Please use this identifier to cite or link to this item: http://ir.buu.ac.th/dspace/handle/1513/623
Title: STUDY OF LAND SUBSIDENCE BY INSAR TIME SERIES OF ALOS-2, SENTINEL-1 AND GNSS CORS STATIONS IN CHAOPRAYA BASIN, SAMUTPRAKAN, THAILAND
การศึกษาการทรุดตัวของจังหวัดสมุทรปราการ ด้วยข้อมูลอนุกรมเวลาโดยใช้ข้อมูลดาวเทียม ALOS-2 Sentinel-1 และสถานี CORS 
Authors: Adisorn Sittiwong
อดิสร สิทธิวงษ์
TIMO BALZ
TIMO BALZ
Burapha University. Faculty of Geoinformatics
Keywords: InSAR
Land subsidence
ALOS-2
Sentinel-1
Samutprakan
PS-InSAR
Issue Date:  11
Publisher: Burapha University
Abstract: Samutprakan province is one of the economically most important provinces in Thailand. The province is located in the northern gulf of Thailand near Bangkok. This province is facing flooding from sea level rise. This problem is getting closer to the capital city: Bangkok. Samutprakan and surrounding provinces are facing sea level rise, flooding, and land subsidence. The land subsidence is an important factor of flooding in Samutprakan, shown by case studies showing that the land subsidence in Samutprakan is caused by many factors such as the use of ground water, land reclaiming, and movements of the Earth surface. The Department of Groundwater Resources started to do research between 1978 - 1981 and they found land subsidence of more than 10 cm per year in Bangkok and Samutprakan. After that, the study of land subsidence has been widespread to many Universities in Thailand such as King Mongkut University of Technology vicinity (Bangmod), Chulalongkorn University, and Kasetsart University to work on monitoring land subsidence in the central part of Thailand. This study will identify the movement ratio of land subsidence rate in the last six years by using Interferometric Synthetic Aperture Radar; InSAR time series technique from ALOS-2 satellite, Sentinel-1 and Precise Point Positioning (PPP) from GNSS CORS stations to identify the rate of land subsidence and compare the land subsidence with three difference methods above in last 6 years of Samutprakan province Thailand. The InSAR time series technique has been used for many decades to measure earth surface deformation with high resolution and high accuracy. The InSAR time series will correct data by using radio detection and ranging (RADAR) to send electromagnetic wave to object to the earth surface and reflect to satellite’s antenna itself. The satellite images will be collected by sun-synchronous orbit satellite in many modes of transmission such as HH, VV, HV, VH and from ascending and descending orbits. Many scenes of satellite images in s time series will be processed by interferometric phase measurements which wrapped and unwrapped phases and compared with many scenes of images to find the subsidence rate of objects on earth surface with high accuracy number in millimeter. The Precise Point Positioning (PPP) and GNSS stations Continuously Operating Reference (CORS) or a permanent GNSS satellite receiver station. These stations receive signals 24 hours a day, 365 days a year to use the information that obtained to refer to the coordinates. It is a reference station for RTK (Real-Time Kinematic) and Network RTK (VRS) surveys. All data will be combined before PPP processing to remove GNSS errors and get the highest position accuracy from one receiver. Accuracy data from many stations and many times will be presented the difference of GNSS CORS stations in Latitude, Longitude, and Height to present the difference numbers of time series. Both techniques are used to identify data from difference sources to find the subsidence rates of the study area in Samutprakan, in order to allocate the suitable area for industrial constructions and farming areas. The result from this thesis will benefit the residents in Samutprakan and the planning of industrial areas in the next 6 to 12 years and indicate the most accuracy methods from these three methods.
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Description: Master Degree of Science (M.Sc.)
วิทยาศาสตรมหาบัณฑิต (วท.ม.)
URI: http://ir.buu.ac.th/dspace/handle/1513/623
Appears in Collections:Faculty of Geoinformatics

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