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A Modified Bare Soil Index to Identify Bare Land Features during Agricultural Fallow-Period in Southeast Asia Using Landsat 8

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  • Can Trong Nguyen

    (The Joint Graduate School of Energy and Environment, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand
    Center of Excellence on Energy Technology and Environment (CEE), PERDO, Ministry of Higher Education, Science, Research and Innovation, Bangkok 10140, Thailand)

  • Amnat Chidthaisong

    (The Joint Graduate School of Energy and Environment, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand
    Center of Excellence on Energy Technology and Environment (CEE), PERDO, Ministry of Higher Education, Science, Research and Innovation, Bangkok 10140, Thailand)

  • Phan Kieu Diem

    (College of Environment and Natural Resources, Can Tho University, Can Tho 94115, Vietnam)

  • Lian-Zhi Huo

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

Bare soil is a critical element in the urban landscape and plays an essential role in urban environments. Yet, the separation of bare soil and other land cover types using remote sensing techniques remains a significant challenge. There are several remote sensing-based spectral indices for barren detection, but their effectiveness varies depending on land cover patterns and climate conditions. Within this research, we introduced a modified bare soil index (MBI) using shortwave infrared (SWIR) and near-infrared (NIR) wavelengths derived from Landsat 8 (OLI—Operational Land Imager). The proposed bare soil index was tested in two different bare soil patterns in Thailand and Vietnam, where there are large areas of bare soil during the agricultural fallow period, obstructing the separation between bare soil and urban areas. Bare soil extracted from the MBI achieved higher overall accuracy of about 98% and a kappa coefficient over 0.96, compared to bare soil index (BSI), normalized different bare soil index (NDBaI), and dry bare soil index (DBSI). The results also revealed that MBI considerably contributes to the accuracy of land cover classification. We suggest using the MBI for bare soil detection in tropical climatic regions.

Suggested Citation

  • Can Trong Nguyen & Amnat Chidthaisong & Phan Kieu Diem & Lian-Zhi Huo, 2021. "A Modified Bare Soil Index to Identify Bare Land Features during Agricultural Fallow-Period in Southeast Asia Using Landsat 8," Land, MDPI, vol. 10(3), pages 1-18, February.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:3:p:231-:d:505545
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    References listed on IDEAS

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    1. Nguyen, Phuong Minh & Van Le, Khoa & Botula, Yves-Dady & Cornelis, Wim M., 2015. "Evaluation of soil water retention pedotransfer functions for Vietnamese Mekong Delta soils," Agricultural Water Management, Elsevier, vol. 158(C), pages 126-138.
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    3. Uday Pimple & Asamaporn Sitthi & Dario Simonetti & Sukan Pungkul & Kumron Leadprathom & Amnat Chidthaisong, 2017. "Topographic Correction of Landsat TM-5 and Landsat OLI-8 Imagery to Improve the Performance of Forest Classification in the Mountainous Terrain of Northeast Thailand," Sustainability, MDPI, vol. 9(2), pages 1-26, February.
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