激光与光电子学进展, 2018, 55 (10): 102804, 网络出版: 2018-10-14   

NPP/VIIRS微光图像融合中国中东部城市灯光算法 下载: 830次

NPP/Visible Infrared Image Radiometer Suite Low-Light Image Fusion Algorithm for City Lights in Mid-Eastern China
作者单位
1 北京理工大学光电学院光电成像技术与系统教育部重点实验室, 北京 100081
2 中国气象局国家卫星气象中心, 北京 100081
3 中国气象局中国遥感卫星辐射测量和定标重点开放实验室, 北京 100081
摘要
美国新一代环境气象卫星NPP/联合极轨卫星系统(JPSS)增加了可见光红外成像辐射仪(VIIRS)白天/夜间波段(DNB)的微光昼夜成像通道, 继承了**气象卫星计划(DMSP)线性扫描业务系统(OLS)收集全球微光成像数据的能力, 并在性能上有大幅提升, 利用VIIRS DNB数据可以进行夜间城市灯光探测。针对中国中东部经济快速发展区域城市灯光产品的迫切需求, 综合考虑云层、月光、太阳照射、闪电、火灾等因素的影响, 对低质量数据和非灯光特征数据进行识别和剔除, 采用VIIRS DNB多天夜间数据进行融合, 将多天无月光的有效灯光辐亮度数据进行平均, 生成中国中东部地区夜间城市灯光的月合成产品。将本算法生成的产品与美国国家海洋和大气管理局(NOAA)业务城市灯光产品的辐射亮度值进行对比验证后发现, 两者具有可比性。所开发的城市灯光融合产品算法为后端的衍生应用及其他夜间微光遥感产品的反演奠定了技术基础。
Abstract
As part of the next-generation American environmental meteorological satellites, the NPP/Joint Polar Satellite System (JPSS) has introduced the Visible Infrared Image Radiometer Suite (VIIRS) Day and Night Band (DNB) low-light day/night imaging band. DNB employs the ability of defense meteorological satellite program (DMSP)/Operational Linescan System (OLS) to collect global low-light imaging data, which has resulted in a considerably optimized performance. The nighttime city lights can be detected using the VIIRS DNB data. Because of the urgent requirement for city lights in the rapidly developing regions that are located in mid-eastern China, this study comprehensively considers the influence of various important factors, including clouds, moonlight, sunlight, lightning, and fire, while identifying and rejecting low-quality data and non-light characteristic data in addition to adopting VIIRS DNB multi-day nighttime data fusion. The average of multi-day non-moonlit effective radiance data is used to generate monthly nighttime city lights in mid-eastern China. The results that are obtained by analyzing the radiance value of the product are comparable with those obtained by analyzing the National Oceanic and Atmospheric Administration (NOAA) city lights business product. The city lights fusion product algorithm, which is developed in this study, provides the technical foundation to develop the back-end generative application and for the inversion of the remaining low-light remote-sensing nighttime products.

余越, 胡秀清, 闵敏, 许廷发, 何玉青, 陈林, 徐榕焓. NPP/VIIRS微光图像融合中国中东部城市灯光算法[J]. 激光与光电子学进展, 2018, 55(10): 102804. Yu Yue, Hu Xiuqing, Min Min, Xu Tingfa, He Yuqing, Chen Lin, Xu Ronghan. NPP/Visible Infrared Image Radiometer Suite Low-Light Image Fusion Algorithm for City Lights in Mid-Eastern China[J]. Laser & Optoelectronics Progress, 2018, 55(10): 102804.

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