收藏设为首页 广告服务联系我们在线留言

干旱区地理 ›› 2023, Vol. 46 ›› Issue (8): 1250-1259.doi: 10.12118/j.issn.1000-6060.2022.522

• 气候与水文 • 上一篇    下一篇

黄河源区夏季地表温度变化研究

唐太斌1(),周保1(),金晓媚2,魏赛拉加1,马涛1,张永艳1   

  1. 1.青海省地质环境监测总站,青海 西宁 810008
    2.中国地质大学(北京)水资源与环境学院,北京 100083
  • 收稿日期:2022-10-14 修回日期:2022-12-08 出版日期:2023-08-25 发布日期:2023-09-21
  • 通讯作者: 周保(1984-),男,正高级工程师,主要从事地质灾害、冰川冻土等方面的研究. E-mail: 41448053@qq.com
  • 作者简介:唐太斌(1995-),男,工程师,主要从事冰川冻土等方面的研究. E-mail: 2435729762@qq.com
  • 基金资助:
    青海省科技厅应用基础研究项目(2021-ZJ-T08)

Change of surface temperature in the source area of the Yellow River in summer

TANG Taibin1(),ZHOU Bao1(),JIN Xiaomei2,WEI Sailajia1,MA Tao1,ZHANG Yongyan1   

  1. 1. Qinghai Geological Environmental Monitoring Station, Xining 810008, Qinghai, China
    2. China University of Geosciences Beijing, School of Water Resources and Environment, Beijing 100083, China
  • Received:2022-10-14 Revised:2022-12-08 Online:2023-08-25 Published:2023-09-21

摘要:

利用较高空间分辨率的Landsat卫星数据,以覃志豪单窗算法反演黄河源区1990—2018年(间隔3~5 a)的夏季(7月或8月)地表温度,并对反演结果进行相关性分析。结果表明:(1)黄河源区夏季地表温度平均值与MODIS地表温度产品的平均值相关系数不高,约为0.5,主要原因是Landsat数据与MODIS产品的空间分辨率不一致。(2)水体的地表温度基本保持不变,其他地物的地表温度均呈现上升趋势,冰川的地表温度升高最快。(3)黄河源区各年份地表温度与高程存在明显的负相关关系,相关系数平均值为-0.65。(4)空间上,黄河源区地表温度值与土壤湿度值的空间分布存在负相关关系。(5)在气候因素中,降水与地表温度存在明显的负相关关系,其相关系数小于-0.5的区域约占整个源区面积的70%。

关键词: 黄河源区, 地表温度, 遥感反演, 变化特征, 影响因素

Abstract:

Using Landsat satellite data with high spatial resolution, the Qin Zhihao mono window algorithm was used to retrieve the summer (July or August) surface temperature in the source area of the Yellow River from 1990 to 2018 (with an interval of 3-5 years), and correlation analysis was conducted on the retrieval results. The results show that: (1) The correlation coefficient between the average retrieved surface temperature and the average MODIS surface temperature product is not high, about 0.5, mainly due to the inconsistent spatial resolution between Landsat data and MODIS products. (2) The surface temperature of water remains basically unchanged, while the surface temperature of other features shows an upward trend, with glaciers experiencing the fastest increase in surface temperature. (3) There is a significant negative correlation between surface temperature and elevation in the source area of the Yellow River in various years, with an average correlation coefficient of -0.65. (4) In terms of space, there is a negative correlation between the spatial distribution of surface temperature values and soil moisture values in the source area of the Yellow River. (5) Among climate factors, there is a significant negative correlation between precipitation and surface temperature, with regions with a correlation coefficient less than -0.5 accounting for 70% of the entire source area.

Key words: the source area of the Yellow River, surface temperature, remote sensing retrieval, changing characteristics, controlling factors