基于遥感、地理信息系统中山陵风景区景观动态分析
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摘要
本文以2003年的SPOT-5和2006年Quickbird影像作为信息源,结合地学信息,以遥感、地理信息系统为主要技术手段,通过图像融合、几何校正、正射校正、纹理提取、图像分类、目视解译等步骤,提取出分类矢量图,再使用景观分析软件对中山陵风景区景观的构成、景观的形状、景观多样性、景观的破碎化进行分析,共分析了16个景观指标,并利用马尔柯夫预测模型,对两期数据进行分析,并预测来了2009年和2012年的景观状况,最后提出措施和对策。本研究的主要内容与结果归纳如下:
(1)景观格局分析:阔叶林、苗圃地、竹林、其它土地的面积增加,针叶林、针阔混交、农地、乔灌面积减少,水域面积基本不变。林业用地面积增加,说明生态环境维系良好。
(2)景观形状分析结果:几种类型形状越来越复杂,但分维数都不高,有必要提高景观单元的分维数,减少人为对景区的干扰。伸长指数都有增加,表明景观形状在缩小,边缘效应在减弱。
(3)景观多样性分析结果:多样性、均匀度降低,优势度变高,这表明研究区景观的阔叶林的优势性越来越明显。
(4)景观破碎度分析结果:整个研究区的破碎度增加。其中,阔叶林的破碎度减少;针叶林、针阔混交,苗圃地、农地、竹林、其它土地、破碎度增加。
(5)马尔柯夫模型得出结论:①对阔叶林面积增长贡献的是针叶林、针阔混交林、乔灌、其它土地;而针叶林主要转化为其它土地、竹林、针阔混交和阔叶林;由于道路建设、景区扩建、黄马水库附近的树木砍伐等原因使得其它土地增多;②从针叶林过渡到针阔混交林、直至向阔叶林的转移,自然演替是中山陵风景区植被类型变化的主要驱动力。③阔叶林面积将会持续增加,2012年将超出总面积一半,但增长速度变慢;针叶林减少速度也有所减缓。
This research mainly uses the SPOT-5 image data in 2003 and Quickbird image data in 2006 as the Information source.Combined with other study information,the remote sensing and the geographic information system are adopted as the main technical method.Use geometric correction,ortho-rectification,image fusion,texture extraction,image classification,visual interpretation to Extract vector diagram.Then,use the software to analysis the landscape composition,the landscape shape,the landscape diversity,the landscape fragmentation.This research statistic sixteen landscape index.This research use markov ' s prediction models to analysis and predict two years data and the corresponding countermeasure is put forward.The main contents and results of this research are summarized as follows:
1)Landscape pattern analysis:This analysis shows the area of broadleaf forest,nursery land, bamboo forest and other land are increasing,the area of coniferous forest,needle broad-leaved mixed forest,farmland and shrub are decreasing,the water area doesn't change on the whole. The increasing of forestland demonstrates the good maintaining of ecological environment.
2)Shape analysis:Several types of landscape shape become more complex,fractal dimension is low,it is necessary to improve fractal dimensions of landscape units and reduce disturbance from human activities.The elongation indices are increasing which demonstrates the landscape shape is shrinking,in the mean time,edge effect is bating.
3)Diversity analysis:Diversity index and evenness index are in the trends of declining, dominance index is going up,the diversity analysis shows the broad-leaved forest as dominant group in the Sun Yat-sen's Mausoleum scenic area is getting more distinct.
4)The degree of fragmentation analysis:As a whole,the fragmentation degree of study area is increasing.The fragmentation degree of forest is increasing while the fragmentation degree of needle forest,needle broad-leaved mixed forest,nursery land,farmland,bamboo forest and other land is decreasing.
5)Dynamic analysis:
●The contribution to the increasing of broad-leaved forest area from needle forest,needle broad-leaved mixed forest,shrub and other land,however,the needle forest mainly transforms to other land,bamboo forest,needle broad-leaved mixed forest and broad-leaved forest.By the reasons of road construction,expansion of beauty spot,the disforestation around HuangMa reservoir,other land increases.
●The transforming from needle forest towards needle broad-leaved mixed forest, eventually completes the transformation.The main driving force for the changing of the Sun Yat-sen's Mausoleum scenic area's vegetation is Natural Succession.
●The area of broad-leaved forest will be increasing consistently,it is predictable the area will dominate over 50%of the whole forest area,but the trend is getting slower and slower, meanwhile the declining of needle forest tends slowly.
(1)景观格局分析:阔叶林、苗圃地、竹林、其它土地的面积增加,针叶林、针阔混交、农地、乔灌面积减少,水域面积基本不变。林业用地面积增加,说明生态环境维系良好。
(2)景观形状分析结果:几种类型形状越来越复杂,但分维数都不高,有必要提高景观单元的分维数,减少人为对景区的干扰。伸长指数都有增加,表明景观形状在缩小,边缘效应在减弱。
(3)景观多样性分析结果:多样性、均匀度降低,优势度变高,这表明研究区景观的阔叶林的优势性越来越明显。
(4)景观破碎度分析结果:整个研究区的破碎度增加。其中,阔叶林的破碎度减少;针叶林、针阔混交,苗圃地、农地、竹林、其它土地、破碎度增加。
(5)马尔柯夫模型得出结论:①对阔叶林面积增长贡献的是针叶林、针阔混交林、乔灌、其它土地;而针叶林主要转化为其它土地、竹林、针阔混交和阔叶林;由于道路建设、景区扩建、黄马水库附近的树木砍伐等原因使得其它土地增多;②从针叶林过渡到针阔混交林、直至向阔叶林的转移,自然演替是中山陵风景区植被类型变化的主要驱动力。③阔叶林面积将会持续增加,2012年将超出总面积一半,但增长速度变慢;针叶林减少速度也有所减缓。
This research mainly uses the SPOT-5 image data in 2003 and Quickbird image data in 2006 as the Information source.Combined with other study information,the remote sensing and the geographic information system are adopted as the main technical method.Use geometric correction,ortho-rectification,image fusion,texture extraction,image classification,visual interpretation to Extract vector diagram.Then,use the software to analysis the landscape composition,the landscape shape,the landscape diversity,the landscape fragmentation.This research statistic sixteen landscape index.This research use markov ' s prediction models to analysis and predict two years data and the corresponding countermeasure is put forward.The main contents and results of this research are summarized as follows:
1)Landscape pattern analysis:This analysis shows the area of broadleaf forest,nursery land, bamboo forest and other land are increasing,the area of coniferous forest,needle broad-leaved mixed forest,farmland and shrub are decreasing,the water area doesn't change on the whole. The increasing of forestland demonstrates the good maintaining of ecological environment.
2)Shape analysis:Several types of landscape shape become more complex,fractal dimension is low,it is necessary to improve fractal dimensions of landscape units and reduce disturbance from human activities.The elongation indices are increasing which demonstrates the landscape shape is shrinking,in the mean time,edge effect is bating.
3)Diversity analysis:Diversity index and evenness index are in the trends of declining, dominance index is going up,the diversity analysis shows the broad-leaved forest as dominant group in the Sun Yat-sen's Mausoleum scenic area is getting more distinct.
4)The degree of fragmentation analysis:As a whole,the fragmentation degree of study area is increasing.The fragmentation degree of forest is increasing while the fragmentation degree of needle forest,needle broad-leaved mixed forest,nursery land,farmland,bamboo forest and other land is decreasing.
5)Dynamic analysis:
●The contribution to the increasing of broad-leaved forest area from needle forest,needle broad-leaved mixed forest,shrub and other land,however,the needle forest mainly transforms to other land,bamboo forest,needle broad-leaved mixed forest and broad-leaved forest.By the reasons of road construction,expansion of beauty spot,the disforestation around HuangMa reservoir,other land increases.
●The transforming from needle forest towards needle broad-leaved mixed forest, eventually completes the transformation.The main driving force for the changing of the Sun Yat-sen's Mausoleum scenic area's vegetation is Natural Succession.
●The area of broad-leaved forest will be increasing consistently,it is predictable the area will dominate over 50%of the whole forest area,but the trend is getting slower and slower, meanwhile the declining of needle forest tends slowly.
引文
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[3]郭晋平.森林景观生态研究.北京:科学出版社,2001.
[4]章家恩,3S技术在景观生态学中的应用研究概述,国土与自然资源研究,2006 No.3]
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[6]蒋卫国,谢志仁,王文杰等.基于3S技术的安徽省景观生态分类系统研究[J].水土保持研究,2002:9(3).
[7]周维,孟永庆,叶兵等.基于3S技术的景观结构分析一以北京百望山地区为例[J].广西林业科学,2002:31(4).
[8]刘惠明,杨燕琼,罗富和.基于3S技术的景观灵敏度测定研究[J].华南农业大学学报(自然科学版),2003:24(3).
[9]张志锋,谢志茹,宫辉力等.基于3S技术构建森林景观信息系统[J].首都师范大学学报(自然科学版),2003:24(2).
[10]付梅臣,陈秋计,米静等.农田景观规划设计及3S技术应用[J].农业工程学报,2003:19(1).
[11]张永生.高分辨率遥感卫星应用[M],北京:科学出版社,2004:56.
[12]Zhang Z,Deriche R,Faugeras O,etal.A Robust Techniquefor Matching Two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry[J].Artificial Intelli-gence,1995:78,(1-2):87-119.
[13]赵英时.遥感应用分析原理与方法[M],北京:科学出版社,2003:75.
[14]于海洋,闫柏琨,甘甫平等.基于Gram-Schmidt变换的高光谱遥感图像改进融合方法[J].地理与地理信息科学,2007.9:23(5).
[15]常庆瑞等.遥感技术导论[M],北京:科学出版社,2004.2:105.
[16]刘慧平,肖志强等.遥感影像的正射校正方法比较[J],遥感技术与应用,2007.12:22(6).
[17]杨志刚,纹理信息在遥感影像分类中的应用[J],硕士论文,2007.3:14.
[18]阮秋琦.数字图像处理学[M],北京:电子工业出版社,2001:156.
[19]李明诗.结合光谱、纹理及地形特征的森林生物量建模研究[J],遥感信息,2006:06.
[20]汤国安,张友顺等.遥感数字图像处理[M],北京:科学出版社,2004:142.
[21]梅安新等.遥感导论[M],北京:高等教育出版社,2001:198.
[22]Vapnik V,Levin E,Le Cun Y.Measuring theVC2dimension of a learning machine[J].neural Computation,1994,6:851-876.
[23]张华煜.基于支持向量机的海量天体光谱数据分类系统研究[D],中国科学院研究生院硕士学位论文,2006:35.
[24]O Chapelle,V Vapnik et al.Choosing Multiple Parameters for Support Vector achines[J].Machine Learning,2002:46:131-159.
[25]王鹏,朱小燕.基于RBF核的SVM的模型选择及其应用[J],计算机工程与应用,2003,24:72-73.
[26]K.Tsuda,G.Ratsch,S.Mika,etal.Learning to Predict the Leave-one-out Error of Kernel basedClassifiers.In:Proc.2001 Int'1 Conf.Artificial Neural Networks-ICANN 2001.Berlin:Springer-Verlag:2001:156.
[27]陆元昌等.基于森林资源二类调查数据的森林景观分类研究[J].林业科学,205,41(2):21-29.
[28]陆元昌等.遥感影像分类技术在森林景观分类评价中的应用研究[J].林业科学研究,2005,18(1):31-35.
[29]袁金国.遥感数字图像处理[M],北京:中国环境科学出版社,2006:95.
[30]濮静娟.遥感图像目视解译原理与方法[M],北京:中国科学技术出版社,1992:88.
[31]李建新.景观生态学实践与评述[M],北京:中国环境科学出版社2007:14-15.
[32]Forman RT.1995.Land Mosaics,the Ecology of Landscape and Regions.Cambridge:Cambridge University Press:18-140.
[33]傅伯杰,陈利顶,马克明等.景观生态学原理及应用[M],北京:科学出版社,2001.7:202.
[34]马海州.基于遥感与GIS的景观类型信息提取及景观格局分析[D],中国科学院研究生院硕士学位论文,2005年4月:39.
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