针对GOCI遥感数据的官方处理软件(GDPS(GOCI data processing system))中的标准大气校正算法在渤海近岸浑浊水体区域处理中存在的问题,以MODIS/Aqua数据NIR-SWIR波段联合大气校正处理所得的水色遥感反射率产品结果和GOCI的星上反射率数据为基础,基于神经网络模型进行浑浊水体GOCI影像的大气校正方法研究结果表明,神经网络方法能显著减少标准产品中大气校正失效区域,特别是在443、490、680、555、745nm波段改进效果非常明显;但412、660、865nm波段的紧邻近岸的浑浊水体部分区域存在遥感反射率空间分布不合理,这可能与MODIS对应波段产品本身的大气校正精度不高有关.由于缺乏对应的实测数据,后续验证工作还需要进一步开展.
We explored the potential of the environment and disaster monitoring and forecasting small satellite constellations (HJ-1A/1B satellites) charge-coupled device (CCD) imagery (spatial resolution of 30 m, revisit time of 2 days) in the monitoring of total suspended sediment (TSS) concentrations in dynamic water bodies using Poyang Lake, the largest freshwater lake in China, as an example. Field surveys conducted during October 17-26, 2009 showed a wide range of TSS concentration (3-524 mg/L). Atmospheric correction was implemented using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) module in ENVI with the aid of aerosol information retrieved from concurrent Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) surveys, which worked well at the CCD bands with relatively high reflectance. A practical exponential retrieval algorithm was created between satellite remote sensing reflectance and in-situ measured TSS concentration. The retrieved results for the whole water area matched the in-situ data well at most stations. The retrieval errors may be related to the problem of scale matching and mixed pixel. In three selected subregions of Poyang Lake, the distribution trend of retrieved TSS was consistent with that of the field investigation. It was shown that HJ-1A/1B CCD imagery can be used to estimate TSS concentrations in Poyang Lake over synoptic scales after applying an appropriate atmospheric correction method and retrieval algorithm.