A Validation Study of an Improved SWIR Iterative Atmospheric Correction Algorithm for MODIS-Aqua Measurements in Lake Taihu, China

被引:24
|
作者
Zhang, Minwei [1 ]
Ma, Ronghua [2 ]
Li, Junsheng [1 ]
Zhang, Bing [1 ]
Duan, Hongtao [2 ]
机构
[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[2] Chinese Acad Sci, Nanjing Inst Geog & Limnol, State Key Lab Lake Sci & Environm, Nanjing 210008, Jiangsu, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Atmosphere; lakes; remote sensing; water pollution; TURBID PRODUCTIVE WATERS; CHLOROPHYLL-A CONCENTRATION; AEROSOL OPTICAL-THICKNESS; OCEAN COLOR; SEAWIFS IMAGERY; LEAVING REFLECTANCE; REMOTE ESTIMATION; COASTAL; BANDS; ABSORPTION;
D O I
10.1109/TGRS.2013.2283523
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
We have presented an improved short-wave infrared (SWIR)-based iterative algorithm for the atmospheric correction (AC) of Moderate Resolution Imaging Spectroradiometer (MODIS) data over Lake Taihu, China. The algorithm was validated by means of matchup comparison between MODIS-retrieved and in situ remote sensing reflectances (R-rs). Four examples of the matchup comparison were first carried out for the observation stations within a +/- 5-min time window of MODIS overpass and field measurements. It is shown in the examples that the retrieved R-rs spectra compare reasonably well with the in situ measurements not only over relatively clear waters (with R-rs(859) about 0.0014 sr(-1)) but also over turbid waters (with R-rs(859) about 0.013 sr(-1)). The matchup comparison was further carried out for a total of 54 observation stations within a +/- 2-h time window, indicating that the AC algorithm has good performance for producing water spectra from MODIS data over Lake Taihu. The development of an algal bloom event has been monitored using MODIS-measured R-rs(443) and R-rs(859), showing that MODIS data, combined with the AC algorithm, can be a useful tool for monitoring the water quality of Lake Taihu. The SWIR iterative algorithm, along with the chlorophyll-a concentration (Chl-a) retrieval model using red to near-infrared bands, has the potential of monitoring Chl-a quantitatively and providing useful information for decision makers to manage the water environment and to prepare for events as algal blooms.
引用
收藏
页码:4686 / 4695
页数:10
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