地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (10): 2023-2037.doi: 10.12082/dqxxkx.2020.200078
高亮1,2(), 杜鑫1, 李强子1,*(
), 王红岩1, 张源1, 王思远1,2
收稿日期:
2020-02-17
修回日期:
2020-05-12
出版日期:
2020-10-25
发布日期:
2020-12-25
通讯作者:
李强子
E-mail:gaoliang@aircas.ac.cn;liqz@aircas.ac.cn
作者简介:
高亮(1994— ),男,甘肃定西人,硕士生,主要从事农业遥感和农业气象灾害方面的研究。E-mail:基金资助:
GAO Liang1,2(), DU Xin1, LI Qiangzi1,*(
), WANG Hongyan1, ZHANG Yuan1, WANG Siyuan1,2
Received:
2020-02-17
Revised:
2020-05-12
Online:
2020-10-25
Published:
2020-12-25
Contact:
LI Qiangzi
E-mail:gaoliang@aircas.ac.cn;liqz@aircas.ac.cn
Supported by:
摘要:
空气温度是评价人居环境的重要指标,与人类的生产生活息息相关;其观测对于水文、环境、生态和气候变化等方面的研究具有重要意义。传统的大范围空气温度观测数据一般通过气象站点获取,但由于气象观测站点空间分布离散稀疏的特点,所获取的数据不能精确描述空间连续的空气温度变化情况。因此,实现基于遥感数据的近地表空气温度精准估算具有重要的现实意义。本研究基于精细的地表覆盖类型、空间连续的土壤水分、地表温度(LST)数据,并结合其他辅助数据,构建了近地表空气温度空间化模型,并对近地表空气温度影响因子进行评估,发现地表覆盖类型对近地表空气温度的影响最大,土壤水分为最活跃的影响因素,经验证,模型精度较高,R2接近0.85,RMSE为0.5℃。本研究获取的精确空间连续的近地表空气温度信息,能够充分表达其空间异质性,为农业气象灾害灾变过程监测、农作物生长过程模拟、区域气候变化分析等研究提供良好的近地表空气温度数据支撑。
高亮, 杜鑫, 李强子, 王红岩, 张源, 王思远. 融合土地覆盖和土壤水分产品的近地表空气温度空间化方法[J]. 地球信息科学学报, 2020, 22(10): 2023-2037.DOI:10.12082/dqxxkx.2020.200078
GAO Liang, DU Xin, LI Qiangzi, WANG Hongyan, ZHANG Yuan, WANG Siyuan. A Near-surface Air Temperature Spatialization Method Integrating Landuse and Soil Moisture Products[J]. Journal of Geo-information Science, 2020, 22(10): 2023-2037.DOI:10.12082/dqxxkx.2020.200078
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