More than half of Vietnam's national rice production is produced in the Mekong Delta. Many hectares of rice were damaged due to extensive salinity intrusion during the dry season of 2016. The impact of salinity intrusion on rice production is studied by (1) mapping the impact using remote sensing data (MODIS NDVI time-series) and (2) investigating how the impact affects farmers' lives. Ground data is collected in Soc Trang province through interviews with commune officials and farmers. Quantitative data includes damages to rice areas as aggregated by the local government and land use points for classification. Rice areas are mapped through supervised classification, using extreme gradient boosting. Peak detection analysis is used to distinguish distinct rice cropping schedules within district boundaries. Compared against an evaluated climatology, hampered rice growth is mapped for two hot-spots (Long Phu and Nga Nam district). This can be attributed to salinity problems through interpretation of ground collected information and an understanding of the local salt-intrusion mechanisms. Reconciling affected rice grid cells mapped through satellite analysis with hectares of damaged rice recorded by the local government is difficult. Analyzed perspectives of salinity affected farmers highlight the uncertain current conditions and future for rice production in the Mekong Delta. Local government officials and farmers feel the changing climate conditions and the urge to respond through preventive or adaptive measures to avoid similar impacts of salinity intrusion in the future. In this research, soft information gathered through interviews provided contextual learning opportunities to better direct, develop and interpret remote sensing analysis and results.

Agriculture is of huge economic significance in The Netherlands where the provision of real-time, reliable information on crop development is essential to support the transition towards precision agriculture. Optical imagery can provide invaluable insights into crop growth and development but is severely hampered by cloud cover. This case study in the Flevopolder illustrates the potential value of Sentinel-1 for monitoring five key crops in The Netherlands, namely sugar beet, potato, maize, wheat and English rye grass. Time series of radar backscatter from the European Space Agency's Sentinel-1 Mission are analyzed and compared to ground measurements including phenological stage and height. Temporal variations in backscatter data reflect changes in water content and structure associated with phenological development. Emergence and closure dates are estimated from the backscatter time series and validated against a photo archive. Coherence data are compared to Normalized Difference Vegetation Index (NDVI) and ground data, illustrating that the sudden increase in coherence is a useful indicator of harvest. The results presented here demonstrate that Sentinel-1 data have significant potential value to monitor growth and development of key Dutch crops. Furthermore, the guaranteed availability of Sentinel-1 imagery in clouded conditions ensures the reliability of data to meet the monitoring needs of farmers, food producers and regulatory bodies.@en