第29回日本情報地質学会講演会 講演要旨集 037-038頁 2018年

Correlating geologic properties of tidal flat sediments with reflectance spectra
for remote sensing-based environmental monitoringfrom a case study of Van Uc estuary (Vietnam)
Vu Thi Thu Thuy*, Nguyen Thi Thu Ha**, Nguyen Thuy Linh** and Katsuaki Koike***Graduate School of Engineering, Kyoto University, Katsura C1–2–215, Kyoto 615–8540, Japan.
E–mail: koike.katsuaki.5x@kyoto–u.ac.jp (K. Koike)**Department of Geology, VNU University of Science, Hanoi, Vietnam.

Key words: Remote sensing, Sediment properties, Reflectance spectra, Van Uc estuary

1. Introduction

Tidal flat is an important part of the coastal zone withmany functions such as storage capacity, protect
estuaries ecological system and also the filters ofpollutant contaminant from land-based discharge.
Several researches have addressed a significant
relationship of composition with different sedimenttypes (Zhang, 2001; Duquesne et al., 2006). As theresults, grain-size sediment property was specified as animportant factor to understand the intertidal
environment as well as monitor the environmental
change in the estuary area. According to Ngoc et al.
(2013), there is a strong correlation between the grainsize property and the reflectance spectra, and thiscorrelation can be estimated from the satellite images
such as ALOS-AVNIR. Furthermore, Sentinel 2A (S2A),
one of satellites of an Earth observation mission in theCopernicus Programme developed by the European Space
Agency has a multi-spectral imager including 13 spectral
bands spanning from the blue to shortwave infrared(SWIR) region, with high quality image at 10, 20, and 60 m
ground resolutions. It is suitable to apply the images toestimate the change in grain-size of surface sediment in thetidal flat of Van Uc estuary with high accuracy.

with 10, 20, and 60 m resolutions. Level-1C (L1C) MSI
dataset was downloaded from the Copernicus Open
AccessHub,whichcontainedorthorectified,georeferenced and radiometrically calibrated top-ofatmosphere (TOA) reflectance in the UTM projection
with the WGS84 datum. The S2A Toolbox in theSentinel Application Platform (SNAP) ver. 5.0 on
Windows 10 was used to resample the images at the 10m resolution. Then, a traditional empirical line method(ELM) was applied as an atmospheric correction to theS2A scene. Finally, the distribution map of grain size
was generated by the density slicing tool of ENVI 5.3
and ArcGIS 10.5.

2. Materials and methods

The Van Uc estuary belonging to Thai Binh river issituated in the northern part of the Red River Delta
coastal zone, the second most important flat plain inVietnam. As the discharged area of the Thai Binh riversystem, this area has complex environment components
with mangrove and intertidal eco-systems (Fig. 1).
Total 20 sediment samples were taken from the tidal
flat of Van Uc estuary on 17 December 2017 by spoon,preserved in plastic bags under cool condition after
measuring their reflectance spectra by the field
spectrometers RS3. In the laboratory, the Laser Particle
Size Analyzer MODEL LA-950V2 of laser scattering
method was used to identify the grain-size properties ofall samples and transform them into soil types by themethod of Wentworth (1922).
The S2A image used in this study was acquired at
17:46 GMT on 25 September 2016 at the UTM zone 48NFigure 1. Land covers in the Van Uc estuary in which mudflat
area is colored yellow.

3. Results

The measured grain-size of the total 20 sediment
samples in the Van Uc estuary were ranged in widevalue, from 78.22 % of the maximum silt content to 1%of the minimum sand content. As the average, thehighest and lowest proportions were silt content (mean60.84%) and clay content (mean 17.25%), respectively.

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The measured reflectance spectra of all the sediment
samples were in the range from visible to SWIR region.
By focusing on the relationship between the reflectancespectra and the soil type of sediment, there seemedsmall correlation between all kinds of grain-size and thesimulated S2A band reflectance in the total wavelength
range, because their Pearson coefficients (R) were 0.1,0.2, and 0.3 for the clay, sand, and silt content,respectively.

the change in grain-size components in the tidal flat isdemonstrated.

Figure. 2 Cross-relationship of in-situ silt content withsimulated S2A ratio band reflectance.

On the contrary, all sediment types were wellcorrelated with the in-situ S2A band ratios with R larger
than 0.5. The maximum R was specified for therelationship between the silt content and the ratio of theband in NIR (band 7, B7) versus the band in deep blue
(band 1, B1) with R = 0.77 (Fig. 2). Accordingly, the mostsuitable equation to estimate the silt content from theratio of S2A band 1 versus band 7 is expressed as:
S (%) = 23.62e 0.33 (B7/B1)
where S is the silt content in the surface sediment oftidal flats (%) and B7/B1 is ratio of S2A band 7 versus
band 1.
Applying the above equation to the S2A image sceneacquired on 25th September 2016, the distribution of silt
content in surface sediment in the study area wasmapped as shown in Fig. 3. It can be observed from theresult that the silt content of surface sediment in the Van
Uc estuary is wide in the range from 33.6 to 81.2%. The
highest proportion of the silt content was detected near
the shoreline and decrease to off-shore, the lowest level islocated in the north tidal flat and two small areas in themiddle estuary. Besides, the in-situ silt content data is
totally fitted to the estimated silt content, which candemonstrate the highly accurate estimation of the silt
content by satellite remote sensing technique.

4. Conclusion

A strong correlation was clarified between the in-situ
reflectance spectra data and the sediment types of thesurface sediment samples in the Van Uc estuary.
Applying the correlated equation to the S2A image, thedistribution map of silt content was generated. The result
confirmed the potential of Sentinel 2A band ratio toestimate the distribution of grain-size properties in thesurface sediment in tidal flat of the estuary. Furthermore,a high possibility of using satellite image for monitoring

Figure. 3 Distribution map of silt content estimated from
Sentinel 2A acquired on 25th September 2016 by a correlation
equation.

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