助信息的森林蓄积量空间模拟   [下载全文]
Spatial Modeling of Forest Stock Volume Based on Auxiliary Information   [Download Pdf][in English]
投稿时间:2016-03-11  
DOI:10.6041/j.issn.1000-1298.2016.06.037
中文关键词:  森林蓄积量  普通克里格  协同克里格  辅助信息
基金项目:国家林业局948项目(2015—4—23)和国家重点林业工程监测技术示范推广项目(\[2015\]02号)
作者单位
王海宾 北京林业大学 
彭道黎 北京林业大学 
范应龙 中南林业调查规划设计院 
李伟涛 北京林业大学 
张超 北京林业大学 
中文摘要:以北京市密云县一类清查的样地蓄积量为研究对象,结合与蓄积量相关的辅助因子,采用普通克里格法、协同克里格法对森林蓄积量进行空间插值估测,并与文献[25]同一研究区的基于偏最小二乘法回归法估测结果进行比较分析。结果表明,普通克里格法、基于辅助信息的协同克里格法、偏最小二乘回归法的蓄积量估测值与实测值间的相关系数分别为0.389、0.845、0.766;基于辅助信息的协同克里格法要优于普通克里格法和偏最小二乘回归法,能够明显提高预测精度;与普通克里格法相比,所产生的均方根误差减小了71%,预测值和实测值的相关系数提高了54%。最后生成了密云县森林蓄积量空间分布图。研究表明应用地统计学方法进行蓄积量估测具有很好的应用前景,可以为森林蓄积量的估测提供一种可行的方法。
Wang Haibin  Peng Daoli  Fan Yinglong  Li Weitao  Zhang Chao
Beijing Forestry University,Beijing Forestry University,South—Central Forest Inventory and Planning Institute of SFA,Beijing Forestry University and Beijing Forestry University
Key Words:forest stock volume  ordinary Kriging  Co-Kriging  auxiliary information
Abstract:Taking the stock volume of continuous forest inventory in Miyun District of Beijing as research object, and combining auxiliary factors associated with stock volume, the spatial interpolation analysis of the stock volume was carried out by using the ordinary Kriging and Co-Kriging methods, and the results were compared with those of reference 25 in the same study area based on the partial least squares regression method. The results show that based on the auxiliary information, Co-Kriging method is superior to ordinary Kriging and partial least squares regression method, the correlation coefficient between the estimated value and the measured value based on Co-Kriging method was 0.845, the correlation coefficient between the estimated value and the measured value based on ordinary Kriging method was 0.389, and the correlation coefficient between the estimated value and the measured value based on partial least squares regression method was 0.766, respectively. Co-Kriging can significantly improve the prediction accuracy compared with ordinary Kriging, generating the root mean square error decreased by 71%, respectively, and the correlation coefficient between predicted values and measured values increases by 54%. Finally, the spatial distribution map of forest stock volume in Miyun was generated. The research shows that the application of geo-statistical methodology has a good application prospect, and it can provide a feasible method for the estimation of forest stock.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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