| 城市公园绿地水热通量的环境影响因素定量分析 |
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| 引用本文： | 王修信,高凤飞,朱启疆,孙睿,杨胜天.城市公园绿地水热通量的环境影响因素定量分析[J].干旱区资源与环境,2008,22(1):64-69. |
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| 作者姓名： | 王修信 高凤飞 朱启疆 孙睿 杨胜天 |
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| 作者单位： | 1. 北京师范大学地理学与遥感科学学院遥感与地理信息系统研究中心,北京,100875;遥感科学国家重点实验室,北京,100875;环境遥感与数字城市北京市重点实验室,北京,100875;广西师范大学计算机科学与信息工程学院,桂林,541004
2. 北京师范大学地理学与遥感科学学院遥感与地理信息系统研究中心,北京,100875;遥感科学国家重点实验室,北京,100875;环境遥感与数字城市北京市重点实验室,北京,100875 |
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| 基金项目： | 国家自然科学基金项目(40571109)，北京市自然科学基金重点基金项目(4051003)，北京市教委共建项目(SYS100270431和JD100270540)资助 |
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| 摘 要： | 在北京近郊区海淀公园架设涡度相关仪,连续观测城市公园绿地水热通量及其环境影响因素数值日变化。分别采用神经网络、相关分析和灰关联方法研究植被生长季节影响水热通量的环境因素权重,结果表明:公园绿地水热通量受多个环境因素的综合影响,净辐射影响最大,其次是下垫面温度,再次相对湿度和气温影响潜热,风速对潜热的影响较弱,而气温和风速对显热的影响也相对较弱。神经网络方法直接给出非线性关系权值,分析结果较准确,优于统计分析方法。
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| 关 键 词： | 城市公园绿地 水热通量 环境因素 影响分析 神经网络方法 |
| 文章编号： | 1003-7578（2008）01-064-06 |
| 收稿时间： | 2006-11-13 |
| 修稿时间： | 2006年11月13 |
Environmental Affect Variable Analysis on Water and Heat Flux in the Urban Park Green Space |
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| WANG Xiu-xin,GAO Feng-fei,ZHU Qi-jiang,SUN Rui,YANG Sheng-tian.Environmental Affect Variable Analysis on Water and Heat Flux in the Urban Park Green Space[J].Journal of Arid Land Resources and Environment,2008,22(1):64-69. |
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| Authors: | WANG Xiu-xin GAO Feng-fei ZHU Qi-jiang SUN Rui YANG Sheng-tian |
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| Abstract: | Eddy covariance system was set up in Haidian Park of Beijing urban area.Water and heat fluxes between underlying surface and atmosphere and environmental variables were measured continuously.The influent weights of environmental variables for the fluxes were gotten with neural network analysis,correlation analysis,and gray relevancy analysis during growth season.The results indicated that the fluxes were affected by several environmental variables.The most important environmental variable affecting the fluxes was net radiation,followed was ground temperature,and third were relative humidity and atmospheric temperature for latent heat.Wind speed had less influence on latent heat.Also atmospheric temperature and wind speed had less influence on sensible heat.Neural network analysis showed nonlinear accurate weights directly,was more effective than statistic analysis. |
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| Keywords: | Urban park green space water and heat flux environmental variables influent analysis neural network analysis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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