The Application of GOCI Data Based Remote Sensing Technology in the Field of Sediment Reserch

2013 ◽  
Vol 303-306 ◽  
pp. 786-789
Author(s):  
Hua Feng Liu ◽  
Rui Jie Li ◽  
Xi Shan Pan ◽  
Lie Mo
Keyword(s):  
Remote Sensing ◽  
Water Level ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Remote Sensing Data ◽  
Sediment Concentration ◽  
Acceptable Result ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Sediment Transportation

The application of GOCI data in the research of sediment transportation is introduced in the paper..Compared with traditional ways to verify the simulated results, remote sensing data can contain a huge observation scope and a longer observing time.In. The computed results of water level and suspended sediment concentration were compared with processed GOCI data and had an acceptable result.

Retrieval and Analysis on the Sediment Concentration of the South Branch of the Yangtze Estuary Based on TM

2013 ◽  
Vol 353-356 ◽  
pp. 2763-2768 ◽  
Author(s):  
Jia Ling Hao ◽  
Tong Cao ◽  
Zhu Jun Zhang ◽  
Li Ping Yin
Keyword(s):  
Remote Sensing ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration ◽  
Yangtze Estuary ◽  
The South ◽  
The Yangtze Estuary ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Quantitative Remote Sensing

Suspended sediment concentration is important index of water quality, and assessment coefficient of water environment. Remote sensing technology can overcome the shortcomings of conventional methods, such as low speed, long period, and scarce temporal and spatial data distribution. Thus it is meaningful to introduce remote sensing technology to monitoring suspended sediment. In this paper, two TM/ETM+ images of the Yangtze estuary were utilized, and based on review of available domestic and overseas remote sensing data of suspended sediment, also combined with analysis on the 21 samples of synchronizing collection on April 28, 2009 and 3 samples of synchronizing collection on March 26, 2000 at the same time of satellite passing through respectively, the inversion model of satellite quantitative data was setup correlated to suspended sediment concentration. Then the classification diagram of sediment concentration in the surface water at the South Branch of the Yangtze Estuary was drawn. This study gets the following conclusions:(1) TM4 band reflection coefficient is more related to surface sediment concentration, the correlation coefficient is 0.884. (2)Through the regression analysis, the quantitative remote sensing model is established. By the mode, using satellite picture, sediment concentration distribution map in study area is obtained. (3)The diffusion law of suspended sediment, the range of high turbid water region and the estuarine sediment transportation were further discussed from monitoring data, and its characteristic phenomenon were observed and the cause was also explained.

scholarly journals Automatic calibration of a large-scale sediment model using suspended sediment concentration, water quality, and remote sensing data

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Hugo de Oliveira Fagundes ◽  
Fernando Mainardi Fan ◽  
Rodrigo Cauduro Dias de Paiva
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Suspended Sediment ◽  
Large Scale ◽  
Suspended Sediment Concentration ◽  
Remote Sensing Data ◽  
Sediment Concentration ◽  
Spatial Discretization ◽  
Calibration And Validation ◽  
Sediment Model

ABSTRACT Calibration and validation are two important steps in the application of sediment models requiring observed data. This study aims to investigate the potential use of suspended sediment concentration (SSC), water quality and remote sensing data to calibrate and validate a large-scale sediment model. Observed data from across 108 stations located in the Doce River basin was used for the period between 1997-2010. Ten calibration and validation experiments using the MOCOM-UA optimization algorithm coupled with the MGB-SED model were carried out, which, over the same period of time, resulted in 37 calibration and 111 validation tests. The experiments were performed by modifying metrics, spatial discretization, observed data and parameters of the MOCOM-UA algorithm. Results generally demonstrated that the values of correlation presented slight variations and were superior in the calibration step. Additionally, increasing spatial discretization or establishing a background concentration for the model allowed for improved results. In a station with high quantity of SSC data, calibration improved the ENS coefficient from -0.44 to 0.44. The experiments showed that the spectral surface reflectance, total suspended solids and turbidity data have the potential to enhance the performance of sediment models.

Research on the Coastal Suspended Sediment Movement of Matakong Island in Guinea, Africa Based on Remote Sensing Data

2013 ◽  
Vol 333-335 ◽  
pp. 275-279
Author(s):  
Yin Cai ◽  
Hong Bo Zhao ◽  
Shu Hua Zuo
Keyword(s):  
Remote Sensing ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Remote Sensing Data ◽  
Sediment Concentration ◽  
Concentration Data ◽  
Sediment Distribution ◽  
Sensing Data ◽  
Sediment Movement ◽  
Wide Range

A wide range of suspended sediment concentration can be obtained by satellite remote sensing. According to the multi-temporal remote sensing data and quasi-simultaneously surface sediment concentration data, research works on the surface suspended sediment distribution and movement trends of Matakong coastal area, Africa were carried out. The results showed that the suspended sediment concentration of the studied area is not large, and the sediment movement is not active. The sediment source comes from the nearshore shallow flats, where they could be entrained by the wind waves and then diffuses by the tidal currents.

scholarly journals A Semi-Analytical Model for Remote Sensing Retrieval of Suspended Sediment Concentration in the Gulf of Bohai, China

2015 ◽  
Vol 7 (5) ◽  
pp. 5373-5397 ◽  
Author(s):  
Jin-Ling Kong ◽  
Xiao-Ming Sun ◽  
David Wong ◽  
Yan Chen ◽  
Jing Yang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Suspended Sediment ◽  
Analytical Model ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration
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