Abstract
The study aims at the detection of coast lines of the Tonle Sap Lake, Cambodia in flood season using JERS-1 SAR Data for the estimation of the total volume of the lake.
JERS-1 SAR Data were mainly used together with other data such as JERS-1 AVNIR, ERS-1 SAR, LANDSAT TM, NOAA AVHRR etc. as well as topographic maps and hydrological records
The detection of coast lines at different water levels from 1.0 meter to 10.0 meters (the maximum water level) were partially made and the interpolation of the coast lines at 1 meter interval were implemented using a linear function.
The water depth of the lake at the minimum water level was estimated by applying a regression model with the correlation between brightness temperature of NOAA AVHRR and shallow water depth with less than one meter.
The results obtained from the study would be very useful for water use planning and flood management of the Tonle Sap Lake.
Introduction
The Tonle Sap Lake, Cambodia is the biggest lake in the Southeast Asia, though the exact water surface and volume in dry and flood season is still unknown. It is very important for Cambodia to use this lake on sustainable level for fishery, flood control, transportation, sightseeing etc.
During the flood season from June to October, a great amount of water flows up to the Tonle Sap Lake from the Mekong and Tonle Sap River with the water level increasing by 8~10 meters. It will work as a huge reservoir to protect the capital city of Phnom Penh from flood. The lake in flood season will range several times in area and volume bigger than in the dry season.
Even in dry season with the minimum water level, the lake is very big with about 30 km in width and 100 km in length, that makes difficult to survey the water depth, even though the depth is very shallow with less than one meter.
Objectives
The objectives of the study are as follows:
1) To produce a water depth map in the dry season using a relationship between brightness temperature of NOAA AVHRR and water depth using measurements of actual surface temperature with respect to the depth.
2) To detect the coast lines at different times in the monsoon season up to the maximum water level using JERS-1 SAR data and other reference data.
3) To interpolate coast contour lines at one meter interval
4) To estimate the perimeter, water surface and water volume of the Tonle Sap Lake from the results of remote sensing data in comparison with the results from the existing topographic maps.
Water Depth Map in Dry Season
Four NOAA AVHRR scenes (15:19, 03 April, 1998, 13:08. 07 April 1998, 15:31, 11 April 1998 and 14:36, 16 April 1998) were used to make cloud free mosaics of the Tonle Sap Lake at the minimum water level.
From the measurements of water surface temperature and water depth at the site implemented on 22nd to 26th April 1998, we found that the afternoon water surface temperature (13:00-15:00) on the 22nd April had a high correlation with the water depth as shown in figure 1. Then brightness temperature of NOAA AVHRR data were found to be highly correlated with the corresponding water depth with the high correlation factor as shown in figure 2. The water depth map was produced with the above regression model as shown in Figure 3.
Coorrelation between Water Surface Temperature and Depth of Tonlesap Lake, 22nd April 1998, from 13 to 15O'Clock
Figure 1 The Result of Correlation with Correlation Factor of 0.8391
The Relationship between Depth and Surface Temperature Detected by NOAA/AVRR
Figure 2 The Relationship between Depth and Brightness Temperatured Detected by NOAA/VHRR
Figure 3 Estimated Depth Contour Map of the Tonle Sap Lake in the Dry Season from NOAA/AVHRR data
