高技术通讯2009，Vol.19Issue(11)：1195-1200,6.DOI:10.3772/j.issn.1002-0470.2009.11.017
利用AMSR-E被动微波数据反演地表温度的神经网络算法
A neural network method for retrieving land-surface temperature from AMSR-E data
摘要
Abstract
This paper utilizes the characteristic of multiple-sensor/multiple-resolution of the AQUA (an earth observing satellite) and the neural network to retrieve land surface temperature from the AMSR-E data. The MODIS land surface temperature ( LST) product is made as the ground data, and the average value of part MODIS pixels in an AMSR-E pixel can be used to overcome the influence of cloud. The retrieval result and analysis indicate that the neural network can be used to accurately retrieve land surface temperature from AMSR-E data. The accuracy is the highest when five frequencies (ten channels) are used, which shows that using more channels can better eliminate the influence of soil moisture, roughness, atmosphere and other influence factors. The average land surface temperature error is under 2 K relative to the MODIS LST product.关键词
地表温度(LST)/神经网络(NN)/AMSR-E/MODISKey words
land surface temperature (LST)/neural network (NN)/AMSR-E/ MODIS分类
信息技术与安全科学引用本文复制引用
毛克彪,王道龙,李滋睿,张立新,周清波,唐华俊,李丹丹..利用AMSR-E被动微波数据反演地表温度的神经网络算法[J].高技术通讯,2009,19(11):1195-1200,6.基金项目
国家自然科学基金(40930101),973计划(2007CB714403)和中央级公益性科研院所基本科研业务费资助项目. （40930101）
