上海城市植被生态系统净第一性生产力动态模拟
摘要
植被作为陆地生态系统中不可或缺的一部分,在全球变化研究中占有举足轻重的地位。植被净第一性生产力(NPP)的研究有助于碳循环、碳动态和碳平衡的研究,其敏感性对全球气候系统有着重要的影响。随着RS,GIS和计算机技术的快速发展,利用遥感数据进行植被NPP的研究日趋成熟,成为研究的主导方向。这些技术的综合应用,不仅实现了植被NPP大范围快速监测,而且可以正确评价植物群落在自然条件下的生产能力,以便为有关部制定宏观调控政策及应急政策提供科学依据。
本文以过程机理模型为主要研究手段对上海城市植被生态系统净第—性生产力(NPP)的时空格局变化进行了动态模拟估算(以2006年为例),旨在通过研究探索上海城市植被生态系统NPP时空格局。依据这一研究目的,我们在GIS支持下通过上海市航片的解译和实地植被调查等步骤建立了上海城市植被数据库,参考TREEDYN模型和TREEDEV模型运用VB语言编写了光合生产模型,应用此数据库和模型,对2006年上海城市植被生态系统NPP的时空分布格局进行了较为全面的定量估算。利用Kriging插值法,在地理信息系统技术的支持下,对上海城市植被NPP状况进行了模拟估算。通过研究,主要得到以下几方面的结论:
1、研究区航片植被分布情况和功能的解译,植被的解译工作是本文的前期基础工作。运用ArcGIS9.2数字化比例尺为1:5700的航片图统计分析得到上海市城市绿地总面积为139.11km~z,占研究区域总面积的20.2%;其中公园绿地、居住区绿地、单位附属绿地、道路绿地、沿岸绿地、生产绿地面积分别为18.46km~2、34.22km~2、56.28km~2、16.17km~2、3.36km~2、10.62km~2,占全部绿地面积的百分比分别为13.27%、24.6%、40.46%、11.62%、2.41%、7.63%。
2、以上海城市植被参数为状态变量,多年平均气候数据作为驱动变量运用光合生产模型对上海城市植被净第一性生产力状况进行了估算,模拟所选物种均为各群落类型的建群种,分别是香樟、悬铃木、水杉、雪松、夹竹桃、红叶李和竹。从单位面积NPP来讲,不同植被类型的NPP差异明显,其年NPP随常绿针叶林、落叶针叶林、落叶灌丛、常绿阔叶林、落叶阔叶林、常绿灌丛、竹灌丛依次上升。就上海市年内NPP来讲,年NPP总量为35.5Mt C,平均值为2552.98tC/(ha~*y)。其中,常绿阔叶林、落叶阔叶林、常绿针叶林、落叶针叶林、常绿灌丛、落叶灌丛、竹灌丛NPP总量依次为16.1Mt C/y、11.77Mt C/y、0.23Mt C/y、0.64Mt C/y、5.34Mt C/y、0.97Mt C/y、0.47Mt C/y,占总年NPP的比例分别为45.3%、33.1%、0.6%、1.8%、15%、2.7%、1.3%。对上海城市植被全年NPP的贡献率来讲,常绿阔叶林和落叶阔叶林贡献最多,二者占78.4%,其次为常绿灌丛,其余的四种植被共贡献了6.6%,贡献最小。
3、上海城市植被年NPP分布情况是:年单位面积NPP为2552tC/(ha~*y),在对全年NPP的贡献率上,上海城市植被的净第一性生产力区域差异明显,最小值和最大值分别为459tC/(ha~*y)和2769tC/(ha~*y)。在宝山区东北部、浦东新区北部和东南部以及南汇区东北部最大,宝山区西南部、普陀区东北部、闸北区南部、虹口区西南部及浦东新区东北角的小部分区域为NPP,总量低值范围。
4、上海城市植被生态系统NPP的季节变化很明显,季节时空格局存在较大差异。在对全年NPP的贡献率上,主要体现在夏季,NPP极大值为16.4821MtC,占全年净初级生产力的46.4%。四季NPP依次为:夏季)秋季)春季)冬季,NPP分别为:16.4821MtC、10.7655MtC、7.448MtC、0.8188MtC,占全年净初级生产力的比例依次为:46.4%、30.3%、20.9%、2.3%。
从空间分布来讲,四季NPP变化也同样显著。四季的单位面积NPP季节平均值分别为535.41tC/ha、1184.84tC/ha、773.89tC/ha、58.87tC/ha。其中,宝山区东北角和与其相邻的浦东新区西北角地区、浦东新区东南部和南汇区的外环以内部分是上海城市植被中净第一性生产力较高的区域,均大于各季节的平均值。而NPP最小的地区则为宝山区西南部、普陀区东北部以及普陀区和闸北区邻接处,四个季节的NPP都是整个研究区域内最小的,而且年内的NPP季节变化较其它区域也变化较小。
Vegetation,as an indispensable factor of the terrestrial ecosystem,plays an important role in global change. Vegetation Net Primary Productivity(NPP) is helpful to studying carbon cycle、carbon trend and carbon balance on the earth , and its sensitivity is also important to global climate. With the rapid development of RS,GIS and cyber-technology,the study by using remote sensing for NPP hastens maturely. It can monitor NPP of vegetation in a large scale fast and evaluate the productivity of the plant community in natural environment combined with these technology. So it can provides important basic information for decision department .
This study aimed to explore NPP tempo-spatial patterns of Shanghai urban vegetation ecosystem by process-based model as 2006 for example. For the research purposes,Shanghai urban vegetation database have been set up,and a photosynthesis-production model have been made by VB process language consulting with TREEDYN model and TREEDEV model. With supports of database and photosynthesis-production model , net primary production (NPP)of Shanghai urban vegetation ecosystem have been quantified generally and quantificationally. With the support of the GIS technology, the kriging interpolation method was used to calculate Shanghai urban vegetation NPP .The estimated results have suggested that:
1. The vegetation's digital map of different function region of Shanghai has been made,this is a basic work of this thesis. This paper used ArcGIS Desktop 9.2 software to interpret Shanghai aerial imagemap which scale is 1:5700 .The result shows that: the green land area of Shanghai is 139.11km~2, the percentage is 20.2%;the area of park green land, residential green land, accessory green land, road green land, water-side green land and procreative green land is 18.46km~2、34.22km~2、56.28km~2、16.17km~2、3.36km~2、10.62km~2 respectively,the percentage is 13.27%、24.6%、40.46%、11.62%、2.41%、7.63% respectively.
2. Based on the vegetation parameters in Shanghai as state variables , several years average weather data as driving variables , urban vegetation NPP in Shanghai was calculated using Photoproduction simulation model. The species which was used in simulating was constructive species of every community types and they are Cinnamomum camphora、Platanus acerifolia、Metasequoia glyptostroboides、Cedrus deodara、Nerium indicum、Prunus cerasifera、bamboo respectively. The NPP of unit area varys depending on different vegetation. NPP of seven vegetations increase in turn:evergreen coniferous forest 3. The distribution trend of year's NPP in Shanghai is :the average value of unit area in a year is 2552t C/(ha*y), the contribution rate for total NPP has obvious diversity in different area. The maximum and minimum values is 2769t C/(ha*y) and 459t C/(ha*y).The maximum areas contain the northeastern Baoshan , northern and southeastern Pudong、northeastern Nanhui ,the minimum areas contain southwestern Baoshan , northeastern Putuo、southern Zhabei、southwestern Hongkou and northeastern corner of Pudong.
4. The seasonal change of vegetation's NPP in Shanghai is remarkable,spatio-temporal situation has obvious diversity in different season. The contribution rate of summer's NPP for total year's NPP is maximum in all seasons, the value is 16.4821Mt C and the percentage is 46.4% accounting for total year's NPP. NPP of four seasonal increase in turn:winter The seasonal change of NPP in spatial distribution is visible too. The average NPP values per unit in four seasons are 535.41t C/ha、1184.84t C/ha、773.89t C/ha、58.87t C/ha respectively. NPP is higher in Northeastern corner of Baoshan、northwestern corner and southeastern of Pudong and Nanhui district which part is in Shanghai Outer Loop Line than other parts of study area. NPP's minimum areas contain southwestern Baoshan、northeastern Putuo and the joinning part of Putuo and Zhabei district. NPP values of four seasons are minimum in all study area. Besides,the seasonal change of annual NPP is lower than other parts of study area.
本文以过程机理模型为主要研究手段对上海城市植被生态系统净第—性生产力(NPP)的时空格局变化进行了动态模拟估算(以2006年为例),旨在通过研究探索上海城市植被生态系统NPP时空格局。依据这一研究目的,我们在GIS支持下通过上海市航片的解译和实地植被调查等步骤建立了上海城市植被数据库,参考TREEDYN模型和TREEDEV模型运用VB语言编写了光合生产模型,应用此数据库和模型,对2006年上海城市植被生态系统NPP的时空分布格局进行了较为全面的定量估算。利用Kriging插值法,在地理信息系统技术的支持下,对上海城市植被NPP状况进行了模拟估算。通过研究,主要得到以下几方面的结论:
1、研究区航片植被分布情况和功能的解译,植被的解译工作是本文的前期基础工作。运用ArcGIS9.2数字化比例尺为1:5700的航片图统计分析得到上海市城市绿地总面积为139.11km~z,占研究区域总面积的20.2%;其中公园绿地、居住区绿地、单位附属绿地、道路绿地、沿岸绿地、生产绿地面积分别为18.46km~2、34.22km~2、56.28km~2、16.17km~2、3.36km~2、10.62km~2,占全部绿地面积的百分比分别为13.27%、24.6%、40.46%、11.62%、2.41%、7.63%。
2、以上海城市植被参数为状态变量,多年平均气候数据作为驱动变量运用光合生产模型对上海城市植被净第一性生产力状况进行了估算,模拟所选物种均为各群落类型的建群种,分别是香樟、悬铃木、水杉、雪松、夹竹桃、红叶李和竹。从单位面积NPP来讲,不同植被类型的NPP差异明显,其年NPP随常绿针叶林、落叶针叶林、落叶灌丛、常绿阔叶林、落叶阔叶林、常绿灌丛、竹灌丛依次上升。就上海市年内NPP来讲,年NPP总量为35.5Mt C,平均值为2552.98tC/(ha~*y)。其中,常绿阔叶林、落叶阔叶林、常绿针叶林、落叶针叶林、常绿灌丛、落叶灌丛、竹灌丛NPP总量依次为16.1Mt C/y、11.77Mt C/y、0.23Mt C/y、0.64Mt C/y、5.34Mt C/y、0.97Mt C/y、0.47Mt C/y,占总年NPP的比例分别为45.3%、33.1%、0.6%、1.8%、15%、2.7%、1.3%。对上海城市植被全年NPP的贡献率来讲,常绿阔叶林和落叶阔叶林贡献最多,二者占78.4%,其次为常绿灌丛,其余的四种植被共贡献了6.6%,贡献最小。
3、上海城市植被年NPP分布情况是:年单位面积NPP为2552tC/(ha~*y),在对全年NPP的贡献率上,上海城市植被的净第一性生产力区域差异明显,最小值和最大值分别为459tC/(ha~*y)和2769tC/(ha~*y)。在宝山区东北部、浦东新区北部和东南部以及南汇区东北部最大,宝山区西南部、普陀区东北部、闸北区南部、虹口区西南部及浦东新区东北角的小部分区域为NPP,总量低值范围。
4、上海城市植被生态系统NPP的季节变化很明显,季节时空格局存在较大差异。在对全年NPP的贡献率上,主要体现在夏季,NPP极大值为16.4821MtC,占全年净初级生产力的46.4%。四季NPP依次为:夏季)秋季)春季)冬季,NPP分别为:16.4821MtC、10.7655MtC、7.448MtC、0.8188MtC,占全年净初级生产力的比例依次为:46.4%、30.3%、20.9%、2.3%。
从空间分布来讲,四季NPP变化也同样显著。四季的单位面积NPP季节平均值分别为535.41tC/ha、1184.84tC/ha、773.89tC/ha、58.87tC/ha。其中,宝山区东北角和与其相邻的浦东新区西北角地区、浦东新区东南部和南汇区的外环以内部分是上海城市植被中净第一性生产力较高的区域,均大于各季节的平均值。而NPP最小的地区则为宝山区西南部、普陀区东北部以及普陀区和闸北区邻接处,四个季节的NPP都是整个研究区域内最小的,而且年内的NPP季节变化较其它区域也变化较小。
Vegetation,as an indispensable factor of the terrestrial ecosystem,plays an important role in global change. Vegetation Net Primary Productivity(NPP) is helpful to studying carbon cycle、carbon trend and carbon balance on the earth , and its sensitivity is also important to global climate. With the rapid development of RS,GIS and cyber-technology,the study by using remote sensing for NPP hastens maturely. It can monitor NPP of vegetation in a large scale fast and evaluate the productivity of the plant community in natural environment combined with these technology. So it can provides important basic information for decision department .
This study aimed to explore NPP tempo-spatial patterns of Shanghai urban vegetation ecosystem by process-based model as 2006 for example. For the research purposes,Shanghai urban vegetation database have been set up,and a photosynthesis-production model have been made by VB process language consulting with TREEDYN model and TREEDEV model. With supports of database and photosynthesis-production model , net primary production (NPP)of Shanghai urban vegetation ecosystem have been quantified generally and quantificationally. With the support of the GIS technology, the kriging interpolation method was used to calculate Shanghai urban vegetation NPP .The estimated results have suggested that:
1. The vegetation's digital map of different function region of Shanghai has been made,this is a basic work of this thesis. This paper used ArcGIS Desktop 9.2 software to interpret Shanghai aerial imagemap which scale is 1:5700 .The result shows that: the green land area of Shanghai is 139.11km~2, the percentage is 20.2%;the area of park green land, residential green land, accessory green land, road green land, water-side green land and procreative green land is 18.46km~2、34.22km~2、56.28km~2、16.17km~2、3.36km~2、10.62km~2 respectively,the percentage is 13.27%、24.6%、40.46%、11.62%、2.41%、7.63% respectively.
2. Based on the vegetation parameters in Shanghai as state variables , several years average weather data as driving variables , urban vegetation NPP in Shanghai was calculated using Photoproduction simulation model. The species which was used in simulating was constructive species of every community types and they are Cinnamomum camphora、Platanus acerifolia、Metasequoia glyptostroboides、Cedrus deodara、Nerium indicum、Prunus cerasifera、bamboo respectively. The NPP of unit area varys depending on different vegetation. NPP of seven vegetations increase in turn:evergreen coniferous forest
4. The seasonal change of vegetation's NPP in Shanghai is remarkable,spatio-temporal situation has obvious diversity in different season. The contribution rate of summer's NPP for total year's NPP is maximum in all seasons, the value is 16.4821Mt C and the percentage is 46.4% accounting for total year's NPP. NPP of four seasonal increase in turn:winter
引文
1 .Bergen KM, et al.1999.Antegration of remotely sensed radar imagery in modeling and mapping of forest Biomass and net primary production[J].Ecol.Mod.,122:257-274.
2.Bossel,H.,Schafer,H., 1989:Generic Simulation of forest growth, carbon, and nitrogen dynamics[ J ] .Ecological Modelling ,48:221-265.
3.Brack C. L. 2002.Pollution mitigation and carbon sequestration by an urban forest [ J ] .Environmental Pollution,116: S195-S200.
4.CRAMER W, KICKLIGHTER D W, BONDEAU A,et al .1999. Comparing global models of terrestrial net primary productivity(NPP) : overview and key results [ J ] . Global Change Biology ,5 : 1 - 15.
5.Davis J.C.1986.Statistics and Data Analysis in Geology.2~d ed.New York: John Wiley&Sons.
6.Fengming Yuan, M. Altaf Arain, T. Andrew Black et al. 2007. Energy and water exchanges modulated by soil-plant nitrogen cycling in a temperate Pacific Northwest conifer forest[J] .Ecological Modelling,201 :331-347
7.FIELD C B , RANDERSON J T , MALMSTROM C M. 1995.Global net primary production :combining ecology and remote sensing [ J ] .Remote Sens Environ , 51 : 74-88.
8.Fleld C B, Behrenfeld M J, Randerson J T, et al. 1998. Primary Production of the Biosphere:Integrating Terrestrial and Oceanic Components[J]. Science, 281 :237 -240.
9.Foley , J . A. 1994.Net primary productivity in the terrestrial biosphere : The application of a global model. J. Geophys. Res . 99(D10) :20773-20783.
10.Heimann , M., Keeling , C. D. 1989. A three-dimensional model of atmospheric CO_2 transport based on observed winds : 2. Model description and simulated tracer experiments. In : D. H.Peterson ,(ed.). Climate Variability in the Pacific and the Western Americas ,American Geophysical Union. pp. 237-275.
11 .Issaks.E.H.,andR.M.Srivastava. 1989 AnlntroductiontoAppliedGeostatistics.Oxford:Oxford University Press.
12.Lieth H, Box E O X. 1972.Evapotranspiration and primary production: C WThornthwaite Lieth H,Whittaker R H.1975.Primary productivity of the Biosphere.New York:Springer Verlag.Memorial Mode[J]. Publications in climatalo-gy, 25(2):37-46.
13.Leith H,Wittaker R H.1975.PrimaryProductivityoftheBiosphere[M].NewYork:SpringerVerlag.
14.Lieth H. 1972.Modeling the productivity of the world[J]. Nature and Resources, UNESCO paris, 5-10
15.Lieth H, Whittaker R H,王业蘧,等译.1985.生物圈的第一性生产力[M].北京:科学出版社.
16.Liu J,Chen JM, Chen W. 1999. Net Primary Productivity Distribution in the BOREAS Region from a Process Model Using Satellite and Surface Data[J] Journal of Geophysical Research,104(D22) :27735-27754.
17.MARTENS S N,USTIN S L,ROUSSEAU R A.2004.Estimation of tree canopy leaf area index by gap fraction analysis[J].Forest Ecology and Management,61:91 - 108.
18.McGuire , A. D. and Melillo ,J . M. et al .1992.Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America. Global Biogeochem. Cycles , 6 :101 -124.
19.Melillo, J . M. and McGuire, A. D. et al. 1993.Global climate change and terrestrial net primary production. Nature , 363 : 234 -240.
20.Monteith, J . L. 1972. Solar radition and productivity in tropical ecosystems. J. A ppl. Ecol. 9 :747-766.
21.Nathalie, J J. 2003 .Ground-based measurement of leaf area index: a review of method,instruments and current controversies [J]. Journal of Experimental Botany,54(392):2403-2417.
22.Potter , C. S. and Randerson , J . T. et al. 1993. Terrestrial ecosystem production : A process model based on global satellite and surface data , Global Biogeochem. Cycles , 7 (4) :811 - 841.
23.Prince , S. D., Goward, S. N. 1995. Global primary production : a remote sensing approach. J.Biogeogr. ,22:815-835.
24.Raich , J . W., Rastetter, E. B. et al. 1991.Potential net primary production in South America.Ecol.A ppl., 1 :399-429.
25.Ralf K,et al .2000.Comparison of direct and indirect estimation of leaf area index in mature Norway spruce stands of eastern Germany [J].Canadian Journal of Forest Research,30(3): 440-447.
26.Ruimy , A. , Saugier , B. 1994. Methodology for the estimation of terrestrial net primary production from remotely sensed data. J.Geophys. Res ., 99 (D3) :5263-5283.
27.Running , S. W., Coughlan , J . C. 1988. A general model of ecosystem processes for regional applications I. Hydrologic balance ,canopy gas exchange and primary production processes.Ecol .Modelling, 42 :125-154.
28.SCHIMEL D , ENTING I G, HEIMANN M, et al. 1995.CO2 and the carbon cycle [ C]. Climate change 1994 ( Intergovernmental panel on climate change) . Cambridge : Cambridge University Press .
29.UchijimaZ,SeinoH. 1985. Agroclimatic Evaluation of Net Primary Productivity of Natural Vegtation (1) : Chikugo Model for Evaluating Pro ductivity[J]. Journal of Agricultural Meteorology ,40 :343 -353.
30.Uchijima Z, Seino H. 1985. Agroclimatic Evaluation of Net Primary Productivity of Natural Vegetation.(1)Chikugo Model for Evaluating Primary Productivity.Journal of Agricultural Meteorology,40:343-352.
31.蔡承侠.2003.植被净第一性生产力及其对气候变化响应研究进展[J].新疆气象,26(6):1-7.
32.陈国南.1987.用迈尔密模型测算我国生物生产量的初步尝试[J].自然资源学报,2(3):270-278.
33.陈利军,刘高焕,励惠国.2002.中国植被净第一性生产力遥感动态监测[J].遥感学报,6(2):129-135.
34.陈述彭,周成虎,等.地理信息系统导论.北京:科学出版社.2000.
35.方精云,刘国华等.1996.我国森林植被的生物量和净生产量[J].生态学报,16(5):497-508.
36.韩文胜.2007.两种主要彩色树种光合生理的研究[J].安徽农学通报,13(13):32-35.
37.贺庆棠,Baumqartner.A.1986.中国植被的可能生产力:农业和林业的气候产量[J].北京林业大学学报,(2):84-98.
38.郝永萍,陈育峰,张兴有.1998.植被净初级生产力模型估算及其对气候变化的响应研究进展[J].地球科学进展,13(6):564-570.
39.侯光良,游松才.1990.用筑后模型估算我国植被气候生产力[J].自然资源学报,5(1):60-65.
40.黄晓鸾等.1998.城市生存环境绿色量值群的研究(1)[J]_中国园林,14(55):61-63.
41.柯金虎,朴世龙.2003.长江流域植被净第一性生产力及其时空格局研究[J].植物生态学报,27(6):764-770.
42.梁春,林植芳,孔国辉.1997.不同光强下生长的亚热带树苗的光合-光响应特性的比较[J].应用生态学报,8(1):7-11.
43.刘立民等.绿量—城市绿化评估的新概念[J].中国园林,16(71):32-34.
44.刘卫国.2007.新疆陆地生态系统净初级生产力和碳时空变化研究[D].新疆大学博士学位论文.
45.刘玉安.2005.RS和GIS支持下的策勒绿洲植被NPP与Biomass估测研究[D].新疆大学硕士学位论文.
46.朴世龙,方精云,郭庆华.2001.利用CASA模型估算我国植被净第一性生产力[J].植物生态学报,25(5):603-608.
47.朴世龙,方精云.2002.1982-1999年青藏高原植被净第一性生产力及其时空变化[J].自然资源学报,17(3):373-380.
48.裘伟廷等.2002.城市园林绿化建设应关注城市绿量[J].国土绿化,3:11.
49.饶戎等.2004.绿容率指标体系解读[N].中国建设报,8.
50.上海统计年鉴.http://www.stats-sh.gov.cn
51.上海市地方志办公室.http:www.shtong.gov.cn/
52.孙睿,朱启疆.2000.中国陆地植被第一性生产力及季节变化研究[J].地理学报,55(1):36-45.
53.孙睿,朱启疆.1999.陆地植被净第一性生产力的研究[J].应用生态学报,10(6):757-760.
54.孙睿,朱启疆.1998.植被净第一性生产力模型及中国净第一性生产力的分析[J].北京师范大学学报(自然科学版),34(增刊):132-137.
55.孙睿,朱启疆.2001.中国陆地植被净第一性生产力及季节变化研究[J].遥感学报,5(4):300-305.
56.田大伦,罗勇,项文化,闫文德.2004.樟树幼树光合特性及其对C0_2浓度和温度升高的响应[J].林业科学,40(5):88-92.
57.王秀珍,黄敬峰,李云梅,等.2003.水稻叶面积指数的多光谱遥感估算模型研究[J].遥感技术与应用,18(2):57-65.
58.肖文发.1998.杉木人工林叶片至冠层光合作用的扩展与模拟研究[J].生态学报,18(6):620-628.
59.谢会成,姜志林,尹建道.2002.杉木的光合特性及其对C0_2倍增的响应[J].西北林学院学报,17(2):1-3.
60.徐晓桃.2008.黄河源区NPP及植被水分利用效率时空特征分析[D].兰州大学硕士学位论文.
61.颜文洪,胡玉佳.2004.海南石梅湾青皮林LAI的冠层数字成像间接法测算[J].中山大学学报(自然科学版),43(3):71-74.
62.闫淑君,洪伟,吴承祯等.2001.自然植被净第一性生产力模型的改进[J].江西农业大学学报,23(2):248-252.
63.杨士弘.1994.城市绿化树木的降温增湿效应研究[J].地理研究,13(4):74-80.
64.张桂莲.2006.运用模拟模型研究鼎湖山森林生态系统的动态[D].中国科学院研究生院博士学位论文.
65.张仁华等.1998.叶面积指数的快速测定方法/植被定量遥感的地面标定技术[J].国土资源遥感,1:54-60.
66.张仁华,孙晓敏,朱治林,苏红波.2000.遥感区域地表植被二氧化碳通量的机理及其应用[J].中国科学,30(2):21-25.
67.张宪洲.1993.我国自然植被净第一性生产力的估算与分布[J].自然资源,(1):15-21.
68.赵平等.2002.利用数字植物冠层图象分析仪测定南亚热带森林叶面积指数的初步报[J].广西植物,22(6):485-489.
69.郑元润,周广胜.2000.基NDVI的中国天然森林植被净第一性生产力模型[J].植物生态学报,24(1):9-12.
70.周广胜,张新时.1995.自然植被净第一性生产力模型初探[J].植物生态学报,19(3):193-200.
71.周广胜,张新时.1996.全球气候变化的中国自然植被的净第一性生产力研究参考文献[J].植物生态学报,20(1):11-19.
72 朱志辉.1993.自然植被净第一性生产力估计模型[J].科学通报,38(15):1422-1426.
73.庄猛,姜卫兵,宋宏峰等.2006.紫叶李与红美丽李(绿叶)光合特性的比较[J].江苏农业学报,22(2):154-158.
2.Bossel,H.,Schafer,H., 1989:Generic Simulation of forest growth, carbon, and nitrogen dynamics[ J ] .Ecological Modelling ,48:221-265.
3.Brack C. L. 2002.Pollution mitigation and carbon sequestration by an urban forest [ J ] .Environmental Pollution,116: S195-S200.
4.CRAMER W, KICKLIGHTER D W, BONDEAU A,et al .1999. Comparing global models of terrestrial net primary productivity(NPP) : overview and key results [ J ] . Global Change Biology ,5 : 1 - 15.
5.Davis J.C.1986.Statistics and Data Analysis in Geology.2~d ed.New York: John Wiley&Sons.
6.Fengming Yuan, M. Altaf Arain, T. Andrew Black et al. 2007. Energy and water exchanges modulated by soil-plant nitrogen cycling in a temperate Pacific Northwest conifer forest[J] .Ecological Modelling,201 :331-347
7.FIELD C B , RANDERSON J T , MALMSTROM C M. 1995.Global net primary production :combining ecology and remote sensing [ J ] .Remote Sens Environ , 51 : 74-88.
8.Fleld C B, Behrenfeld M J, Randerson J T, et al. 1998. Primary Production of the Biosphere:Integrating Terrestrial and Oceanic Components[J]. Science, 281 :237 -240.
9.Foley , J . A. 1994.Net primary productivity in the terrestrial biosphere : The application of a global model. J. Geophys. Res . 99(D10) :20773-20783.
10.Heimann , M., Keeling , C. D. 1989. A three-dimensional model of atmospheric CO_2 transport based on observed winds : 2. Model description and simulated tracer experiments. In : D. H.Peterson ,(ed.). Climate Variability in the Pacific and the Western Americas ,American Geophysical Union. pp. 237-275.
11 .Issaks.E.H.,andR.M.Srivastava. 1989 AnlntroductiontoAppliedGeostatistics.Oxford:Oxford University Press.
12.Lieth H, Box E O X. 1972.Evapotranspiration and primary production: C WThornthwaite Lieth H,Whittaker R H.1975.Primary productivity of the Biosphere.New York:Springer Verlag.Memorial Mode[J]. Publications in climatalo-gy, 25(2):37-46.
13.Leith H,Wittaker R H.1975.PrimaryProductivityoftheBiosphere[M].NewYork:SpringerVerlag.
14.Lieth H. 1972.Modeling the productivity of the world[J]. Nature and Resources, UNESCO paris, 5-10
15.Lieth H, Whittaker R H,王业蘧,等译.1985.生物圈的第一性生产力[M].北京:科学出版社.
16.Liu J,Chen JM, Chen W. 1999. Net Primary Productivity Distribution in the BOREAS Region from a Process Model Using Satellite and Surface Data[J] Journal of Geophysical Research,104(D22) :27735-27754.
17.MARTENS S N,USTIN S L,ROUSSEAU R A.2004.Estimation of tree canopy leaf area index by gap fraction analysis[J].Forest Ecology and Management,61:91 - 108.
18.McGuire , A. D. and Melillo ,J . M. et al .1992.Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America. Global Biogeochem. Cycles , 6 :101 -124.
19.Melillo, J . M. and McGuire, A. D. et al. 1993.Global climate change and terrestrial net primary production. Nature , 363 : 234 -240.
20.Monteith, J . L. 1972. Solar radition and productivity in tropical ecosystems. J. A ppl. Ecol. 9 :747-766.
21.Nathalie, J J. 2003 .Ground-based measurement of leaf area index: a review of method,instruments and current controversies [J]. Journal of Experimental Botany,54(392):2403-2417.
22.Potter , C. S. and Randerson , J . T. et al. 1993. Terrestrial ecosystem production : A process model based on global satellite and surface data , Global Biogeochem. Cycles , 7 (4) :811 - 841.
23.Prince , S. D., Goward, S. N. 1995. Global primary production : a remote sensing approach. J.Biogeogr. ,22:815-835.
24.Raich , J . W., Rastetter, E. B. et al. 1991.Potential net primary production in South America.Ecol.A ppl., 1 :399-429.
25.Ralf K,et al .2000.Comparison of direct and indirect estimation of leaf area index in mature Norway spruce stands of eastern Germany [J].Canadian Journal of Forest Research,30(3): 440-447.
26.Ruimy , A. , Saugier , B. 1994. Methodology for the estimation of terrestrial net primary production from remotely sensed data. J.Geophys. Res ., 99 (D3) :5263-5283.
27.Running , S. W., Coughlan , J . C. 1988. A general model of ecosystem processes for regional applications I. Hydrologic balance ,canopy gas exchange and primary production processes.Ecol .Modelling, 42 :125-154.
28.SCHIMEL D , ENTING I G, HEIMANN M, et al. 1995.CO2 and the carbon cycle [ C]. Climate change 1994 ( Intergovernmental panel on climate change) . Cambridge : Cambridge University Press .
29.UchijimaZ,SeinoH. 1985. Agroclimatic Evaluation of Net Primary Productivity of Natural Vegtation (1) : Chikugo Model for Evaluating Pro ductivity[J]. Journal of Agricultural Meteorology ,40 :343 -353.
30.Uchijima Z, Seino H. 1985. Agroclimatic Evaluation of Net Primary Productivity of Natural Vegetation.(1)Chikugo Model for Evaluating Primary Productivity.Journal of Agricultural Meteorology,40:343-352.
31.蔡承侠.2003.植被净第一性生产力及其对气候变化响应研究进展[J].新疆气象,26(6):1-7.
32.陈国南.1987.用迈尔密模型测算我国生物生产量的初步尝试[J].自然资源学报,2(3):270-278.
33.陈利军,刘高焕,励惠国.2002.中国植被净第一性生产力遥感动态监测[J].遥感学报,6(2):129-135.
34.陈述彭,周成虎,等.地理信息系统导论.北京:科学出版社.2000.
35.方精云,刘国华等.1996.我国森林植被的生物量和净生产量[J].生态学报,16(5):497-508.
36.韩文胜.2007.两种主要彩色树种光合生理的研究[J].安徽农学通报,13(13):32-35.
37.贺庆棠,Baumqartner.A.1986.中国植被的可能生产力:农业和林业的气候产量[J].北京林业大学学报,(2):84-98.
38.郝永萍,陈育峰,张兴有.1998.植被净初级生产力模型估算及其对气候变化的响应研究进展[J].地球科学进展,13(6):564-570.
39.侯光良,游松才.1990.用筑后模型估算我国植被气候生产力[J].自然资源学报,5(1):60-65.
40.黄晓鸾等.1998.城市生存环境绿色量值群的研究(1)[J]_中国园林,14(55):61-63.
41.柯金虎,朴世龙.2003.长江流域植被净第一性生产力及其时空格局研究[J].植物生态学报,27(6):764-770.
42.梁春,林植芳,孔国辉.1997.不同光强下生长的亚热带树苗的光合-光响应特性的比较[J].应用生态学报,8(1):7-11.
43.刘立民等.绿量—城市绿化评估的新概念[J].中国园林,16(71):32-34.
44.刘卫国.2007.新疆陆地生态系统净初级生产力和碳时空变化研究[D].新疆大学博士学位论文.
45.刘玉安.2005.RS和GIS支持下的策勒绿洲植被NPP与Biomass估测研究[D].新疆大学硕士学位论文.
46.朴世龙,方精云,郭庆华.2001.利用CASA模型估算我国植被净第一性生产力[J].植物生态学报,25(5):603-608.
47.朴世龙,方精云.2002.1982-1999年青藏高原植被净第一性生产力及其时空变化[J].自然资源学报,17(3):373-380.
48.裘伟廷等.2002.城市园林绿化建设应关注城市绿量[J].国土绿化,3:11.
49.饶戎等.2004.绿容率指标体系解读[N].中国建设报,8.
50.上海统计年鉴.http://www.stats-sh.gov.cn
51.上海市地方志办公室.http:www.shtong.gov.cn/
52.孙睿,朱启疆.2000.中国陆地植被第一性生产力及季节变化研究[J].地理学报,55(1):36-45.
53.孙睿,朱启疆.1999.陆地植被净第一性生产力的研究[J].应用生态学报,10(6):757-760.
54.孙睿,朱启疆.1998.植被净第一性生产力模型及中国净第一性生产力的分析[J].北京师范大学学报(自然科学版),34(增刊):132-137.
55.孙睿,朱启疆.2001.中国陆地植被净第一性生产力及季节变化研究[J].遥感学报,5(4):300-305.
56.田大伦,罗勇,项文化,闫文德.2004.樟树幼树光合特性及其对C0_2浓度和温度升高的响应[J].林业科学,40(5):88-92.
57.王秀珍,黄敬峰,李云梅,等.2003.水稻叶面积指数的多光谱遥感估算模型研究[J].遥感技术与应用,18(2):57-65.
58.肖文发.1998.杉木人工林叶片至冠层光合作用的扩展与模拟研究[J].生态学报,18(6):620-628.
59.谢会成,姜志林,尹建道.2002.杉木的光合特性及其对C0_2倍增的响应[J].西北林学院学报,17(2):1-3.
60.徐晓桃.2008.黄河源区NPP及植被水分利用效率时空特征分析[D].兰州大学硕士学位论文.
61.颜文洪,胡玉佳.2004.海南石梅湾青皮林LAI的冠层数字成像间接法测算[J].中山大学学报(自然科学版),43(3):71-74.
62.闫淑君,洪伟,吴承祯等.2001.自然植被净第一性生产力模型的改进[J].江西农业大学学报,23(2):248-252.
63.杨士弘.1994.城市绿化树木的降温增湿效应研究[J].地理研究,13(4):74-80.
64.张桂莲.2006.运用模拟模型研究鼎湖山森林生态系统的动态[D].中国科学院研究生院博士学位论文.
65.张仁华等.1998.叶面积指数的快速测定方法/植被定量遥感的地面标定技术[J].国土资源遥感,1:54-60.
66.张仁华,孙晓敏,朱治林,苏红波.2000.遥感区域地表植被二氧化碳通量的机理及其应用[J].中国科学,30(2):21-25.
67.张宪洲.1993.我国自然植被净第一性生产力的估算与分布[J].自然资源,(1):15-21.
68.赵平等.2002.利用数字植物冠层图象分析仪测定南亚热带森林叶面积指数的初步报[J].广西植物,22(6):485-489.
69.郑元润,周广胜.2000.基NDVI的中国天然森林植被净第一性生产力模型[J].植物生态学报,24(1):9-12.
70.周广胜,张新时.1995.自然植被净第一性生产力模型初探[J].植物生态学报,19(3):193-200.
71.周广胜,张新时.1996.全球气候变化的中国自然植被的净第一性生产力研究参考文献[J].植物生态学报,20(1):11-19.
72 朱志辉.1993.自然植被净第一性生产力估计模型[J].科学通报,38(15):1422-1426.
73.庄猛,姜卫兵,宋宏峰等.2006.紫叶李与红美丽李(绿叶)光合特性的比较[J].江苏农业学报,22(2):154-158.