杉木生长的起伏型时间序列模拟研究

应用生态学报 ›› 2001, Vol. 12 ›› Issue (5): 659-662.

杉木生长的起伏型时间序列模拟研究

吴承祯¹, 洪伟¹, 姜志林²

1. 福建农林大学林学院, 南平 353001;
2. 南京林业大学森林资源与环境学院, 南京 210037

收稿日期:2000-01-10 修回日期:2000-04-10 出版日期:2001-09-25 发布日期:2001-09-25
通讯作者: 吴承祯,1970年生,教授,博士.主要从事数量生态学与森林生态学、环境科学等领域研究,发表学术论文100余篇.E-mail:zjWucz@public.npptt.fj.cnl E-mail:zjWucz@public.npptt.fj.cnl
基金资助:
福建省自然基金资助项目(B0010021).

Simulation of Cunninghamia lanceolata growth by wave-type time series analysis

WU Chengzhen¹, HONG Wei¹, JIANG Zhiling²

1. College of Forestry, Fu jian Agriculture and Forestry University, Nanping 353001;
2. College of Forest Resources and Environment, Nanjing Forestry University, Nanjing 210037

Received:2000-01-10 Revised:2000-04-10 Online:2001-09-25 Published:2001-09-25

摘要/Abstract

摘要： 起伏型时间序列法是一种新的时间序列分析法,本文介绍了起伏型时间序列林木模拟与预测方法.以杉木人工林生长为研究对象,对杉木胸径生长进行建模模拟,模拟精度达到98.3%,结果令人满意,且比逐步回归法、多维时间序列分析法模拟效果更优,说明起伏型时间序列分析方法可应用于林木生长模拟与预测,从而丰富了林木生长预测与预报方法.

关键词: 杉木, 生长, 模拟, 起伏型时间序列, 土地利用/覆被, CA-Markov模型, 艾比湖湿地自然保护区, 遥感, 模拟和预测

Abstract: Wave type time series analysis is a new method of time series analysis.With Cunninghamia lanceolata plantation as research objective,the analysis of wave type time series to simulate its growth was introduced in this paper.The model of Cunninghamia lanceolata growth was deduced, and its simulation precision reached 98.3%,which was satisfactory,and better than that of stepwise regression and multidimensional time series analyse.The results showed that wave type tim e series analysis could be used to simulate forest growth,and enrich the method s of simulating forest growth.

Key words: Cunninghamia lanceolata, Growth, Simulating, Wave type time series, remote sensing, simulation and forecast, CA-Markov model, Ebinur Lake Wetland Nature Reserve, land use/cover

中图分类号:

Q141

吴承祯, 洪伟, 姜志林. 杉木生长的起伏型时间序列模拟研究[J]. 应用生态学报, 2001, 12(5): 659-662.

WU Chengzhen, HONG Wei, JIANG Zhiling. Simulation of Cunninghamia lanceolata growth by wave-type time series analysis[J]. Chinese Journal of Applied Ecology, 2001, 12(5): 659-662.

参考文献

[1] Cooperative Group of Chinese Fir(南方杉木科研协作组).1981. Thegeographical distribution and suggestion of the main commercial timberproduction areas of Chinese fir. Sci Silvae Sin(林业科学),17(2):50～57(in Chinese)

[2] Cox GW. 1979. Trans. Jiang Y-X(蒋有绪). 1979. Laboratory Manualof General Ecology. Beijing:Science Press. 53～59(in Chinese)

[3] Liu J-F(刘金福),Hong W(洪伟).1999. A study on time seriesmodel of individual age and diameter in Castanopsis kawakamii. ActaPhytoecol Sin(植物生态学报),23(3):283～288(in Chinese)

[4] Qiu X-Q(邱学清),Jiang X-D(江希钿).1989. The time series AR(P)model used in estimating monthly increment on the wattle stand. JFujianForColl(福建林学院学报),9(1):43～49(in Chinese)

[5] Wei F-Y(魏凤英),Cao H-X(曹鸿兴)1990. Mathematical model forlong-term prediction and its application. Beijing:Meteorological Press.107～115(in Chinese)

[6] Wu C-Z(吴承祯),Hong W(洪伟),Jiang Z-L(姜志林).1999.Preliction for the growth of Cunninghamia lanceolata by sun-pot and au-to-correlated factors. J Plant Resour Environ(植物资源与环境),8(2):18～21(in Chinese)

[7] Wu C-Z(吴承祯),Hong W(洪伟).1999. Multidimensional timeseries analysis on tree growth. Chin J Appl Ecol(应用生态学报),10(4):395～398(in Chinese)

[8] Wu J(吴敬),Hong W(洪伟).1983. A study on the den-drochronology of Cunninghamia lanceolata. J Meteorol Sci Technol(气象科技),(3):47～54(in Chinese)

[9] Yao X-H(姚晓红).1990. Time series analysis of stand growth data. JBeijing For Univ(北京林业大学学报),12(4):10～16(in Chinese)

[10] Yunnan College of Forestry(云南林学院)ed. 1979. Meteorology. Bei-jing:Agricultural Press. 5～156(in Chinese)

[11] Zhang H-G(张荷观).1986. Application of arima time series model intree growing forecast.Sci Silvae Sin(林业科学),22(1):94～100(inChinese)

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