USING THERMAL INFRARED REMOTE SENSING IMAGES TO MONITOR THE SEA SURFACE TEMPERATURE IN EAST SEA

REGION, VIETNAM IN JUNE OF 2003, 2006 AND 2009

HANH Tran Hong1 and PHONG Doan Ha2

1MSc, Hanoi University of Mining and Geology, Dong Ngac, Tu Liem, Hanoi, Vietnam; Tel: (84)-912090940 or (84)-4-38541044

Email: honghanhtranvn@yahoo.com

2Dr, Institute of Meteorology, Hydrology and Environment, Phao Dai Lang Street, Dong Da, Hanoi, Vietnam; Tel: (84)-913212325

Email: doanhaphong@gmail.com

KEY WORDS: thermal infrared image, sea surface temperature, mapping, oceanography. ABSTRACT: Sea Surface Temperature - SST - is one of the environmental and sea water quality group's parameters. The components monitoring and analyzing are necessary to watch the climate change process, ecological sea system change, natural resource management and environment protection. The SST monitoring in Vietnam is currently done by using small boats moving near seaside. Monitored points are sparse in large sea areas with low frequency. Patterns are only collected at unique points and in specific time of year. This paper aims to develop remote sensing method using thermal infrared images. This method has many advantages, for example supplying updated information and covering a large area, so that it is very useful for sea surface temperature monitoring. SeaDAS or Envi software is used in order to extract SST values from level 0 (.PDF) to level 2 (.HDF or GeoTif). SST physical values (from oK to oC) are saved in a single band (32 bit floating-point). MapInfo or ArcGIS software is used so as to edit and establish the thematic maps of sea surface temperature in East Sea region of Vietnam to the VN-2000 coordinate system according to month or year periods. The paper compares and contrasts the average sea surface temperature in June of 2003, 2006 and 2009. In addition, the sea surface temperature graphs are conducted with the cross-section; as well as the three sea surface temperature maps are established. 1. Problem Statement

Sea Surface Temperature (SST) is one of the parameters of the sea water components. The components in terms of water, sediment as well as biology are monitored and also analyzed in order to monitor the climate change caused by global warming. The climate change consists of the increase of sea surface temperature, the rise level of polluted environment, the fluctuation of the ecosystems and coastal waters. The observation and monitoring provide database for many scientific researches, management and planning, rational use of coastal resources and protecting the environment. Moreover, sustainable development of the exclusive socio-economic is necessary and urgent.

Currently, the research and the monitoring of SST are directly processed at the naval station offices in Vietnam with the cycle for many years. However, data for the certain sea with more than 3 million km 2 can not be met the actual requirements. In recent years, some results of monitoring in the East Sea show a significant difference with regard to SST. The sea water temperature monitoring in Vietnam today is mainly used small boats to move inshore, and then people collect samples and observe at the specific points and in the unique time of the year. Therefore, observed points are much less than the vast sea and the frequency of monitoring is also sparse.

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Common method used to measure and monitor sea surface temperature is sampling on the field, in the air or on the ground. The first method used is measured by their hands, they directly embedded a thermometer into surface water. The automatic measurement method was first done using the pipelines with sea water into the ship. However, the accuracy and the consistency of time are always the difficult issues for the traditional measurement data. The method basing on fixed ocean buoys, then data is transmitted to the center via satellites in order to provide automatically and continuously, is known as the highest accuracy and the repeated frequency measurement. The remote sensing method using thermal infrared images has many advantages which are providing continuous information as well as observation in a large area. Especially, that method combined and edited with field data will provide high reliability in the study of sea surface temperature nowadays. 2. Methodology

Image data of the East Sea area was selected to conduct the study’s experiment. East Sea is located at the edge of the Western Pacific Ocean, surrounded by the mainland namely China, Indochina, Thailand, and some islands namely Malaysia, Indonesia, the Philippines. Its area is about 3.4 million km 2 , and its volume is almost 4 million km 3 . The average temperature in June of sea surface in East Sea region was established from the process of MODIS infrared thermal images. Those images with the resolution 1 km were collected from the first day until the last day in June by the years of 2003, 2006 and 2009 and also were processed from level 0 to level 2 by SEADAS software Version 6.0. Afterwards, they were edited by MapInfo software Version 10.0. The steps of correction in terms of radiation, geometry as well as ortho-rectified were handled automatically by astronomical data, flight schedules, digital terrain model which are integrated and updated in the software.

The main steps of image process and establishment of thematic maps distributed average sea surface temperature in East Sea of Vietnam are shown on the figure 1.

Extraction of thermal infrared bands 31, 32 into the value of radiation

MODIS images at level 1A and 1B (Radiant correction, geometric correction in the WGS-84 system)

MODIS images (Aqua, Terra) at level 0

Using the Planck function to calculate the brightness temperature

for MODIS bands 31.32 (oK)

Using the linear algorithm level 2 to determine sea surface temperature (oK)

SST physical values (from oK to oC) 32 bit floating images

Edit and present maps in the geographic coordinate grid VN-2000

Figure 1. The main steps of image process and establishment of thematic maps distributed average sea surface temperature

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The first non-linear algorithm (NLSST) with MODIS images for spectral bands in range of 11 μm and also for spectral bands acquiring during the days and nights was Kilpatrick, Podesta and Evans (2001) developed as following:

43231332312311 )1)(sec()( CTTCTTTCTCSST sfc +−−+−+= θ (2.1) Where, + T : Reynolds SST collecting from NOAA in the past is known as the average

temperature according to week or monthsfc

+ C1, C2, C3, C4: the constants depend on the difference in temperature between two thermal bands 31 and 32

+ θ : the solar zenith angleTable 2.1. MODIS Specifications

No Band Bandwidth (μ m) Primary Use Spatial Resolution (m)

1 31 10,780-11,280 Surface Temperature 1000 2 32 11,770-12,270 Surface Temperature 1000

+ a0, a1, a2: the experimental coefficients depend on each satellite and geographical

condition in each areaTable 2.2. The coefficients for the non-linear SST equation

of SEADAS software V6.0∆T=T31-T32 (K) C1 C2 C3 C4

≤0.7 0.976 0.126 1.683 1.2026 ≥0.7 0.891 0.125 1.109 2.7478

3. Result and Discussion After the process of MODIS thermal infrared remote sensing images using specific

software namely SEADAS from level 0 to level 2 (Figure 1), the authors used MapInfo software V10.0 for editing, establishing maps and graphs of average sea surface temperature changing in June of 2003, 2006, 2009 by a cross section in East Sea region of Vietnam.Figure 2. following shows the three thematic maps distributing average sea surface temperatures in June of the year 2003.2006, 2009 in East Sea region of Vietnam with scale 1: 500,000.

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June 2003 June 2006

June 2009

Figure 2. Thematic maps distributing average sea surface temperatures in June of the year 2003.2006, 2009 in East Sea region of Vietnam with scale 1: 500,000

On the maps, the color temperature scale is edited with the variety of colors such as dark blue, light blue, dark green, light green, dark yellow, light yellow, red and others with increasing temperature correspondingly. In June by the year 2003, 2006 and 2009, sea surface temperature of East Sea region in range from 24 0 C to 30 0 C, 24 0 C to 32 0 C, 24 0 C to 32 0 C respectively.

Generally, it can be commented that in June 2003, the Northern coastal average temperature is 29 0 C. There are a few other coastal areas, for example, Hai Phong and Thanh Hoa where the temperature is about 31 0 C. The Central Coastal temperature is similar between 29 0 C and 30 0 C. The Southern coastal average temperatures is from 27 0 C to 29 0 C, especially in Ninh Thuan and Binh Thuan sea regions, the temperature is lower the other regions between 24 0 C and 28 0 C.

In June 2006, the Northern coastal average temperature is from 28 0 C to 30 C, however, 0

a few other coastal areas such as Hai Phong , the temperature is around 31 C. The Central 0

coastal average temperature is in range from 28 0 C to 30 C, particularly in coastal areas of 0

Thanh Hoa province in June reached at peak of 32 0 C. The Southern coastal average temperature is from 28 0 C to 30 C. 0

In June 2009, the Northern coastal average temperature is from 28 C to 30 C, a few 0 0

other areas of coast, the temperature is approximately 31 C. The Central coastal temperature is slightly higher than that of other regions, especially in Hue - Da Nang coastal areas, sea surface temperature is higher between 29 C and 31 C. The Southern coastal temperature is 29 C or 30 C, particularly in Ninh Thuan and Binh Thuan sea regions, the temperature is gradually lower than that of other regions from 24 0 C to 28 0 C.

0

0 0

0 0

Finally, after establishing the maps distributing the average temperature distribution, the authors used MapInfo software to establish some graphs of average sea surface temperature changing by a cross section in June of 2003, 2006 and 2009.

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June 2003

June 2006

June 2009

In June of 2003, 2006, 2009 Figure 3. Graphs of sea surface temperature by a cross section in June of

2003, 2006, 2009 and a general graph even 3 yearsIn figure 3, sea surface temperature is expressed in a cross section, namely the 112th

meridian. The cross section is represented by a straight, dashed line of red from North to South on the thematic maps distributed of average sea surface temperature in June in East Sea of Vietnam with scale 1: 500,000. The horizontal axis shows the meridian from North to South with the distance from 8 degrees to 20 degrees. The vertical axis shows average sea surface temperature in June (SST with C). On the cross section and the ortho-rectify of SST in the East Sea of Vietnam in June by the years, we see change in sea temperature in the Central region, the coastal Gulf of Tonkin and the West Sea. The temperature is higher than the other regions. Vung Tau and Con Dao areas often have the blocks of cold water in coastal areas in many years we have surveyed.

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Where, + Red, green, blue - change in sea surface temperature by the cross section in 2003,

2006, 2009 respectively.

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This general graph shows that the regions reach at peak in the relatively homogeneity in 2003, 2006 and 2009 corresponding to three regions namely the Northern Gulf, the Central Coast as well as the West Sea with the figures at 200,000 m; 500,000m; and 1,000 m respectively follow the horizontal axis on the graph. In 2006 the temperature is the highest. In 2009 the temperature is the lowest. It can be explained that the number of images collected in May 2009 are lower than that in 2003 and 2006. Therefore, the average temperature will be affected.

4. Conclusions - Form of the processing of MODIS images in the specific condition in Vietnam in order

to determine the parameter SST from MODIS images using non-linear algorithm NLSST. - Establishment a database of remote sensing images, SST images and map as well as

orhto-rectify data in June 2003, 2006 and 2009. - The experiment was done and estimated the results of monitoring the average sea

surface temperature of Northern Gulf, the Central coast and the Western sea in June 2003, 2006 and 2009.

- The research is an useful reference in teaching and practical instruction in temrs of remote sensing technology application as well as monitoring natural resources and environment of marine of Vietnam.

- Currently, there are many algorithms applied to MODIS. It depends on the natural geographical conditions in each area. Therefore, it is necessary to study the researches and measure the fields so as to establish coefficients in Vietnam's conditions.

- There have been many thermal infrared remote sensing images for 30 years. This is a very valuable resource for Vietnam when we still lack a lot of field measurement data. Consequenlty, it is necessary to conduct assimilately of thermal infrared remote satellite data into a unified and scientific database.

- The infrared thermal remote sensing images are influenced by weather condition. Therefore, the study of average temperature according to week, month or year periods should be carried out with a sequence data in 5, 10 years or more to draw the natural rules. In the limit of funds and time of this subject, the authors conducted in a cycle of 3 years .

- SST is a basic parameter for studying of climate change issue, so if there is a good SST database, it will help us to look more realistic on the impact of climate change in Vietnam. 5. References [1]. ATBD_mod25: MODIS Infrared Sea Surface Temperature Algorithm, Algorithm Theoretical Basis Document, Version 2.0. Otis B. Brown, Peter J. Minnett. University of Miami. April 30, 1999. [2]. MODIS Sea Surface Temperature (SST) Products, ftp://podaac.jpl.nasa.gov/pub/sea_surface_temperature/modis/doc/modis_sst.gd.html. [3]. Overview of MODIS Aqua Data Processing and Distribution. Donna Thomas and Bryan Franz, May 2006. www.oceancolor.gscf.nasa.gov

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