Application of MODIS in mapping of total suspended solids in Singapore’s coastal waters

• Main Author: Low, Yu Yao
• Other Authors: Law Wing-Keung, Adrian
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Civil engineering
• Online Access: http://hdl.handle.net/10356/76292
• Institution: Nanyang Technological University

Singapore is carrying out a number of reclamation projects at Tekong Island and Tuas. In the midst of the reclamation process, the government do their due diligence to monitor the environmental quality so that the ecosystem will not be adversely impacted. This study aims at changing the water quality monitoring method by developing a regional model which can predict the Total Suspended Solids (TSS) concentrations. Field samplings were conducted in July 2018 and water samples were collected within 15 minutes of the satellite overpass time. The TSS concentrations were measured using the conventional filtration method in the laboratory. The MODIS remote sensing images (Terra MOD09GQ and Aqua MYD09GQ) were downloaded from the Earth Explorer. The MODIS Terra and Aqua remote sensing images were reprojected to the area of interest, and Band 1 and Band 2 reflectance data were extracted using SeaDAS Version 7.5. Regression analysis was performed to establish the relationship between the Total Suspended Solids (TSS) and the Remote Sensing Reflectance (Rrs). Linear, polynomial and logarithmic regression model were developed and calibrated using different input parameters. For instance, Rrs Band1, Rrs Band2, their summation, difference as well as complex ratio was analysed to predict the TSS concentrations in the Singapore’s coastal water. The accuracy of each model was indicated by R-Squared (R2) and Root-Mean-Square Error (RMSE). The algorithm having the highest R2 and lowest RMSE will be selected to be the most optimal model. The model developed using 1x1 pixel window was compared with the the model developed using 3x3 pixel window. The results suggests that using the 3x3 pixel window extraction method could produce a model with higher accuracy. The most optimal algorithm for Terra sensor is y=-254.4x^2+166.7x+2.412 whereas the most optimal algorithm for Aqua sensor is y=-20.15x^2+52.14x+1.296. The mapping software - SeaDAS Version 7.5 was also deployed to create the map of TSS in order to provide a better illustration of the water quality of the region of interest. The map developed shows that the Singapore coastal waters are of low TSS concentration and well-monitored.