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Abstract
The Vietnamese Mekong Delta has been devastatingly impacted by climate change coupled with sea level rise and natural hazards. As a result, salinity intrusion has become a pressing issue in the coastal provinces of the Mekong Delta in recent years. This environmental problem has called a great attention from the global scientists as demonstrated by the paper Nguyen et al. (Prog Earth Planet Sci 7:1, 2020. 10.1186/s40645-019-0311-0) “Soil salinity assessment by using an indicator derived from Landsat 8 OLI data: A case study in the Tra Vinh, Mekong Delta, Vietnam” (reached 27 k accesses as of July 31, 2022). Recently, Silvestri et al. (PEPS, 2022) have commented on Nguyen et al. (2020) article with three main points highlighted: (1) Within the coastal portion of the Mekong Delta, extensively ponded due to widespread shrimp farming, about 90% of Landsat 8 pixels are fully or partially covered by water so that Landsat 8 OLI spatial resolution is not suitable to distinguish between ponded and non-ponded areas; (2) The decreased near-infrared (NIR) reflectance ascribed to increased soil salinity is instead due to the presence of water in Landsat 8 mixed pixels; and (3) NIR reflectance is equally reduced independently of whether the water ponding area is salt or freshwater. We appreciate Silvestri et al. (2022) for their correspondence regarding our 2020 article (Nguyen et al. 2020) where we showed the capacity of using freely accessible Landsat 8 OLI image for the rapid soil salinity detection at the top soil layer in the agricultural land that is of valuable information for agricultural activities. We conducted field survey and collected the soil samples during the dry season at different agricultural soil types. Notably, the soil samples were collected at the same time with the satellite passing over the study area. The soil salinity derived from Landsat 8 is in line with the analysis from in situ data and consistent with the findings of previous studies. Importantly, two points are stressed in this reply: (1) The goal of our study is to utilize the freely accessible data source with rapid method of mapping soil salinity to investigate the salinity in the agricultural land, but not in the water body. Therefore, it has been a serious mistake to state that 90% of Landsat 8 pixels are fully or partially covered by water as claimed in Silvestri et al. (2022); and (2) The Tra Vinh Province has recorded the highest salinity level normally in March or April every year when the rainfall exhibits the lowest of the year, and at this time, most of the water in the river/canal is affected by saline intrusion. Thus, it is advised that Silvestri et al. (2022) should use the images acquired in March or April rather than random months.
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1 National Central University, Center for Space and Remote Sensing Research, Taoyuan City, Taiwan, ROC (GRID:grid.37589.30) (ISNI:0000 0004 0532 3167); Vietnam Academy of Science and Technology (VAST), Institute of Geography, Hanoi City, Vietnam (GRID:grid.267849.6) (ISNI:0000 0001 2105 6888)
2 National Central University, Center for Space and Remote Sensing Research, Taoyuan City, Taiwan, ROC (GRID:grid.37589.30) (ISNI:0000 0004 0532 3167)
3 VAST, Ho Chi Minh City Institute of Resources Geography, Ho Chi Minh City, Vietnam (GRID:grid.267849.6) (ISNI:0000 0001 2105 6888)
4 VAST, Graduate University of Science and Technology, Hanoi City, Vietnam (GRID:grid.267849.6) (ISNI:0000 0001 2105 6888); VAST, Ho Chi Minh City Space Technology Application Center, Vietnam National Space Center, Ho Chi Minh City, Vietnam (GRID:grid.267849.6) (ISNI:0000 0001 2105 6888)
5 Representative Office of VAST in Ho Chi Minh City, Ho Chi Minh City, Vietnam (GRID:grid.267849.6)