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Exploring the Potential of Soil Salinity Assessment through Remote Sensing and GIS: Case Study in the Coastal Rural Areas of Bangladesh

Author

Listed:
  • Billal Hossen

    (Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Japan
    Department of Agricultural Extension, Khamarbari, Farmgate, Dhaka 1215, Bangladesh)

  • Helmut Yabar

    (Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Japan)

  • Md Jamal Faruque

    (Bangladesh Agricultural Development Corporation (BADC), Dhaka 1000, Bangladesh)

Abstract

Soil salinity is a negative impact of climate change, and it is a significant problem for the coastal region of Bangladesh, which has been increasing in the last four decades. The issue of soil salinity substantially limits the agricultural crop production in coastal areas. Therefore, a soil salinity assessment is essential for proper land-use planning in agricultural crop production. This research was carried out to determine the soil salinity area with different salinity levels in Barguna Sadar Upazila (sub-district). The remote sensing technique, which is a potentially quick yet effective method for the soil salinity estimation in data-scarce conditions, was applied. The methodology employed the Landsat 8 OLI dataset along with nine soil salinity indices to develop a soil salinity map. The maps were from Soil Resource Development Institute (SRDI), and low NDVI value (−0.01 to 0.48) was produced using satellite images illustrate the extent of the soil salinity for the study area. However, nine linear regressions, which were made between the pixel value of the satellite-based generated map and ground truth soil salinity data, that is, the EC value, indicate a maximum R 2 value for the salinity index SI 7 = G × R/B, representing a value of 0.022. This minimal R 2 value indicates a negligible relationship between the ground EC value and the pixel value of the salinity index generated map, inferring that the indices are not sufficient to assess the soil salinity. Nonetheless, this research’s findings offer a guide for researchers to investigate alternative geospatial approaches for this geophysical condition.

Suggested Citation

  • Billal Hossen & Helmut Yabar & Md Jamal Faruque, 2022. "Exploring the Potential of Soil Salinity Assessment through Remote Sensing and GIS: Case Study in the Coastal Rural Areas of Bangladesh," Land, MDPI, vol. 11(10), pages 1-18, October.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:10:p:1784-:d:941317
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    References listed on IDEAS

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    1. Amireeta Rawlani & Benjamin Sovacool, 2011. "Building responsiveness to climate change through community based adaptation in Bangladesh," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 16(8), pages 845-863, December.
    2. Khan, Nasir M. & Rastoskuev, Victor V. & Sato, Y. & Shiozawa, S., 2005. "Assessment of hydrosaline land degradation by using a simple approach of remote sensing indicators," Agricultural Water Management, Elsevier, vol. 77(1-3), pages 96-109, August.
    3. Dasgupta, Susmita & Hossain, Md. Moqbul & Huq, Mainul & Wheeler, David, 2014. "Climate change, soil salinity, and the economics of high-yield rice production in coastal Bangladesh," Policy Research Working Paper Series 7140, The World Bank.
    4. Dasgupta, Susmita & Kamal, Farhana Akhter & Khan, Zahirul Huque & Choudhury, Sharifuzzaman & Nishat, Ainun, 2014. "River salinity and climate change : evidence from coastal Bangladesh," Policy Research Working Paper Series 6817, The World Bank.
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