干旱区生态环境知识资源中心(Arid): 基于被动微波的寒旱区地表温度反演

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	基于被动微波的寒旱区地表温度反演
其他题名	Land Surface Temperature Retrieved from Passive Microwave Data over Cold and Arid Regions
	彭丹青 1; 李京 1; 赵天杰 2; 张立新 3
ISSN	1000-0240
出版年	2009
卷号	31 期号:2 页码:233-238
中文摘要	以各频段水平极化和垂直极化发射率问的相关关系为条件,利用被动微波数据反演地表温度.算法既解决了地表温度反演过程中发射率难以确定的问题,又克服了热红外遥感受大气影响较大的缺点,其物理意义清晰,计算简便.算法以MODIS温度产品为评价标准,对36.5GHz和89 GHz反演结果进行分析.结果表明:89 GHz亮温数据反演精度高于36.5 GHz;与耕地和草场反演精度相比,裸土和山地反演精度较高.其原因在于高频数据穿透能力较低,能更好地表达地表温度.同时,低频数据相对高频更容易受到地表土壤水分变化的影响,发射率相对不够稳定,对反演结果有一定影响.
英文摘要	Land surface temperature (LST) is a critical parameter for global climate research.Many investigations have been made for LST retrieval using thermal remote sensing data. In fact, thermal images provided by satellite or aircraft platforms are deeply influenced by atmosphere condition. Thus accuracy of thermal remote sensing algorithms will be low if the weather is not clear. Microwave could penetrate cloud, and is hardly influenced by atmosphere. So it has the particular advantage for LST estimation. In this study, microwave data and AIEM model were used to simulate land surface polarized emissivities. First, a linear relationship between microwave surface emissivities at horizontal and vertical polarizations over arctic land surface was found. And then land surface temperature is retrieved on the basis of radiation transfer equation. Finally, MODIS temperature products were applied for result verification. AIEM model is the further development of IEM model. They both take Kirchhoff field into consideration, and a compensate field is introduced to correct the imperfection of the Kirchhoff field. Shi et al. (2000, 2005) verified the capability of AIEM model over low-frequency and high-frequency. Results showed that the model not only can simulate the case of small rough surface, but also be able to simulate rough surface condition. According to in situ measurements, relevant length between 30 cm and 50 cm, root mean square height between 1 cm and 3 cm, soil moisture changes in the range between 0.03 V/V and 0.20 V/V were inputted the model to simulate polarized emissivities. Results were utilized for regression analysis,and a linear relationship between microwave surface horizontal and vertical emissivities is founded. This allowed land surface temperature being retrieved from microwave brightness temperatures conveniently. A land surface temperature method was established on the foundation of linear relationship. And a technique without atmosphere effect was proposed. One AMSR-E image covering 31.57°～35. 5°N,89.31°～108.35° E observed on March 14, 2007 was collected to retrieve land surface temperature. Temperature was calculated using 36.5 GHz and 89 GHz data. And one MODIS L2 temperature product was collected to evaluate this algorithm. MODIS was boarded on the same satellite with AMSR-E. And temperature product taken in clear weather has a high precision with accuracy within 1 K. This makes validation easy. In the study area, 398 pixels were collected with temperature range of 259.34～276.86 K for algorithm validation. Results indicated that 89 GHz data had higher accuracy than 36.5 GHz ones. The average relative error for 36.5 GHz and 89 GHz was 14. 766 and 12.122, respectively. Crop surface and grassland had rather high precision compared to the bare earth and mountainous surface. The reason is that high-frequency microwave has low penetration and the surface temperature can be better expressed by microwave data. At the same time, low-frequency data is more vulnerable by the changes of surface soil moisture. The relative low emissivity stability has a certain influence to the retrieval results. This method not only solves the difficulty in the process of land surface emissivity determination, and is also not impacted by the atmosphere as the thermal infrared remote sensing. It has clear physical meaning and is simple to calculation.
中文关键词	被动微波 ; 地表温度 ; 极化发射率
英文关键词	passive microwave land surface temperature polarized emissivity
语种	中文
国家	中国
收录类别	CSCD
WOS类目	REMOTE SENSING
WOS研究方向	Remote Sensing
CSCD记录号	CSCD:3567834
来源机构	北京师范大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/223279
作者单位	1.民政部,教育部减灾与应急管理研究院, 北京 100875, 中国; 2.北京师范大学, 感科学国家重点实验室, 北京 100875, 中国; 3.北京师范大学, 遥感科学国家重点实验室, 北京 100875, 中国
推荐引用方式 GB/T 7714	彭丹青,李京,赵天杰,等. 基于被动微波的寒旱区地表温度反演[J]. 北京师范大学,2009,31(2):233-238.
APA	彭丹青,李京,赵天杰,&张立新.(2009).基于被动微波的寒旱区地表温度反演.,31(2),233-238.
MLA	彭丹青,et al."基于被动微波的寒旱区地表温度反演".31.2(2009):233-238.