Open Access

ARTICLE

Retrieval of Surface Soil Moisture Using Landsat 8 TIRS Data: A Case Study of Faisalabad

Uzair Abbas¹, Zahid Maqbool¹, Muhammad Adnan Shahid^1,2,*, Muhammad Safdar^1,2, Saif Ullah Khan^1,3

1 National Centre of GIS and Space Applications (NCGSA)-Agricultural Remote Sensing Lab (ARSL), University of Agriculture Faisalabad, Faisalabad, 38000, Punjab, Pakistan
2 Department of Irrigation and Drainage, University of Agriculture Faisalabad, Faisalabad, 38000, Punjab, Pakistan
3 Multan Development Authority, HUD & PHED, Multan, 54000, Punjab, Pakistan

* Corresponding Author: Muhammad Adnan Shahid. Email:

(This article belongs to the Special Issue: Applications of GNSS Remote Sensing)

Revue Internationale de Géomatique 2025, 34, 655-668. https://doi.org/10.32604/rig.2025.064279

Received 11 February 2025; Accepted 10 July 2025; Issue published 11 August 2025

Abstract

This study was conducted to devise an integrated methodology for retrieval of surface soil moisture (SSM) using Landsat 8 TIRS data. For this purpose, Landsat 8 images of 15 May 2021 (pre-monsoon) and 20 November 2021 (post-monsoon) were processed for retrieval of soil moisture index (SMI) based on land surface temperature (LST). Moreover, field-based SM in the laboratory was also determined and correlated with satellite-based SMI. A moderate correlation between field-based SM and satellite-based SMI with R² = 0.60 was obtained. Based on this relationship, SSM maps of Tehsil Faisalabad Saddar for the pre-and post-monsoon seasons of 2021 were developed. Significant variations in the spatial distribution of SSM of Tehsil Faisalabad Saddar (total area of 1492.45 km²) for pre- and post-monsoon seasons were observed. In the pre-monsoon season, 68.1% of the area of Faisalabad Saddar showed SSM contents ranging from 10.37% to 15.40%. Only 8.7% of the total area of Faisalabad Saddar exhibited SSM in the range of 15.41%–22.82% in the pre-monsoon season. It was astonishing to notice that no area in Faisalabad Saddar was detected with SSM above 22.82% in the pre-monsoon season. However, in the post-monsoon season, only 0.11% of the total study area exhibited SSM in the range of 0.0% to 26.97%. The maximum area (52.29% of the total area) in post-monsoon season exhibited SSM ranging from 36.18% to 40.02%, followed by 32.02%–36.17% (34.3% of the total area). The study concluded that satellite-based retrieval of surface soil moisture realistically monitored the variations in soil moisture due to the onset of the monsoon season. The novel methodology developed in this study could be helpful for policy making regarding groundwater recharge and its sustainable use in an area, as well as for estimating surface soil moisture to provide irrigation scheduling and crop management guidelines.

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