地理学报 ›› 2011, Vol. 66 ›› Issue (7): 917-927.doi: 10.11821/xb201107005

• 气候变化 • 上一篇    下一篇

基于Modis地表温度的横断山区气温估算及其时空规律分析

姚永慧, 张百平, 韩芳   

  1. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室, 北京 100101
  • 收稿日期:2011-04-15 修回日期:2011-05-19 出版日期:2011-07-20 发布日期:2011-09-07
  • 通讯作者: 张百平(1963-), 男, 研究员, 博士生导师, 中国地理学会会员(S110001706M)。E-mail: zhangbp@lreis.ac.cn E-mail:zhangbp@lreis.ac.cn
  • 作者简介:姚永慧(975-), 女, 湖北安陆人, 博士, 中国地理学会会员(S110007303M), 主要从事GIS、RS应用与山地环境研究。E-mail: yaoyh@lreis.ac.cn
  • 基金资助:

    国家自然科学基金(41030528; 41001278)

MODIS-based Air Temperature Estimation in the Hengduan Mountains and Its Spatio-temporal Analysis

YAO Yonghui, ZHANG Baiping, HAN Fang   

  1. State Key Laboratory of Resource and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2011-04-15 Revised:2011-05-19 Online:2011-07-20 Published:2011-09-07
  • Supported by:

    National Natural Science Foundation of China, No.41030528; No.41001278

摘要: 横断山区气象观测站稀少且多分布在河谷之中,气温资料极度匮乏,严重影响山区地理与生态研究。随着遥感技术的发展,热红外遥感数据,结合地面观测数据,可以用来推测山区气温。本文通过对横断山区2001 年-2007 年间64 个气象台站的多年月平均气温数据(Ta) 与Modis地表温度多年月平均值(Ts) 进行了时序分析和回归分析,并取得如下研究结果:(1) Ts 与Ta 具有非常好的线性相关关系,89%的台站的决定系数高于0.5;95%的台站的标准误差都低于3 oC,84.4%的台站标准误差低于2.5 oC;12 个月份的Ts 与Ta 的决定系数R2在0.63~0.90 之间,标准误差在2.22~3.05 oC之间。(2) 研究区内月均气温的变化范围在-2.25~15.64 oC之间;生长季(5-9 月份) 的月均气温变化范围为:10.44~15.64 oC。(3) 等温线的海拔高度自山体外围向内部逐渐升高,与山体效应的增温效应相吻合;0 oC等温线自10 月份从海拔4700±500 m左右逐渐降低,至1月份降至最低点,约在3500±500 m左右,此后,逐渐回升,至次年5 月份再次达到4700±500 m左右,也就是说横断山区5200 m以下的广大山区全年至少有6~12 个月的气温在0 oC以上。研究表明:可以利用Modis月均地表温度结合地面观测台站的数据较精确的估算山区月均气温。

关键词: 气温估算, 地表温度, Modis, 时序分析, 横断山区

Abstract: Climatic conditions are difficult to obtain in high mountain areas due to few meteorological stations and, if any, their poorly representative locations in valleys. Fortunately, remote sensing data can be used to estimate near-surface air temperature (Ta) and other climatic conditions. This paper makes use of recorded meteorological data and MODIS data on land surface temperature (Ts) to estimate monthly mean air temperatures in the Hengduan Mountains. A total of 64 weather stations and 84 MODIS images for seven years (2001 to 2007) are used for analysis. Regression analysis and spatio-temporal analysis of monthly mean Ts vs. monthly mean Ta are carried out, showing that recorded Ta is closely related to MODIS Ts in the study region (mean R2 = 0.72) and the mean standard error of 2.07 oC. The regression analysis of monthly mean Ts vs. Ta for every month of all the stations shows that monthly mean Ts can be used to accurately estimate monthly mean Ta (R2 ranging from 0.63 to 0.90 and standard error between 2.22 oC and 3.05 oC). Thirdly, the retrieved monthly mean Ta for the whole study region varies between -2.25 oC (in January, the coldest month) and 15.64 oC (in July, the warmest month), and for the warm (growing) season (May-September), it is from 10.44 oC to 15.64 oC. Finally, the elevation of isotherms is greater in the central mountain ranges than that in the outer margins; the 0 oC isotherm occurs at elevations of about 4700±500 m in October, and it drops to 3500±500 m in January, and ascends back to 4700±500 m in May next year, which means that monthly mean Ta in the areas below 5200 m is above 0 oC for 6 to 12 months. This clearly indicates that MODIS data could be used to have an accurate estimation of air temperature in mountain regions.

Key words: land surface temperature, MODIS, air temperature estimation, spatial-temporal analysis, the Hengduan Mountains