Reply to “Comment on ‘Soil salinity assessment by using near-infrared channel and Vegetation Soil Salinity Index derived from Landsat 8 OLI data: a case study in the Tra Vinh Province, Mekong Delta, Vietnam’ by Kim-Anh Nguyen, Yuei-An Liou, Ha-Phuong Tran, Phi-Phung Hoang and Thanh-Hung Nguyen”

Kim Anh Nguyen, Yuei An Liou, Ha Phuong Tran, Phi Phung Hoang, Thanh Hung Nguyen

Research output: Contribution to journalLetterpeer-review

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. [Figure not available: see fulltext.]

Original languageEnglish
Article number46
JournalProgress in Earth and Planetary Science
Volume9
Issue number1
DOIs
StatePublished - Dec 2022

Keywords

  • Climate change
  • Landsat 8
  • Mekong Delta
  • Soil salinity
  • Tra Vinh Province

Fingerprint

Dive into the research topics of 'Reply to “Comment on ‘Soil salinity assessment by using near-infrared channel and Vegetation Soil Salinity Index derived from Landsat 8 OLI data: a case study in the Tra Vinh Province, Mekong Delta, Vietnam’ by Kim-Anh Nguyen, Yuei-An Liou, Ha-Phuong Tran, Phi-Phung Hoang and Thanh-Hung Nguyen”'. Together they form a unique fingerprint.

Cite this