项目名称: 基于红外二氧化碳激光器的地表方向和半球发射率主被动协同反演和验证方法
项目编号: No.41471297
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 天文学、地球科学
项目作者: 吴骅
作者单位: 中国科学院地理科学与资源研究所
项目金额: 90万元
中文摘要: 本项目旨在现有热红外定量遥感研究成果的基础上,针对地表热红外发射率遥感反演存在的朗伯近似等不足,充分发挥红外波长可调的二氧化碳激光器能够作为红外主动光源的潜力,运用遥感主动和被动观测模式相结合的方式,通过设置条件可控的多角度精细观测试验,结合对典型目标红外双向反射机理的剖析,揭示地表方向发射率随观测角度的变化规律,阐明地表方向发射率和半球发射率间的定量关系和转换途径,探索地表方向和半球发射率地面真实性检验的方法,形成一套准确且可操作的基于红外二氧化碳激光器的地表方向和半球发射率主被动协同反演和验证的理论与方法,弥补传统被动方法获取发射率的局限性,提高地表发射率遥感反演精度和水平,为推广星机地二氧化碳激光法反演大面积地表发射率提供必要的理论基础和技术手段。
中文关键词: 热红外遥感;发射率;多光谱遥感;多角度遥感;协同反演
英文摘要: On the basis of existing research achievements in thermal infrared remote sensing, with the merit of wavelength-adjustable CO2 laser that can be used as an active infrared light source, this project is planning to explore an accurate and operable CO2-laser-based method for the retrieval of surface bidirectional emissivity and surface directional hemispherical emissivity with synergistic use of passive and active remote sensing, aiming to overcome the drawbacks and limitations of traditional methods of surface emissivity retrieval from passive thermal remote sensing. By performing condition-controllable multi-angle observation experiments at the ground, and by analyzing the mechanism of infrared bidirectional reflection of typical objective materials, this project are expected to achieve three main objectives: (1)to reveal the mechanism that explains how surface bidirectional emissivity varies with the viewing angle; (2) to figure out the quantitative relationship between directional emissivity and hemispherical emissivity and develop methods for converting one from another; (3) to propose field validation methods for surface directional and hemispheric emissivity. This project will improve the accuracy of surface emissivity retrieval and lay a solid theoretical and technical foundation for extending the application of CO2-laser-based surface emissivity retrieval method at the large scale by using space-borne/airborne/ground-observed data.
英文关键词: thermal infrared remote sensing;emissivity;multi-spectral remote sensing;multi-angle remote sensing;collaborative inversion