当前位置: 首页 > 文章 > 基于定期调查数据的全林分年生长预测模型研究 中南林业科技大学学报 2010,30 (4) 69-74
Position: Home > Articles > Annual whole-stand growth prediction model based on periodic inventory data Journal of Central South University of Forestry & Technology 2010,30 (4) 69-74

基于定期调查数据的全林分年生长预测模型研究

作  者:
张雄清;雷渊才
单  位:
中国林业科学研究院资源信息研究所
关键词:
林学;森林计测学;全林分年生长模型;可变生长率法;似乎不相关联立估计;油松
摘  要:
以北京山区油松为研究对象,利用可变生长率法构造油松全林分年生长预测模型,并通过似乎不相关联立估计全林分生长模型的参数。研究结果表明:利用可变生长率法建立全林分年生长预测模型符合林分发展的规律,解决了林分生长预测的阶段无偏性,同时为林分经营者提供了林分年变化量,而且通过似乎不相关联立估计得到的全林分生长模型参数,没有明显的估计偏差,从而提高了参数估计的有效性。
译  名:
Annual whole-stand growth prediction model based on periodic inventory data
作  者:
ZHANG Xiong-qing,LEI Yuan-cai (Institute of Forest Resources Information Techniques,CAF,Beijing 100091,China)
关键词:
forestry;measurement science of forest;annual whole stand model;variable rate method;seemingly unrelated regression(SUR);Pinus tabulaeformis
摘  要:
Based on the data of Pinus tabulaeformis in Beijing mountain area,the annual whole stand models were established,and the parameters were estimated via seemingly unrelated regression(SUR).The results show that through using the variable rate method,the annual whole stand models were in line with the developing law of the stand,and have solved the problem of stage unbiasedness of stand growth prediction,and meanwhile could provided annual changes of forest for forest managers;and through adopting SUR the parameter values had no obvious biases,and the precision of parameter estimation was raised.

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