Salinity intrusion is a pressing issue in the coastal areas worldwide. It affects the natural environment and causes massive economic loss due to its impacts on the agricultural productivity and food safety. Here, we assessed the salinity intrusion in the Tra Vinh Province, in the Mekong Delta of Vietnam. Landsat 8 OLI image was utilized to derive indices for soil salinity estimate including the single bands, Vegetation Soil Salinity Index (VSSI), Soil Adjusted Vegetation Index (SAVI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Salinity Index (NDSI). Statistical analysis between the electrical conductivity (EC_1:5, dS/m) and the environmental indices derived from Landsat 8 OLI image was performed. Results indicated that spectral values of near-infrared (NIR) band and VSSI were better correlated with EC_1:5(r²= 0.8 andr²= 0.7, respectively) than the other indices. Comparative results show that soil salinity derived from Landsat 8 was consistent with in situ data with coefficient of determination,R²= 0.89 and RMSE = 0.96 dS/m for NIR band andR²= 0.77 and RMSE = 1.27 dS/m for VSSI index. 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 mapping thesoil salinitycontamination for better selection of accomodating crop types to reduce economical loss in the context of climate change. Our proposed method that estimates soil salinity using satellite-derived variables can be potentially useful as a fast-approach to detect the soil salinity in the other regions with low cost and considerable accuracy.

Rice is one of the main cereal crops in the world that plays an important role in food security, especially in the context of climate change, environmental pollution, and population growth. It is a daily staple food for a major part of the world’s population, especially in the developing countries across Asia, Latin America, and Africa.¹ This has led to an increasing demand for stable rice supply, especially for major rice-producing countries such as China, Thailand, and Vietnam. This issue requires a system that can provide important information for monitoring and managing rice cultivation such as rice age (the number of days after planting), date of planting (dop), and date of harvest (doh). The information on the rice growth stages is also important for implementing management practices including irrigation systems, pest warning, fertilizer application, procurement and export, and other purposes. Furthermore, climate change, resulting in an increase in extreme weather events such as drought and floods,² can damage rice crops and affect food security and farmer livelihoods at local and regional scales. It is, therefore, necessary to accurately and timely determine how much of the rice area is in any stage at any time or position on the map.

Food security has become a key global issue due to rapid population growth, extensive conversion of arable lands, and declining overall productivity in some areas because of the effects of floods, water shortage, salinity intrusion, and plant diseases. In this study, we analyzed the relationship between the pattern of salinity intrusion and the spatiotemporal distribution of rice cultivation in the winter–spring crops of 2015, 2016, 2019 and 2020 in coastal provinces of the Vietnamese Mekong Delta. Sentinel-1 (S-1) data were used to extract the spatial distribution information of six rice growth stages based on a rice age algorithm. The classification accuracy of rice crop growth stages was found to have an overall accuracy of 85% and a Kappa coefficient of 0.80 (n = 373). For evaluating salinity intrusion effects, salinity isolines (4 g/L) were used to determine the percentage of rice areas affected. Results show that in the years observed to have severe salinity intrusion such as 2016 and 2020, a strong shift in planting calendar was identified to avoid salinity intrusion, with some areas being sown or transplanted 10–30 days earlier than normal planting. In addition, the lack of irrigation water and salinity intrusion limits rice cultivation in the dry season of coastal areas. Further analysis from the S-1 data confirms that the spatiotemporal distribution of rice cultivation is related to the change in government policy/recommendation affected by salinity intrusion. These findings demonstrate the potential and feasibility of using S-1 data to develop an operational rice crop adaptation framework on the delta scale.

Rice production in Vietnam has been developing rapidly and sustainably in recent years, contributing to ensuring national food security. However, it is facing the effect of climate change, sea-level rise, salinity intrusion, drought, and flood which threatens food production, especially in the Vietnamese Mekong Delta. For this reason, building a tool that allows estimating rice yield is necessary. SAR (Synthetic Aperture Radar) remote sensing data from Sentinel-1 satellites is provided by European Space Agency (ESA) with no cost, large coverage, and high spatio-temporal resolution, which has the advantage of observation in cloudy, foggy, rainy weather and independent of solar radiation. Therefore, this data is suitable for rice monitoring in countries with tropical monsoon climate like Vietnam. This paper presents the results of estimating the Winter-Spring rice yield in 2018 by using multitemporal Sentinel-1 data with C-band. The estimated rice yield was compared with the in-situ yield, which shows that the average values of the samples of estimated and surveyed yield were equivalent with 6.5 ton/ha and 6.6 ton/ha respectively, and the standard deviation between the estimated and surveyed yield was 0.80 ton/ha. The results demonstrate the applicability of the multitemporal SAR Sentinel-1 data for estimating rice yield in the study area, An Giang province, the Vietnamese Mekong Delta.

The erosion – deposition of shore line is not only a natural phenomenon, but also influenced by human activities. In recent decades, these changes occur more frequently with changes in the shape of shoreline, the change in area of coastal mangroves as well as loss of productive land. In the trend of sea level rise, a study on changes of estuaries is necessary, in order to preserve and develop the mangroves, disposition, production planning infrastructure and civil works, ...By using multi – temporal remote sensing from 1989 to 2015 and techniques appropriate digital image processing. The changes of erosion – deposition in shoreline are determined and contributed to clarify of erosion – deposition rules of the Mekong Delta. The results show that the shoreline of Tra Vinh province has changed over the years. This change is concentrated in some points such as: erosion occurs strongly in Hiep Thanh Commune, Long Thanh and Dan Thanh Communes with erosion rate can reach to 13 - 15 m per year. In addition, the deposition occurs mainly in communes such as My Long Nam commune, the first half of Truong Long Hoa and the area of Dong Hai and Long Vinh communes. The shoreline forecast for 2015 and 2017 is made for the entire shoreline of Tra Vinh province. The forecasted results show the trend of coastal deposition and erosion in the coming years, especially in the shoreline areas with strong changes as mentioned above. The phenomenon of erosion is predicted in the communes of Hiep Thanh, Long Hoa and Dan Thanh in the following years.