地理研究 ›› 2017, Vol. 36 ›› Issue (1): 49-60.doi: 10.11821/dlyj201701004

• 研究论文 • 上一篇    下一篇

天山北坡绿洲—荒漠区高时空分辨率日均气温数据集构建——以三工河流域为例

王新新1,2(), 罗格平1(), 叶辉1,2, 张琪1,2, 蔡鹏1,2, 张苗1,2   

  1. 1. 中国科学院新疆生态与地理研究所,荒漠与绿洲生态国家重点实验室,乌鲁木齐 830011
    2. 中国科学院大学,北京 100049
  • 收稿日期:2016-07-23 修回日期:2016-12-05 出版日期:2017-01-20 发布日期:2017-01-22
  • 作者简介:

    作者简介:王新新(1991- ),男,山东枣庄人,硕士,主要从事土地利用/土地覆被变化、遥感与GIS应用研究。E-mail: wangxinxin0803@outlook.com

  • 基金资助:
    国家自然科学基金—新疆联合基金项目(U1303382);973计划前期研究专项(2014CB460603);国家自然科学基金项目(41271126)

Construction of mean air temperature datasets with high temporal and spatial resolution in oasis-desert region:A case study of Sangong River Basin on thenorthern slope of Tianshan Mountains

Xinxin WANG1,2(), Geping LUO1(), Hui YE1,2, Qi ZHANG1,2, Peng CAI1,2, Miao ZHANG1,2   

  1. 1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2016-07-23 Revised:2016-12-05 Online:2017-01-20 Published:2017-01-22

摘要:

气温是刻画由下垫面不同导致的绿洲—荒漠区水热格局差异并分析其相互作用的关键参量。现有的温度数据集(CRU、MERRY、MODIS等),空间分辨率均无法满足绿洲—荒漠相互作用研究的百米级精度要求。基于Landsat TM影像,通过遥感反演及统计模型估算三工河流域卫星过境日期日均气温空间数据,利用日均气温计算“气温相对变化速率”,以此推算卫星非过境日期的日均气温。结果显示:估算卫星过境日期日均气温的平均RMSE为1.54 ℃,绝对误差为0.50~2.87 ℃。气温相对变化速率为沙质荒漠(1.12)>土质荒漠(1.03)>建设用地(0.97)>农田(0.80)>低山丘陵(0.76);卫星非过境日期日均气温计算值与实测值具有较好的相关性,R2 > 0.90,P < 0.05,RMSE=2.34 ℃。

关键词: Landsat TM影像, 气温相对变化速率, 日均气温数据集, 绿洲—, 荒漠区, 三工河流域

Abstract:

Air temperature is one of key indicators reflecting the spatial hydrothermal heterogeneity, and it is also an indispensable factor driving ecological models or land surface models. Currently, the leading temperature datasets include Climatic Research Unit (CRU), The Climate Forecast System Reanalysis (CFSR), Moderate Resolution Imaging Spectroradiometer (MODIS), but their spatial resolutions are so coarse that they cannot efficiently characterize the difference of heterogeneous hydrothermal patterns in a medium-scale oasis-desert ecosystem in arid regions. So the construction of mean air temperature datasets with high temporal and spatial resolution is crucial for investigating ecological interactions between oasis and desert ecosystems. The Landsat TM/ETM/OLI images, whose spatial resolution of thermal infrared band is 120 m, might be the effective data source for retrieving the daily mean air temperature datasets, which could meet the requirements for effectively representing the interactions between oasis and desert ecosystems. In this paper, firstly, the single-channel algorithm was used to estimate the land surface temperature (LST) based on Landsat TM images. The instantaneous air temperature imageries were retrieved using Zak?ek's algorithm. Then, the daily mean air temperature imageries were created based on the instantaneous temperature imageries, and the relative change rates of air temperature (R-rates) for land-cover types were calculated using the spatial daily mean air temperature imageries in different seasons. Finally, the daily mean air temperature datasets were constructed based on the mean air temperature imageries and R-rates. The R-rates showed great spatial heterogeneity in the Sangong River Basin. The R-rates of sandy desert, soil desert, reference station, cropland and hills was 1.12, 1.03, 0.97, 0.80 and 0.76, respectively, compared with built-up areas. Estimated daily mean air temperature and observed values at different weather stations showed a significant linear correlation (P<0.05). The daily mean air temperature datasets retrieved in this paper could effectively characterize the hydrothermal distribution pattern in oasis-desert ecosystems. The method used in the paper might provide a reference for retrieving the maximum and minimum air temperature.

Key words: Landsat TM images, the relative change rate of air temperature, mean air temperature datasets, oasis-desert region, Sangong River Basin