Remote Sensing Application for Assessing Salinity Intrusion in the Mekong Delta, Vietnam

Thesis (M.Sc., Environmental Management Technology (International Program))--Prince of Songkla University, 2018

Saved in:
Bibliographic Details
Main Author: Nguyen Thi Bich Phuong
Other Authors: Werapong Koedsin
Format: Theses and Dissertations
Language:English
Published: Prince of Songkla University 2020
Subjects:
Online Access:http://kb.psu.ac.th/psukb/handle/2016/12713
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Prince of Songkhla University
Language: English
id th-psu.2016-12713
record_format dspace
spelling th-psu.2016-127132023-11-17T04:02:03Z Remote Sensing Application for Assessing Salinity Intrusion in the Mekong Delta, Vietnam Nguyen Thi Bich Phuong Werapong Koedsin Faculty of Technology and Environment คณะเทคโนโลยีและสิ่งแวดล้อม Deltas Remote sensing Vietnam Soils, Salts in Remote sensing Vietnam Thesis (M.Sc., Environmental Management Technology (International Program))--Prince of Songkla University, 2018 Salinity intrusion is a complex issue in coastal areas. Currently, remote sensing techniques have been widely used to monitor water quality changes, ranging from inland river networks to deep oceans. The Vietnamese Mekong Delta (VMD) is an important rice-growing area and intrusion of saline water into irrigated freshwater- based agriculture areas is one of the most crucial constraints for agriculture development. This study aimed at building a numerical model to realize the salinity intrusion through the relationship between reflectance from the Landsat-8 Operational Land Imager (OLI) images and salinity levels measured in-situ. 103 observed samples were divided into 50% training and 50% test. The Multiple Linear Regression (MLR), Decision Trees (DTs) and Random Forest (RF) approaches were applied in the study. The result showed that the RF approach was the best model to estimate salinity along the coastal river network in the study area. However, the large samples size needed was a significant challenge to circumscribe the predicting ability of the RF models. The reflectance was found good to have a correlation with salinity when locations (latitude - longitude) of salinity measured station were added as a parameter of the Step-wise model. The R-square values were 77.48% in training and 74.16% in test while RMSE was smaller than 3. The reflectance - Location model was employed for mapping salinity intrusion on 24th Jan 2015 and 09th Feb 2015 recognized changes of salinity concentration in the whole study area. However, locality issue was a limitation for mapping salinity by using latitude and longitude as parameters. On the other hand, the real data was used for a re-sampling routine where data was performed re-sampling two times and four times by using bootstrap method. Four statistical models including the DTS, the MLR the RF and the Neural Network (ANN and ANT) were applied. Larger sample sizes that are regularly updated are needed to more fully develop the model. The best model was performed by the RF in re-sampling data four times which was employed for mapping salinity in early dry season 2015. The salinity map on 24th Jan and 09th Feb distinguished the tendency of salinity level as well as salinity dynamics and recognized changes of salinity concentration from upstream to downstream. This study proved the possibility of using the Landsat-8 images for mapping salinity as a useful tool to support the early warning system in the future in the VMD. 2020-03-20T04:07:55Z 2020-03-20T04:07:55Z 2018 Thesis http://kb.psu.ac.th/psukb/handle/2016/12713 en Attribution-NonCommercial-NoDerivs 3.0 Thailand http://creativecommons.org/licenses/by-nc-nd/3.0/th/ application/pdf Prince of Songkla University
institution Prince of Songkhla University
building Khunying Long Athakravi Sunthorn Learning Resources Center
continent Asia
country Thailand
Thailand
content_provider Khunying Long Athakravi Sunthorn Learning Resources Center
collection PSU Knowledge Bank
language English
topic Deltas Remote sensing Vietnam
Soils, Salts in Remote sensing Vietnam
spellingShingle Deltas Remote sensing Vietnam
Soils, Salts in Remote sensing Vietnam
Nguyen Thi Bich Phuong
Remote Sensing Application for Assessing Salinity Intrusion in the Mekong Delta, Vietnam
description Thesis (M.Sc., Environmental Management Technology (International Program))--Prince of Songkla University, 2018
author2 Werapong Koedsin
author_facet Werapong Koedsin
Nguyen Thi Bich Phuong
format Theses and Dissertations
author Nguyen Thi Bich Phuong
author_sort Nguyen Thi Bich Phuong
title Remote Sensing Application for Assessing Salinity Intrusion in the Mekong Delta, Vietnam
title_short Remote Sensing Application for Assessing Salinity Intrusion in the Mekong Delta, Vietnam
title_full Remote Sensing Application for Assessing Salinity Intrusion in the Mekong Delta, Vietnam
title_fullStr Remote Sensing Application for Assessing Salinity Intrusion in the Mekong Delta, Vietnam
title_full_unstemmed Remote Sensing Application for Assessing Salinity Intrusion in the Mekong Delta, Vietnam
title_sort remote sensing application for assessing salinity intrusion in the mekong delta, vietnam
publisher Prince of Songkla University
publishDate 2020
url http://kb.psu.ac.th/psukb/handle/2016/12713
_version_ 1783957333952430080