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

Can Trong Nguyen,Lian-Zhi Huo,Phan Kieu Diem,Amnat Chidthaisong

doi:10.3390/land10030231

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.

Highlights

Remote sensing and satellite imagery have been widely utilized for monitoring land and environmental changes, including urban expansion [1,2,3], deforestation [4,5,6], climate change impacts [7,8], wildfire damage [9,10], and other natural and anthropogenic dynamics
We developed the modified bare soil index (MBI)
We can see that bare soil index (BSI) emphasizes built-up covers instead of bare soil areas because buildings in index images are in a lighter tone compared to bare soil parcels (Figure 5a,c)

Summary

Introduction

Remote sensing and satellite imagery have been widely utilized for monitoring land and environmental changes, including urban expansion [1,2,3], deforestation [4,5,6], climate change impacts [7,8], wildfire damage [9,10], and other natural and anthropogenic dynamics. There are diverse high-resolution satellites which positively support urban studies, such as HyMap [11], Worldview [12], SPOT [13,14], and Sentinel-2 [15,16]. The major limitations of these observation data are data-acquired costs and time of coverage, especially for urban expansion studies, which are often considered over a long-term period. The cost per scene for commercial satellites is costly relative to the income of developing countries. The freely accessible data with fine resolution such as the Sentinel mission has only been available since 2015. Landsat data (i.e., 4, 5, 7-ETM, and 8-OLI) are commonly used in numerous studies worldwide since its data cover nearly 50 years consecutively [19]. With medium multispectral resolution and powerful thermal infrared (TIR) sensors, Landsat

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Conclusion