基于3S技术的天山历史云杉林空间分布的提取
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摘要
运用遥感手段结合历史时期遥感影像数据,以天山云杉(Picea schrenkiana var. tianschanica)林生境特征为固定因子,结合植被指数分析、地形因子分析、主成分分析及面向对象的决策树分类的方法提取历史时期天山云杉林的空间分布信息,从而为历史资料缺失情境下的天然林资源保护工程实施效益评价提供支持。研究表明:①将天山云杉林的年龄特征作为固定因子,以现状年高空间分辨率遥感影像及森林资源二类调查数据作为本底资料,在面向对象分类方法支持下可以很好的从历史时期的遥感影像中提取出天山云杉林的历史空间分布信息,提取精度可达93. 3%;②在植被指数因子中,NDVI对天山云杉林指示性最好,并确定用于天山云杉林提取的最佳NDVI值域为[0. 35,0. 8];③地形因子及主成分分析方法可以大大压缩影像的冗余信息,在提升云杉林信息提取的精度的同时提高运行速度。从整体来看,利用历史时期遥感影像并结合天山云杉林的生境特征,可以很好的提取出历史时期云杉林空间分布信息,从而为资料缺失情境下的森林资源管理措施制定及应对气候变化提供数据支持。
The spatial distribution information of Picea schrenkiana var. tianschanica in the Tianshan Mountains in historical period was extracted based on the vegetation index,topographic factor,principal component analysis,the decision tree classification method and the habitat characteristics of P. schrenkiana in the study area using the remote sensing methods combined with the historical remote sensing image data. So as to provide support for the benefit evaluation of the natural forest resources protection project under the situation of missing historical data. Results showed that: ① the historical spatial distribution information of P. schrenkiana in the Tianshan Mountains could be extracted from the remote sensing images,the forest stand age of P. schrenkiana was set as a fixed factor,and the present remote sensing images with high spatial resolution and forest management investigation data were used as the background information. The accuracy of information extraction of P. schrenkiana in the study area could be as high as 93. 3%,and the remote sensing images can be used to extract the spatial distribution information of P. schrenkiana in the Tianshan Mountains; ② In the vegetation index factors,the response of P. schrenkiana in the Tianshan Mountains to NDVI was the most sensitive,and the best NDVI range for extracting the information of P. schrenkiana in the Tianshan Mountains was [0. 35,0. 8]; ③ Topographic factor and principal component analysis method could greatly compress the redundant information of image,which improved the accuracy of information extraction of P. schrenkiana forest and improved the running speed. On the whole,the spatial distribution information of P. schrenkiana forest in the historical period can be well extracted by using the historical remote sensing images and combining with the habitat characteristics of P. schrenkiana forest in Tianshan Mountains,so as to provide data support for the formulation of forest resource management measures and the response to climate change in the context of data missing.
The spatial distribution information of Picea schrenkiana var. tianschanica in the Tianshan Mountains in historical period was extracted based on the vegetation index,topographic factor,principal component analysis,the decision tree classification method and the habitat characteristics of P. schrenkiana in the study area using the remote sensing methods combined with the historical remote sensing image data. So as to provide support for the benefit evaluation of the natural forest resources protection project under the situation of missing historical data. Results showed that: ① the historical spatial distribution information of P. schrenkiana in the Tianshan Mountains could be extracted from the remote sensing images,the forest stand age of P. schrenkiana was set as a fixed factor,and the present remote sensing images with high spatial resolution and forest management investigation data were used as the background information. The accuracy of information extraction of P. schrenkiana in the study area could be as high as 93. 3%,and the remote sensing images can be used to extract the spatial distribution information of P. schrenkiana in the Tianshan Mountains; ② In the vegetation index factors,the response of P. schrenkiana in the Tianshan Mountains to NDVI was the most sensitive,and the best NDVI range for extracting the information of P. schrenkiana in the Tianshan Mountains was [0. 35,0. 8]; ③ Topographic factor and principal component analysis method could greatly compress the redundant information of image,which improved the accuracy of information extraction of P. schrenkiana forest and improved the running speed. On the whole,the spatial distribution information of P. schrenkiana forest in the historical period can be well extracted by using the historical remote sensing images and combining with the habitat characteristics of P. schrenkiana forest in Tianshan Mountains,so as to provide data support for the formulation of forest resource management measures and the response to climate change in the context of data missing.
引文
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[2]唐光楚.新疆的天山云杉[J].新疆农业科学,1989(5):32-33.[Tang Guangchu.Picea sohrenkiana Fisch et Mey.var.tianschanica in Xinjiang[J].Xinjiang Agricultural Sciences,1989(5):32-33.]
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[7]张震,刘萍,丁易,等.天山云杉林物种组成及其种群空间分布格局[J].南京林业大学学报(自然科学版),2010,34(5):157-160.[Zhang Zhen,Liu Ping,Ding Yi,et al.Species compositions and spatial distribution pattern of tree individuals in the Schrenk spruce forest,Northwest China[J].Journal of Nanjing Forestry University(Natural Sciences Edition),2010,34(5):157-160.]
[8]柏云龙,刘华,白志强,等.天山云杉天然林群落空间结构异质性分析[J].植物科学学报,2012,30(6):552-557.[Bai Yunlong,Liu Hua,Bai Zhiqiang,et al.Spatial pattern heterogeneity of Picea schrenkiana var.tianschanica natural forest in the Tianshan Mountains,Northwest China[J].Plant Science Journal,2012,30(6):552-557.]
[9]李荣,罗惠文,宋于洋,等.天山北坡天山云杉的种群结构特征和空间分布格局[J].干旱区资源与环境,2013,27(1):91-96.[Li Rong,Luo Huiwen,Song Yuyang,et al.Structure characteristics and spatial distribution of Picea schrenkiana population on the northern slopes of the Tianshan Mountain[J].Journal of Arid Land Resources and Environment,2013,27(1):91-96.]
[10]李明辉,何风华,刘云,等.天山云杉种群空间格局与动态[J].生态学报,2005,25(5):1 000-1 006.[Li Minghui,He Fenghua,Liu Yun,et al.Spatial distribution pattern of tree individuals in the Schrenk spruce forest,Northwest China[J].Acta Ecologica Sinica,2005,25(5):1 000-1 006.]
[11]李建贵,潘存德,彭世揆,等.天山云杉种群统计与生存分析[J].北京林业大学,2001,23(1):84-86.[Li Jiangui,Pan Cunde,Peng Shikui,et al.Demography and survival analysis of Picea schrenkiana[J].Journal of Beijing Forestry University,2001,23(1):84-86.]
[12]刘贵峰,刘玉平,郭仲军,等.天山云杉林生物量及其变化规律的研究[J].西北林学院学报,2013,28(5):13-17.[Liu Guifeng,Liu Yuping,Guo Zhongjun,et al.Study of biomass of Picea schrenkiana var.tianschanica and its veriation[J].Journal of Northwest Forestry University,2013,28(5):13-17.]
[13]王燕,赵士洞.天山云杉林生物量和生产力的研究[J].应用生态学报,1998,10(4):389-392.[Wang Yan,Zhao Shidong.Biomass and net productivity of Picea schrenkiana var.tianshanica forest[J].Chinese Journal of Applied Ecology,1998,10(4):389-392.]
[14]张思玉,潘存德.天山云杉人工幼林相容性生物量模型[J].福建林学院学报,2002,22(3):201-204.[Zhang Siyu,Pan Cunde.Study on the compatible biomass model of Picea schrenkiana young plantation[J].Journal of Fujian College of Forestry,2002,22(3):201-204.]
[15]陈冬花,邹陈,李滨勇,等.西天山云杉林生物量与植被指数关系研究[J].北京师范大学学报(自然科学版),2011,47(3):321-325.[Chen Donghua,Zou Chen,Li Bingyong,et al.Relationships between biomass and vegetation index of Picea schrenkiana var.tianshanica in western Tianshan Mountain[J].Journal of Beijing Normal University(Natural Science Edition),2011,47(3):321-325.]
[16]包艳丽,牛树奎,张国林.天山云杉林碳储量研究[J].干旱区资源与环境,2009,23(9):113-117.[Bao Yanli,Niu Shukui,Zhang Guolin.Study on carbon storage in the forest of Picea schrenkiana[J].Journal of Arid Land Resources and Environment,2009,23(9):113-117.]
[17]范静.天山云杉林地表凋落物养分和持水性的初步研究[D].合肥:安徽农业大学,2013.[Fan Jing.Nutrient and Water-holding Characteristics of Litter of Picea schrenkiana var.Tianchanica Forest in the Tianshan Mountains[D].Hefei:Anhui Agricultural University,2013.]
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