The current sea level rise has been causing coastal countries, especially the Delta, to be increasingly vulnerable to salt intrusion through the river network. Salt intrusion is often complicated, unpredictable and influential on a large area. Salinization reduces crop yield, soil degradation, decreases water quality, severely affects agricultural production, environment as well as the life of the people. This article presents the methodology for developing a statistical model for monitoring salinity intrusion in the Mekong Delta based on the integration of satellite imagery and in-situ measurements. The Landsat OLI & TIRS imageries in dry season 2014 were used to examine the correlation between spectral reflectance bands, principal component bands and corresponding salinity measurements on the day of the obtain imagery at 11 monitoring stations. The selected regression model showed a good correlation with the exponential function of the principal component bands’ spectral reflectance value and in-situ measurements (R> 0.8). Simulation of the salinity distribution along the river shows that the intrusion of 4g / l salt boundary from the estuary to the inner field more than 50km. The developed model will be an active contribution, providing managers with adaptation and response solutions suitable for intrusion in the estuary as well as the inner field of the Mekong Delta.
Development of the statistical model for monitoring salinization in the Mekong Delta using remote sensing data and in-situ measurements
Published: 18 June 2018 by MDPI AG in 1st International Electronic Conference on Geosciences session Earth Sciences through Earth Observation
Keywords: delta; intrusion; salinization; satellite imagery; statistical model