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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite I
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High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite I

机译:中国高分辨率地球观测卫星的高分辨率空间气溶胶光学特性反演算法

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摘要

The high-spatial-resolution aerosol retrieval algorithm using Chinese High-Resolution Earth Observation Satellite I (GF-1) wide-field images is developed, which retrieves the aerosol optical depth (AOD) over China for studying the impact of aerosol on climatic and environmental change. The algorithm is based on the red/blue surface reflectance correlations and the lookup table method. To reduce the enormous relative error caused by the constant surface reflectance relationship in the retrieval algorithm, the correlation is parameterized as a function of low, medium, and high values of normalized difference vegetation index (NDVI). Three linear relationships are simulated using MODIS BRDF-adjusted reflectance products (MCD43A4), and MODIS NDVI products are used to ascertain the value of NDVI. By applying the present algorithm to GF-1 images, two different aerosol cases of clear and turbid are analyzed to test the algorithm. Compared with the 10-km MODIS aerosol properties productions, the GF-1 retrieved AOD by our algorithm revealed a significant correlation coefficient with MODIS Dark Target AOD and Deep Blue AOD . Otherwise, the retrieved AOD results are found to be highly correlated with Aerosol Robotic Network (AERONET) sunphotometer observations . Compared with the results relying on the MODIS surface reflectance model, preliminary validation is encouraging that the method based on our updated surface reflectance assumptions successfully improved the accuracy, particularly under the clear sky background and over bright surface.
机译:开发了一种利用中国高分辨率地球观测卫星I(GF-1)宽视场图像的高空间分辨率气溶胶检索算法,该算法检索了中国大陆的气溶胶光学深度(AOD),以研究气溶胶对气候和气候的影响。环境变化。该算法基于红色/蓝色表面反射率相关性和查找表方法。为了减少检索算法中由恒定的表面反射率关系引起的巨大相对误差,将相关性参数化为归一化植被指数(NDVI)的低,中和高值的函数。使用MODIS BRDF调整的反射率产品(MCD43A4)模拟了三个线性关系,并使用MODIS NDVI产品确定NDVI的值。通过将本算法应用于GF-1图像,分析了两种不同的透明和浑浊的气溶胶情况,以测试该算法。与10 km MODIS气溶胶特性生产相比,我们的算法获得的GF-1提取的AOD显示与MODIS暗目标AOD和深蓝AOD有显着的相关系数。否则,发现检索到的AOD结果与气溶胶机器人网络(AERONET)日光计的观测值高度相关。与依赖于MODIS表面反射率模型的结果相比,初步验证令人鼓舞,该方法基于我们更新的表面反射率假设,成功地提高了精度,尤其是在晴朗的天空背景下和明亮的表面上。

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