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| 多角度热红外遥感图像处理、模拟与静止环境卫星地表温度反演研究 | |
| 其他题名 | Research on the process and simulation of multi-angle thermal images and land surface temperature derivation from the Geostationary Operational Environmental Satellite series |
| 方莉 | |
| 出版年 | 2013 |
| 学位类型 | 博士 |
| 导师 | 柳钦火 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 静止环境观测卫星(GOES,\nGeostationary Operational Environmental Satellite)自70年代发射以来，提供了大量有价值的全天时多波段地表观测数据，目前NOAA(National Oceanic and Atmospheric\nAdministration)业务运行的静止环境观测卫星是GOES\n13和GOES\n15。GOES卫星系列的设计已经发展到了第四代，GOES-R作为第四代GOES卫星的代表计划于2015年发射，其辐射和空间分辨率将有跨越式的提高，这些来自静止轨道卫星的高时间分辨率的热红外观测数据为地表温度日变化的监测提供了可能，对环境变化研究提供重要的参考参数。然而现有的GOES卫星温度产品不是从较高质量的热红外波段反演而来，而是Sounder传感器地表辐射产品的一个副产品，其空间分辨率较低（0.125度）并且缺乏系统的验证，因此论文将系统地设计GOES系列卫星（GOES\n8-R）的地表温度产品作为一个主要的研究目标。论文在调研现有的地表温度反演算法的基础上，结合GOES系列卫星传感器的特性，提出两个可行的GOES温度产品的生成算法。高时间分辨率、较高空间分辨率的GOES卫星系列温度产品，作为陆表模型的重要输入参数，将大幅的提高地表模型的预测精度，也将可预见性的增强地表现象检测并扩展其应用领域（如：地表蒸散、热惯量、沙漠化和干旱监测等）。\n\n高精度的地表温度反演一直都是一个极具挑战性的研究方向，影响反演精度的因素众多，对以GOES卫星为代表的大倾角观测的静止轨道卫星而言，角度效应就是一个影响地表温度反演精度的因素，现有的算法对角度效应的考虑还尚不足。论文的第二部分对多角度热红外遥感数据的处理和模拟做了进一步研究。\n\n多角度遥感通过对地面固定目标多个方向的观察，为获取更加详细可靠的地面目标的三维空间结构参数提供了可能，为定量遥感提供新的途径，多角度遥感正成为一个新的研究领域而受到了国内外学者的普遍关注。近些年来，多角度遥感技术和地表多角度反射/辐射特性建模的研究相互促进。一方面，在多角度遥感数据应用需求的驱动下，多角度对地观测遥感技术得到了迅速发展，各类业务运行的星载多角度观测仪陆续升空，各具特色的机载多角度传感器也层出不穷。另一方面，多角度传感器在提供了更多信息量的同时，对如何应用好多角度观测数据并定量化描述地表反射/辐射特性，向科研者们提出了新的挑战。本论文将重点研究机载多角度热红外遥感数据的模拟、获取，处理和应用系统中的关键技术。论文以机载多角度热红外遥感数据为桥梁，结合多角度的地面实测数据和星载数据，建立从地表到传感器的全链路的多角度热红外图像模拟模型。多角度星载热红外模拟图像将用于分析大倾角星载传感器的角度效应，最终实现大倾角/宽视场卫星遥感观测数据的角度订正和归一化。\n\n\n \n Normal\n 0\n \n \n \n \n false\n false\n false\n \n EN-US\n ZH-CN\n X-NONE\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n /* Style Definitions */\n table.MsoNormalTable\n\t{mso-style-name:普通表格;\n\tmso-tstyle-rowband-size:0;\n\tmso-tstyle-colband-size:0;\n\tmso-style-noshow:yes;\n\tmso-style-priority:99;\n\tmso-style-qformat:yes;\n\tmso-style-parent:\ |
| 英文摘要 | The Geostationary Operational\nEnvironmental Satellites (GOES) have been continuously monitoring the earth\nsurface since 1970, providing valuable and intensive data from a very broad\nrange of wavelengths, day and night. The National Oceanic and Atmospheric\nAdministration's (NOAA's) National Environmental Satellite, Data, and\nInformation Service (NESDIS) is currently operating GOES-15 and GOES-13. The\ndesign of the GOES series is now heading to the 4th generation.\nGOES-R, as a representative of the new generation of the GOES series, is\nscheduled to be launched in 2015 with higher spatial and temporal resolution\nimages and full-time soundings. These frequent observations provided by GOES Image\nmake them attractive for deriving information on the diurnal land surface\ntemperature (LST) cycle and diurnal temperature range (DTR). These parameters\nare of great value for research on the Earth’s diurnal variability and climate\nchange. However, current GOES LST product is generated as a byproduct of\nGOES Surface and Insolation Products (GSIP) from Sounder sensor. The GSIP LST\nproduct is poor in resolution with unknown accuracy. Therefore, one of the primary\nobjectives of this study is the development of LST products for GOES series.\nProper LST retrieval algorithms were studied according to the characteristics\nof sensors onboard the GOES series, from GOES 8 to the new generation of GOES R.\nAn integrated software system was developed to produce a brand new GOES LST\nproduct. The brand new LST\nproduct with high spatial and temporal coverage will allow the estimation of\nthe LST diurnal cycle and DTR, which is of great importance for climate change\nresearch. It makes a significant contribution to expand application fields,\nwhich were limited before because of the lack of LST measurements. Consistent GOES LST retrievals are expected\nto enhance phenomena detection over land surfaces, including\nevapotranspiration, thermal inertia, surface humidity, desertification and\ndrought monitoring. Thus, GOES LST products will substantially improve the\naccuracy of global and meso-scale models. |
| 中文关键词 | 地表温度反演 ; 静止环境卫星 ; 图像模拟 |
| 英文关键词 | Land surface temperature derivation Geostationary Operational Environmental Satellite simulation |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 地图学与地理信息系统 |
| 来源机构 | 中国科学院遥感应用研究所 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/287310 |
| 推荐引用方式 GB/T 7714 | 方莉. 多角度热红外遥感图像处理、模拟与静止环境卫星地表温度反演研究[D]. 中国科学院大学,2013. |
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