Recovering low quality MODIS-Terra data over highly turbid waters through noise reduction and regional vicarious calibration adjustment: A case study in Taihu Lake
Recovering low quality MODIS-Terra data over highly turbid waters through noise reduction and regional vicarious calibration adjustment: A case study in Taihu Lake
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通过降噪和区域替代定标调整恢复高浑浊水域低质量MODIS-Terra数据：以太湖为例
DOI：
10.1016/j.rse.2017.05.027
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发表时间：
2017-08
影响因子：
13.5
通讯作者：
Zhang B.
中科院分区：
文献类型：
--
作者：
Li Junsheng;Hu chuanmin;Shen Qian;Barnes B.;Murch B.;Feng L.;Zhang M.;Zhang B.
对浑浊的沿海和内陆沃茨的水质进行遥感需要精确的大气校正，这在技术上具有挑战性。虽然以前的努力表明，使用短波红外波段而不是近红外波段进行大气校正具有优势，但这种方法只能适用于Aqua卫星上的中分辨率成像光谱仪。这是因为来自Terra卫星（MODIST）的MODIS数据包含更多的噪声和其他传感器伪像，因此海洋颜色研究界普遍认为该传感器无法提供科学质量的数据。在这里，我们通过降噪和区域替代校准调整来解决这一技术挑战，并以浑浊的太湖为例展示了初步的成功。首先对短波红外三个波段的噪声进行了评估，然后通过降噪方法进行了降噪。使用校准良好的近红外海洋波段（1公里分辨率）和辐射传输，然后用于调整陆地波段（250米和500米分辨率）在可见光和近红外浑浊的沃茨，其中并发现场测量的反射光谱可用的SWIR波段进行了调整，在开放的海洋沃茨。在SWIR波段的所有三种组合中，发现1240和1640 nm波段的组合表现最好，显示出对太湖的显著提高的反演精度，导致低质量的MODIST数据恢复到与MODISA相当的更高质量的数据，从而使有效数据覆盖范围增加一倍。在另一个高度浑浊的湖泊（中国巢湖）上对这种方法进行的测试显示了类似的结果。虽然这种方法的混浊湖泊的一般应用仍然需要测试的校准系数可能需要当地的调整，这些结果表明，MODIST可以有效地用于监测太湖水质的MODISA。
Remote sensing of water quality in turbid coastal and inland waters requires accurate atmospheric correction, which is technically challenging. While previous efforts have shown the advantage of using the short-wave infrared (SWIR) bands instead of near-infrared (NIR) bands for atmospheric correction, such an approach could only be applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite (MODISA). This is because MODIS data from the Terra satellite (MODIST) contain more noise and other sensor artifacts, thus this sensor has been generally regarded by the ocean color research community as not being able to provide science quality data. Here, we address this technical challenge through noise reduction and regional vicarious calibration adjustment, and demonstrate preliminary success using turbid Taihu Lake as an example. The noise in the three SWIR bands was evaluated first, and then reduced through a noise reduction method. The SWIR bands were adjusted over open-ocean waters using the well-calibrated NIR ocean bands (1-km resolution) and radiative transfer, which were then used to adjust the land bands (250-m and 500-m resolution) in the visible and NIR over turbid waters where concurrent field-measured reflectance spectra are available. Of all three combinations of SWIR bands, the combination of 1240 and 1640-nm bands was found to perform the best, showing significantly improved retrieval accuracy for Taihu Lake, leading to recovery of low-quality MODIST data to higher-quality data comparable to MODISA, and thus doubling valid data coverage. Testing of this approach on another highly turbid lake (Chaohu Lake, China) showed similar results. While the general application of this approach to turbid lakes still needs to be tested as local tuning of the calibration coefficients may be required, these results suggest that MODIST may be used as effectively as MODISA for monitoring Taihu Lake water quality.
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影响因子：
1.9
作者：
M. Wang;S. Bailey
通讯作者：
M. Wang;S. Bailey
中国太湖蓝藻水华的中分辨率成像光谱仪 (MODIS) 观测
影响因子：
3.6
作者：
Hu, Chuanmin;Lee, Zhongping;Shang, Shaoling
通讯作者：
Shang, Shaoling
影响因子：
6.9
作者：
Libiao Yang;K. Lei;W. Meng;G. Fu;Weijin Yan
通讯作者：
Libiao Yang;K. Lei;W. Meng;G. Fu;Weijin Yan
影响因子：
1.7
作者：
Franz, Bryan A.;Kwiatkowska, Ewa J.;McClain, Charles R.
通讯作者：
McClain, Charles R.
影响因子：
4.4
作者：
Gordon, HR
通讯作者：
Gordon, HR