北京山区森林碳储量遥感估测技术研究
摘要
北京市森林对维护和改善本市环境起着至关重要的作用,进行北京市森林碳储量定量研究,探讨其数量及其空间分布格局,可为造林决策、城市规划和管理决策提供依据。本研究在收集前人研究资料和野外调查的基础上,构建单木生物量估测模型,获取标准地生物量；以TM和MODIS为遥感信息源,构建样地生物量遥感估测模型,估测森林地上生物量,进而估算碳储量。北京山区碳储密度混交林33.23 t／hm2、阔叶林34.71 t／hm2、针叶林37.77 t／hm2、灌木林26.31 t／hm2；碳储总量混交林4.OlTg、阔叶林10.25Tg、针叶林5.86Tg、灌木林7.71Tg,北京山区森林地上部分碳储总量27.82Tg。MODIS-NDVI估测模型得到的碳储总量及空间分布格局最佳,MODIS-EVI估测模型得到的碳储总量是MODIS-NDVI模型的82.03%,TM-NDVI和TM-MSAVI模型得到的灌木林碳储总量及分布异常,TM植被指数的一元二次方程生物量估测模型不适合北京山区森林碳储量的估算。
Forest plays an important role on maitaining and improving the environment in Beijing. To research on forest carbon stock, its abundance and distribution pattern will lay a foundation on forestation decision, urban planning and management.
We construct biomass estimation model of single tree to obtain the biomass of sample plot based on collecting previous research material and field investigation and establish biomass remote sensing estimation model of sample plot to get the forest biomass and carbon storage with TM and MODIS data. The conclusions are:1)the carbon storage density of mingled forest, broad-leaved forest, coniferous forest and shrub forest is 33.23 t/hm2,34.71t/hm2,37.77t/hm2 and 26.31h/tm2; 2)the carbon storage of mingled forest, broad-leaved forest, coniferous forest and shrub forest is 4.01Tg,10.25Tg,5.86Tg and 7.71Tg, the above-ground forest carbon stock of Beijing is 27.82Tg; 3)the total carbon stock and distribution pattern of Beijing from the biomass estimation model by MODIS-NDVI are the best; 4)the total carbon storage from the biomass estimation model by MODIS-EVI is eighty-two percent of which by MODIS-NDVI; 5)the carbon stock and distribution pattern from the biomass estimation model by TM-NDVI and TM-MSAVI are abnormal, and the quadric equation between biomass and TM vegetation index is not appropriate for the carbon stock estimation of Beijing.
Forest plays an important role on maitaining and improving the environment in Beijing. To research on forest carbon stock, its abundance and distribution pattern will lay a foundation on forestation decision, urban planning and management.
We construct biomass estimation model of single tree to obtain the biomass of sample plot based on collecting previous research material and field investigation and establish biomass remote sensing estimation model of sample plot to get the forest biomass and carbon storage with TM and MODIS data. The conclusions are:1)the carbon storage density of mingled forest, broad-leaved forest, coniferous forest and shrub forest is 33.23 t/hm2,34.71t/hm2,37.77t/hm2 and 26.31h/tm2; 2)the carbon storage of mingled forest, broad-leaved forest, coniferous forest and shrub forest is 4.01Tg,10.25Tg,5.86Tg and 7.71Tg, the above-ground forest carbon stock of Beijing is 27.82Tg; 3)the total carbon stock and distribution pattern of Beijing from the biomass estimation model by MODIS-NDVI are the best; 4)the total carbon storage from the biomass estimation model by MODIS-EVI is eighty-two percent of which by MODIS-NDVI; 5)the carbon stock and distribution pattern from the biomass estimation model by TM-NDVI and TM-MSAVI are abnormal, and the quadric equation between biomass and TM vegetation index is not appropriate for the carbon stock estimation of Beijing.
引文
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[27]李新一.基于3S技术的内蒙古镶黄旗草原生产力研究[D].北京：中国农业大学,2005：39-45.
[28]肖海燕.基于高光谱遥成像遥感的红树林类型信息提取和生物量研究——以福田红树林为例[D].北京：北京大学图书馆,2006.
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[30]徐小军,杜华强,周国模,范文义.基于遥感植被生物量估算模型自变量相关性分析综述[J].遥感技术与应用,2008,23(2)：239-247.
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[33]郭志华,彭少麟,王伯荪.利用TM数据提取粤西地区的森林生物量[J].生态学报,2002,22(11)：1832-1839.
[34]顾祝军,曾志远,史学正,等.基于遥感图像不同辐射校正水平的植被覆盖度估算模型[J].应用生态学报,2008,19(6)：1296-1302.
[35]高志海,李增元,魏怀东,等.干旱地区植被指数(Ⅵ)的适宜性研究[J].中国沙漠,2006,26(2)：243-248.
[36]彭道黎,滑永春.几种植被指数探测低盖度植被能力的研究[J].福建林学院学 报,2009,29(1)：11-16.
[37]鲁绍伟,刘凤芹,余新晓,等.北京市八达岭林场森林生态系统健康型评价[J].水土保持学报,2006,20(3)：79~105.
[38]潘琛,杜培军,罗艳,等.一种基于植被指数的遥感影像决策树分类方法[J].计算机应用,2009,29(3)：777-797.
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[2]马泽清,刘琪璟,徐雯佳,李轩然,刘迎春.基于TM遥感影像的湿地松林生物量研究[J].自然资源学报,2008,23(3)：467-478.
[3]马钦彦,陈遐林,王娟,等.华北主要森林类型建群种的含碳率分析[J].北京林业大学学报,2002,24(5)：96~100.
[4]方晰,田大伦,项文化,等.第二代杉木中幼林生态系统碳动态与平衡[J].中南林学院学报,2002,22(1)：1-6.
[5]王正兴,刘闯,HUETE Alfredo.植被指数研究进展：从AVHRR-NDVI到MODIS-EVI[J].生态学报,2003,23(5)：979-987.
[6]王正兴,刘闯,陈文波,等.MODIS增强型植被指数EVI与NDVI初步比较[J].武汉大学学报(信息科学版),2006,31(5)：407-410.
[7]王立海,赵正勇,杨旗.利用GIS对吉林针阔混交林TM遥感图像分类方法的初探[J].应用生态学报,2006,17(4)：577-582.
[8]王兵,魏文俊.江西省森林碳储量与碳密度研究[J].江西科学,2007,25(6)：681-687.
[9]王树森.华北土石山区基于森林植被演替规律的森林健康的研究[D].北京：北京林业大学,2005：2-3.
[10]王淑君,管东生.神经网络模型森林生物量遥感估测方法的研究[J].生态环境,2007,16(1)：108-111.
[11]王新欣,朱进忠,范燕敏,等.基于MODIS-NDVI的天山北坡中段草地动态估产模型研究[J].草业科学,2009,26(7)：24-27.
[12]王静,郭铌.Terra MODIS和Aqua MODIS波段反射率及植被指数比较[J].生态学杂志,2008,27(10)：1711-1717.
[13]刑素丽.半干旱区森林植被生物量遥感估测方法研究[D].河北：中国科学院石家庄农业现代化研究所,2004：1-2.
[14]刘卫国,高炜,高志强,等.绿洲生态系统生物量与植被指数分析[J].生态学杂志,2006,25(9)：1119-1123.
[15]刘古宇,黄敬峰,吴新宏等.草地生物量的高光谱遥感估算模型.农业工程学报[J],2004,22(2)：63-66.
[16]刘勇洪,牛铮.基于MODIS遥感数据的宏观土地覆盖特征分类方法与精度分析研究[J].遥感技术与应用,2004,19(4)：217-224.
[17]何红艳,郭志华,肖文发.遥感在森林地上生物量估算中的应用[J].生态学杂志,2007,26 (8)：1317-1322.
[18]张世利.基于RS、GIS的闽江流域杉木林生物量及碳贮量估测研究[D].福州：福建农林大学,2008.
[19]张培松,武伟,刘洪斌,等.基于MODIS影像对NDVI和EVI的分类研究[J].西南师范大学学报(自然科学版),2007,32(2)：70-75.
[20]张萍.北京森林碳储量研究[D].北京：北京林业大学,2009：8-9.
[21]张锋.基于遥感信息估测森林生物量的研究[D].哈尔滨：东北林业大学,2003.
[22]张德全,桑卫国,李曰峰,等.山东省森林有机碳储量及其动态的研究[J].植物生态学报,2002,26(增刊)：93-97.
[23]李凤秀,张柏,刘殿伟,等.洪河自然保护区乌拉苔草生物量高光谱遥感估算模型[J].湿地科学,2008,6(1)：51-59.
[24]李红军,郑力,雷玉平,等.基于EOS/MODIS数据的NDVI与EVI比较研究[J].地理科学进展,2007,26(1)：26-32.
[25]李国清.南方山地丘陵森林主要树种遥感信息提取研究[D].福建：福建农林大学,2009：25-26.
[26]李娜.川西亚高山森林植被生物量及碳储量遥感估算研究[D].四川：四川农业大学,2008.
[27]李新一.基于3S技术的内蒙古镶黄旗草原生产力研究[D].北京：中国农业大学,2005：39-45.
[28]肖海燕.基于高光谱遥成像遥感的红树林类型信息提取和生物量研究——以福田红树林为例[D].北京：北京大学图书馆,2006.
[29]罗亚,徐建华,岳文泽.基于遥感影像的植被指数研究方法述评[J].生态科学,2005,24(1)：75-79.
[30]徐小军,杜华强,周国模,范文义.基于遥感植被生物量估算模型自变量相关性分析综述[J].遥感技术与应用,2008,23(2)：239-247.
[31]徐天蜀.丛于遥感信息的森林生物量、碳储量估测技术研究[J].林业调查规划,2008,33(3)：11-13.
[32]徐新良,曹明奎,李克让.中国森林生态系统植被碳储量时空动态变化研究[J].地理科学进展,2007,26(6)：1-9.
[33]郭志华,彭少麟,王伯荪.利用TM数据提取粤西地区的森林生物量[J].生态学报,2002,22(11)：1832-1839.
[34]顾祝军,曾志远,史学正,等.基于遥感图像不同辐射校正水平的植被覆盖度估算模型[J].应用生态学报,2008,19(6)：1296-1302.
[35]高志海,李增元,魏怀东,等.干旱地区植被指数(Ⅵ)的适宜性研究[J].中国沙漠,2006,26(2)：243-248.
[36]彭道黎,滑永春.几种植被指数探测低盖度植被能力的研究[J].福建林学院学 报,2009,29(1)：11-16.
[37]鲁绍伟,刘凤芹,余新晓,等.北京市八达岭林场森林生态系统健康型评价[J].水土保持学报,2006,20(3)：79~105.
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