| 采用Landsat8产品算法流程的高分一号数据大气校正 |
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| 引用本文： | 张晓月,李琳琳,王莹,张琪,李国春.采用Landsat8产品算法流程的高分一号数据大气校正[J].农业工程学报,2020,36(1):182-192. |
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| 作者姓名： | 张晓月 李琳琳 王莹 张琪 李国春 |
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| 作者单位： | 中国气象局沈阳大气环境研究所,沈阳 110166;辽宁省生态气象和卫星遥感中心,沈阳 110166;高分辨率对地观测系统辽宁数据与应用中心,沈阳 110166;辽宁省生态气象和卫星遥感中心,沈阳 110166;高分辨率对地观测系统辽宁数据与应用中心,沈阳 110166;沈阳农业大学农学院,沈阳 110866 |
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| 基金项目： | 中国气象局沈阳大气环境研究所开放基金（2017SYIAE03） |
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| 摘 要： | 高分一号(GF-1)卫星搭载的传感器,实现了高分辨率和宽幅成像能力的结合,使其在精准农业方面应用发挥重要作用。该文在6S大气辐射模拟模型基础上,参照LaSRC大气校正流程,设计了GF-1卫星WFV/MSS数据从算法原理分析到编码实现的大气校正。算法应用大气总传输率、水汽透过率和大气后向半球反照率等参数和高程、大气可降水以及臭氧含量等值,循环计算使GF-1像元红蓝通道值比等于来自MODIS数据的红蓝通道值比,求得GF-1像元气溶胶,再将包含当日大气可降水和臭氧含量的辅助数据文件等代入6S模型,得到大气校正后的地表反射率。试验表明,该大气校正方法在有农田和林木等植被覆盖的中低纬度大气校正效果较好,对稀疏植被的荒漠裸地和建筑地表大气校正效果相对稍差。比较GF-1WFV/MSS数据与Landsat8(LC8)OLI数据的基于6S模型LaSRC流程算法的大气校正结果,GF-1WFV/MSS各传感器与LC8OLI大气校正结果的相关系数为0.825~0.972,2种卫星数据大气校正结果相关性高,其中WFV相较于MSS显示出与LC8 OLI更相近的大气校正结果。结果表明,应用6S模型原理参照LaSRC校正流程设计的自行估计数据逐像元水平气溶胶参数的GF-1卫星数据大气校正方法应用方便、可操作性强,适合生长季农林监测等陆面应用。
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| 关 键 词： | 卫星 遥感 GF1WFV/MSS LC8OLI 6S LaSRC 大气校正 |
| 收稿时间： | 2019/7/2 0:00:00 |
| 修稿时间： | 2019/12/2 0:00:00 |
Atmospheric correction method of GF-1 data based on Landsat8 product algorithm flow |
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| Zhang Xiaoyue,Li Linlin,Wang Ying,Zhang Qi and Li Guochun.Atmospheric correction method of GF-1 data based on Landsat8 product algorithm flow[J].Transactions of the Chinese Society of Agricultural Engineering,2020,36(1):182-192. |
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| Authors: | Zhang Xiaoyue Li Linlin Wang Ying Zhang Qi and Li Guochun |
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| Institution: | 1. Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166, China; 2. Liaoning Ecological Meteorology and Satellite Remote Sensing Center, Shenyang 110166, China; 3. Liaoning Data and Application Center for High-resolution Earth Observation System, Shenyang 110166, China;,2. Liaoning Ecological Meteorology and Satellite Remote Sensing Center, Shenyang 110166, China; 3. Liaoning Data and Application Center for High-resolution Earth Observation System, Shenyang 110166, China;,2. Liaoning Ecological Meteorology and Satellite Remote Sensing Center, Shenyang 110166, China; 3. Liaoning Data and Application Center for High-resolution Earth Observation System, Shenyang 110166, China;,2. Liaoning Ecological Meteorology and Satellite Remote Sensing Center, Shenyang 110166, China; 3. Liaoning Data and Application Center for High-resolution Earth Observation System, Shenyang 110166, China; and 4. College of Agronomy, Shenyang Agricultural University, Shenyang 110866, China; |
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| Abstract: | GF-1 satellite has the characteristics of high spatial resolution and short revisiting period, serving as the first satellite of the High-resolution Earth Observation System for National Science and Technology Major Project in China. The satellite carries two multi-spectral high-resolution cameras(panchromatic multispectral sensor, PMS) and four multi-spectral medium-resolution camera(wide field of view, WFV). GF-1 captured data play an important role in the identification of the underlying surface, and these data can be obtained free of charge from the website of the China Centre for Resources Satellite Data and Application. An important step for the application of GF-1 satellite data can be the interference removal of atmospheric molecules, aerosols, ozone, water vapor. The spectral response curves from Landsat8(LC8) operational land imager(OLI) and GF-1 MSS/WFV were then analyzed in the visible and near the infrared bands. The results showed that the spectral range of LC8 OLI in the red-and near the infrared bands was relatively narrower than that of GF-1 MSS/WFV, whereas the spectral response function in the blue-and green bands was slightly different from that of GF-1 MSS/WFV, indicating that it is feasible to transplant LaSRC correction process to GF-1 MSS/WFV data. Since GF-1 satellite lacks the short-wave infrared band compared with LC8, the algorithm was modified to adapt to the characteristics of GF-1 channels. The atmospheric correction project was designed for the GF-1 satellite MSS/WFV data, including the algorithm analysis and code implement based on 6 S atmospheric radiation simulation model and C++ programming language. Some parameters were used to estimate initial aerosol, including total atmospheric transmission, gaseous transmission, atmosphere spherical albedo and actual values of digital elevation model, atmospheric precipitation, ozone content. The loop calculation of the aerosol optical thickness(AOT) was carried out until the ratio between the red-and blue bands of GF-1 MSS/WFV data equal to the prescribed ratio of MODIS, according to the relationship between the blue-and the red surface reflectance known from MODIS. The results can be obtained the surface reflectance with the minimum residual error during different ?ngstr?m coefficients, and retrieved the aerosols in the pixel level of GF-1 MSS/WFV data. The pixel aerosol and these parameters were then substituted into 6 S model to calculate the surface reflectance. Since the project was equipped a data file containing the atmospheric precipitation and ozone content at the current day, the surface reflectance could be obtained when only inputting GF-1 MSS/PMS data. Because the data of atmospheric influence gases, such as ozone and water vapor, on the same day of the data to be corrected were sometimes difficult to identify, two schemes can be provided, one is to use the data at that time, the other is to use the daily values of ozone and water vapor in past six years instead. The experimental results show that the proposed method has a good effect on the atmospheric correction in the middle and low latitudes that covered by vegetation, such as farmland and trees, but not good effect on that of the bare land and building surface that covered by sparse vegetation. Based on 6 S model and LaSRC correction process, the correlation coefficient of the atmospheric correction between GF-1 MSS/WFV and LC8 OLI was from 0.825 to 0.972, indicating a high correlation of atmospheric correction results for two satellites. WFV similar spatial resolution to that of LC8 OLI was in good agreement with that of LC8 OLI atmospheric correction compared with that of MSS. The results show that it is convenient and operable for the GF-1 satellite data atmospheric correction method using the self-estimation aerosol parameters in the pixel level based on 6 S model and LaSRC process. This promising atmospheric method can be very suitable for the land surface application, such as agricultural and forestry monitoring in growing season. At present, this method has been successfully implemented on Remote Sensing data processing platform Remote Sensing Desktop(RSD) in China. |
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| Keywords: | satellites remote sensing GF-1 WFV/MSS Landsat8 OLI 6S LaSRC atmospheric correction |
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