• 研究论文 •

### 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

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:2017-01-20
• 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:2017-01-20

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.