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Conference Agenda

Overview and details of the sessions and sub-session of this conference. Please select a date or session to show only sub-sessions at that day or location. Please select a single sub-session for detailed view (with abstracts and downloads if available).

 
Session Overview
Session
B3: ID.10555 Monitoring Yangzte River Mudflats
Time:
Wednesday, 06/Jul/2016:
9:00am - 10:00am

Session Chair: Federica Braga
Session Chair: Fang Shen
Workshop: Oceans & Coastal Zones
Location: Affilated Building 3-202#, School of Remote Sensing and Information Engineering, Wuhan University

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Presentations
Oral presentation

Multi-mission remote sensing of suspended particulate matter and diffuse attenuation coefficient in estuarine, coastal and oceanic waters, China

Fang Shen1, David Doxaran2, Mhd Suhyb Salama3, Xiaolong Yu3, Yanqun Pan1, Yunxuan Zhou1

1Laboratory of Estuarine and Coastal Research, East China Normal University, China; 2Laboratoire d'Océanographie de Villefranche, UMR 7093, CNRS-UPMC, France; 3Department of Water Resources, ITC, University of Twente, the Netherlands;

During the Dragon-3 project (id:10555) period, we mainly have several advances in the following aspects. 1) Inter-comparison of MODIS, MERIS and GOCI derived backscattering coefficient bbp and remote-sensing reflectance Rrs in turbid waters was conducted ((Doxaran et al. 2013). Cross-comparison of five sensors (MODIS/Terra/Aqua, MERIS/Envisat, MERSI/FY-3, GOCI) derived suspended particulate matter (SPM), and as well as validation using matchups of synchronous multi-sensor derived SPM with concurrent in situ SPM time series observed in fixed field stations, was taken (Shen et al. 2014, Sokoletsky et al. 2015). 2) Annual and seasonal variations in SPM from MERIS data time series and its response to decrease of the river discharge were analyzed (Shen et al. 2013). Diurnal changes in SPM from GOCI (Liu et al. 2013), and synergy of in situ, modeling and GOCI observations were further explored for sediment transport mechanism in the estuary (Ge et al. 2015). 3) An analytical forward model and an inversion scheme (2SeaColor) to retrieve the Kd from remote sensing data were developed (Salama & Verhoef, 2015). Further, the parameterization equations in the inverse scheme of the 2Seacolor model was improved and validation against three in-situ datasets collected from Open Ocean to turbid Yangtze estuary showed the model can consistently stable and fairly accurate Kd estimates in both clear and turbid waters without the need of tuning empirical coefficients from field measurements (Yu et al. 2016). 4) Diurnal and vertical variations in bio-optical properties were observed from autonomous profiling floats in East China Sea turbid coastal waters, which can also validate diurnal variation of GOCI derived products (Doxaran et al. in prep). In addition, 5) Simple and operational atmospheric correction methods were recently developed. For instance, an improved algorithm based on spectral optimize algorithm through a water-atmosphere coupled model was proposed for GOCI and MERIS over extremely turbid waters (Pan et al. in prep).

References:
Doxaran, D., et al., Retrieval of the seawater reflectance for suspended solids monitoring in the East China Sea using MODIS, MERIS and GOCI satellite data, Remote Sensing of Environment (2013), http://dx.doi.org/10.1016/j.rse.2013.06.020

Ge, J., F. Shen, W. Guo, C. Chen, and P. Ding (2015), Estimation of critical shear stress for erosion in the Changjiang Estuary: A synergy research of observation, GOCI sensing and modeling, Journal of Geophysical Research: Oceans, 120, doi:10.1002/2015JC010992.

Salama, M. S., & Verhoef, W. (2015). Two-stream remote sensing model for water quality mapping: 2SeaColor. Remote Sensing of Environment, 157, 111–122.

Shen, F., et al., (2013). Remotely sensed variability of the suspended sediment concentration and its response to decreased river discharge in the Yangtze estuary and adjacent coast. Continental Shelf Research, 69, 52–61.

Shen, F. et al. (2014), Satellite multi-sensor mapping of suspended particulate matter in turbid estuarine and coastal ocean, China. International Journal of Remote Sensing, 35:11-12, 4173-4192, DOI: 10.1080/01431161.2014.916053

Sokoletsky L, Yang X, Shen F. (2014). MODIS-based retrieval of suspended sediment concentration and diffuse attenuation coefficient in Chinese estuarine and coastal waters. Proc. SPIE Asia Pacific Remote Sensing, 9261: 926119-1 - 926119-25.

Yu Xiaolong, Salam Suhyb, Shen Fang and Verheof Wouter, (2016). Retrieval of the diffuse attenuation coefficient from GOCI images using the 2SeaColor model: A case study in the Yangtze Estuary. Remote Sensing of Environment, 109 (175).


Oral presentation

Sentinels on Water

Mhd. Suhyb Salama1, Xiaolong Yu1, Palmer Stephani1, Fang Shen2

1University of Twente, Faculty of Geo information Science and Earth Observation, Netherlands, The; 2State Key Laboratory of Eastuarine and Coastal Research, East China Normal University, China;

Efficient monitoring of water quality presents one of the most crucial challenges of this century. Most of the world's population growth will occur in developing countries where monitoring programs are inadequate and the water is already critically scarce and polluted.

Current monitoring practices by water managers depend largely on labour-intensive measurements, which provide only a limited insight into the spatial and temporal distributions. Earth Observation (EO) data especially those that will come available from the European Copernicus program provides a unique opportunity for operational monitoring of water quality.

In this presentation we provide an overview on how the Chines-European cooperation, under the DRAGON ESA program, has contributed to the operational monitoring of water quality in China and Europe.

Salama-Sentinels on Water_Cn_version.pdf

Poster

Retrieval of the Diffuse Attenuation Coefficient from GOCI Images Using the 2SeaColor Model: A Case Study in the Yangtze Estuary

Xiaolong Yu1, Mhd. Suhyb Salama1, Wouter Verhoef1, Fang Shen2

1Faculty of Geo-Information Science and Earth Observation, University of Twente,The Netherlands; 2State Key Laboratory of Eastuarine and Coastal Research, East China Normal University, China;

Diffuse attenuation coefficient (Kd, in m-1) plays an important role in the functioning of ecological processes and biogeochemical cycles in oceanic and coastal ecosystems. Retrieving Kd from earth observation data will provide a better understanding on the distribution of Kdin large spatial scale. In this study, we present an improvement on the parametrization equations in the inverse scheme of the analytical 2Seacolor model developed by Salama and Verhoef (2015). The improved model is then validated with three in-situ datasets and compared with the Zhang model (Zhang and Fell, 2007) and the Lee model (Lee et al., 2005). Validation with radiometric data shows that the 2SeaColor model provides the best estimates of Kd for the full range of observations, with the largest determination coefficient (R2 = 0.935) and the smallest root mean squared error (RMSE = 0.078 m-1). The 2SeaColor model is then applied to the GOCI (Geostationary Ocean Color Imager) level 2 product (L2P) to produce Kd maps over the Yangtze estuary, resulting in a reasonable distribution and expected range of Kd. As for example, Kd (490) was varying from 0.04 to 9.82 m-1 for the image acquired at 02:16 UTC, on March 8th 2013.

The analytical 2SeaColor model is able to provide consistently stable and fairly accurate Kd estimates in both clear and turbid waters without the need of tuning empirical coefficients from field measurements, and thus has great potential for estimating Kd over optically complex waters.

Yu-Retrieval of the Diffuse Attenuation Coefficient from GOCI Images Using the 2SeaColor Model_Cn_version.pdf

Poster

Atmospheric correction of Sentinel-3 OLCI data over highly turbid waters: Simulations based on APEX Acquisitions

Stephani Palmer1, Xiaolong Yu1, Behnaz Arabi1, Fang Shen2, Mhd. Suhyb Salama1

1University of Twente, Faculty of Geo information Science and Earth Observation, Netherlands, The; 2State Key Laboratory of Eastuarine and Coastal Research, East China Normal University, China;

In this poster we simulate Sentinel-3 Ocean and Land Colour Instrument (OLCI) observations from hyperspectral data and estimate the uncertainties of derived inherent optical properties (IOPs). Hyperspectral data were obtained from APEX (Airborne Prism Experiment) acquisitions over the Dutch Wadden Sea. APEX data are atmospherically corrected using MODTRAN computations and verified with in-situ measurements. The resulting values of water leaving reflectance from APEX are then convolved with the spectral response function of OLCI, aggregated to its spatial resolution and propagated to the top of atmosphere (TOA). On this simulated TOA OLCI data set we apply commonly used atmospheric correction and retrieval schemes. We suggest and evaluate a model for OLCI to estimate the uncertainties of derived IOPs. Finally, we verify the resulting uncertainties using in-situ measurements matching the time of APEX flight-lines and discuss the accuracy of OLCI products of IOPs in light of the used atmospheric correction and retrieval schemes.

Palmer-Atmospheric correction of Sentinel-3 OLCI data over highly turbid waters_Cn_version.pdf


 
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