Preprint Article Version 1 This version is not peer-reviewed

Estimation of Salinity Intrusion by Using Landsat 8 OLI Data in The Mekong Delta, Vietnam

Version 1 : Received: 16 August 2018 / Approved: 17 August 2018 / Online: 17 August 2018 (11:41:14 CEST)

How to cite: Tran, P.H.; Nguyen, A.K.; Liou, Y.; Hoang, P.P.; Nguyen, H.T. Estimation of Salinity Intrusion by Using Landsat 8 OLI Data in The Mekong Delta, Vietnam. Preprints 2018, 2018080301 (doi: 10.20944/preprints201808.0301.v1). Tran, P.H.; Nguyen, A.K.; Liou, Y.; Hoang, P.P.; Nguyen, H.T. Estimation of Salinity Intrusion by Using Landsat 8 OLI Data in The Mekong Delta, Vietnam. Preprints 2018, 2018080301 (doi: 10.20944/preprints201808.0301.v1).

Abstract

Salinity intrusion is one of the most serious consequences of climate change coupled with rising sea level that significantly affects agricultural activities in many parts of the world. This phenomenon has increasingly become more serious and frequently occurred in the Mekong Delta of Vietnam. As a result, Vietnam has been ranked among top five countries where have been devastatingly impacted by climate change, in particular, its Tra Vinh Province characterized by coastal plain and alluvial deposit. In addition, this area is of the tropical monsoon zone of long rainy season with source of salt brought from the sea by the tides and sea level rise. Regions that are contaminated by salt are located in lowland and often suffer from floods linking to tidal effects with salty water from river systems and channels. Soil salinity evaluation is critical for coastal protection, restoration, and agricultural planning since it can be considered as an agricultural indicator to evaluate quality of soil. Here, we attempt to estimate the soil salinity in Tra Vinh Province, in the Mekong Delta of Vietnam. Landsat 8 OLI images are utilized to derive indices for soil salinity evaluation including single bands, Vegetation Soil Salinity Index (VSSI), Soil Adjusted Vegetation Index (SAVI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Salinity Index (NDSI). Subsequently, satistical analysis between soil salinity, electrical conductivity (EC, dS/m), and environmental indices derived from Landsat 8 OLI image is performed. Results indicate that spectral value of Near Infrared (NIR) band and VSSI are highly correlated with EC (R2 = 0.7779 and R2 = 0.6957, respectively) in comparison with the other indices. Comparative results show that soil salinity derived from Landsat 8 is consistent with in situ data. Findings of this study demonstrate that Landsat 8 OLI images reveal a high potential for spatiotemporally monitoring the magnitude of soil salinity at the top soil layer. Outcomes of this study are useful for agricultural activities, planners, and farmers by providing the base map of soil salinity contamination for better selection of accomodating crop types to reduce economical lost in the context of climate change. Our proposed method that estimates soil salinity using satellite-derived variables can be applied in the other regions.

Subject Areas

Salinity intrusion; climate change; rising sea level; electrical conductivity; Landsat 8 OLI; Tra Vinh Province; Mekong Delta

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