Shanxi Agriculture Remote Sensing Information Center

Qingdao, China

Shanxi Agriculture Remote Sensing Information Center

Qingdao, China
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Chen J.,Ocean University of China | Chen J.,CAS Qingdao Institute of Oceanology | Quan W.,Shanxi Agriculture Remote Sensing Information Center | Yao G.,Ocean University of China | Cui T.,State Oceanic Administration
Optics Express | Year: 2013

A simple semi-analytical model (SAB) was developed for computing a(560) and bb(550) from HJ-1A/CCD images. By comparison with field measurements, the SAB model produces 5.3-23.5% uncertainty for a(560) and bb(550) retrievals. The a(560) and bb(550) are also retrieved from satellite images. The match-up analysis results indicate that a(560) and bb(550) may be derived from the HJ-1A/CCD images with respective uncertainties of 29.84 and 21.35%. These findings imply that, provided that an atmospheric correction scheme for the green bands is available, the extensive database of HJ-1A/CCD imagery may be used for the quantitative monitoring of optical properties in coastal waters. © 2013 Optical Society of America.


Chen J.,CAS Qingdao Institute of Oceanology | Chen J.,Ocean University of China | Zhang X.,CAS Qingdao Institute of Oceanology | Quan W.,Shanxi Agriculture Remote Sensing Information Center
Optics Express | Year: 2013

The objectives of this study are to validate the applicability of a three-band algorithm in determining chlorophyll- A in eutrophic coastal waters, and to improve the model using improved three-band algorithm. Evaluated using two independent data sets collected from the West Florida Shelf, the variation three-band model was found to have a superior performance to both the three-band and modified three-band model. Using the variation three-band algorithm decreased 18% and 56% uncertainty, respectively, from the three-band and modified three-band algorithms. The significantly reduced uncertainty in chlorophyll- A estimations is attributed to effective removal of absorption of gelbstoff and suspended solids and backscattering of water molecules. © 2013 Optical Society of America.


Chen J.,Ocean University of China | Chen J.,CAS Qingdao Institute of Oceanology | Quan W.,Shanxi Agriculture Remote Sensing Information Center | Wen Z.,Ocean University of China | And 2 more authors.
Advances in Space Research | Year: 2013

"Clear water" is a scale-dependent concept, so it is more likely to successfully find the "clear water" from images with smaller scale than that with larger scale data. In this study, an optimal spectral relationship of moderate-resolution imaging spectroradiometer (MODIS) 250 m and 1 km resolution data at near-infrared bands (OSRLM) is constructed for converting pseudo "clear water" reflectance at 859 nm to those at 748 and 869 nm. According to scale effects, the satellite-observed pseudo "clear water" reflectance is greater than 5.18%, larger than that derived from OSRLM model. An atmospheric correction model for MODIS 1km data using pseudo "clear water" reflectance of MODIS 250 m data (ACMM) was developed for improving the performance of traditional "clear water" atmospheric correction model (CWAC). The model validation results indicate that ACMM model has a better performance than CWAC model. By comparison, the uncertainty decreases by 19.18% in the use of ACMM model over CWAC model for deriving water-leaving reflectance in Taihu Lake, China. This uncertainty is significantly reduced in water-leaving reflectance estimation due to partial removal of scale effects on "clear water". These findings imply that satellite-derived aerosol scattering contribution at smaller scale usually has a better performance than that at larger scale. © 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.


Chen J.,Ocean University of China | Chen J.,CAS Qingdao Institute of Oceanology | Quan W.,Shanxi Agriculture Remote Sensing Information Center | Wen Z.,Ocean University of China | And 2 more authors.
Environmental Earth Sciences | Year: 2013

An improved three-band semi-analytical algorithm was developed for improving the performance of the three- and four-band algorithms, for chlorophyll-a concentration retrievals in the highly turbid waters of the Yellow River estuary. In this special case study of the Yellow River estuary, the optimal wavelengths of the improved three-band semi-analytical algorithm must meet the following requirements: the λ1 and λ2 must be restricted to within the range 660-690 nm, and the λ3 must be longer than 750 nm. The algorithm calibration and validation results indicate that the improved three-band algorithm indeed produces superior performance in comparison to both the three- and four-band algorithms in retrieving chlorophyll-a concentration from the extremely coastal waters of the Yellow River estuary. Comparing the improved three-band algorithm to the original three- and four-band algorithm, the former minimizes the influence of backscattering by suspended solids in near-infrared regions, while the three-band algorithm has a much stronger error tolerance ability than the four-band algorithm. These findings imply that if an atmospheric correction scheme for visible and near-infrared bands is available, the improved three-band algorithm may be used for quantitative monitoring of chlorophyll-a concentration in turbid coastal waters with similar bio-optical properties, although some local bio-optical information or improved models may be required to reposition the optimal band positions of the algorithm. © Springer-Verlag Berlin Heidelberg 2012.


Quan W.,Shanxi Agriculture Remote Sensing Information Center
Journal of the Indian Society of Remote Sensing | Year: 2013

To understand the absolute radiometric calibration accuracy of the HJ-A CCD-1 sensors, image from these sensors were compared to nearly simultaneously image from Landsat-7 ETM+ sensors. Although the HJ-A CCD-1 sensor has almost the same wavelength of each central band and band width as Landsat-7 ETM+ sensor, there is slightly difference in spectral response function (SRF). The impacts of SRF difference effects would produce ~2 % uncertainty in predicting reflectance of HJ-A CCD-1 sensor using Landsat-7 ETM+ sensor. The reflectance observed by satellite at top-of-atmosphere generally depends on its' geometric conditions. The results reveal that the impacts of geometrical conditions would impact on the vicarious cross-calibration accuracy, which should be removed. The performances of cross-calibration are calibrated and validated by four image pairs collected from Yellow River Delta, China, and Qingdao City, China, at four independent times. The results indicate that the HJ-A CCD-1 sensors can be cross calibrated to the Landsat-7 ETM+ sensors to within an accuracy of 3.99 % (denoted by Relative Root Mean Square Error) of each other in all bands except band 4, which has a 6.33 % difference. © 2013 Indian Society of Remote Sensing.


Quan W.,Shanxi Agriculture Remote Sensing Information Center
Journal of the Indian Society of Remote Sensing | Year: 2014

In this study, a theoretical model for studying the scaling effects on the two-band ratio of red to near-infrared band (TBRRN) is suggested. The model is used to explain the relationship between scaling error and local scale error; the results revealed that a special scale scaling procedure can be divided into a series smaller scale scaling procedures, and the total scaling error is the sum of the scaling error of these series' smaller scale scaling procedure. Consequently, under the condition that the local scale is adequately fine, the total scale error at the target scale may be estimated accurately. In order to understand the mechanisms associated with scale in practical remote sensing, TBRRN data with 250 m and 1 km resolution is estimated from MODIS data at 645 and 859 nm, retrieved on September 1, 2009, in the Yellow River estuary, China. It is found that the TBRRN estimated from the 1 km resolution MODIS data is ~2.94 % smaller than as estimated from the 250 m MODIS data. The large scaling error distributes neither in the turbid waters, nor in the low suspended sediment regions, but instead in the high-low suspended sediment concentration transitional zone, which may be attributed to the spatial variable of suspended sediment in the transitional zone. This paper also points out that, owing to the importance of total scale error in achieving NASA's mission in oceanic remote sensing, the way in which to conveniently and precisely estimate the total scale error of remote sensing parameters may potentially be an important topic in the field of oceanic remote sensing, both in present research and in the future. © 2014 Indian Society of Remote Sensing.

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