Dryland soil quality modelling in Najran, Saudi Arabia, using a GIS-based geometric approach
File(s)
Published version
Author(s)
ALQURASHI, MESHAL
Lawrence, James
Mason, Philippa
Ghail, Richard
Type
Journal Article
Abstract
Introduction: Ensuring that natural resources are managed sustainably to achieve global food security is vital given changing climates and increasing demand for food due to population growth. In seeking to secure food security, assessing and safeguarding soil quality is an essential factor in ensuring that increasing demands for food can be met.
Methods: This study uses the Soil Quality Index (SQI) in Najran, Saudi Arabia to conduct spatial modelling of the geomorphological, physical, chemical, and fertility parameters of soil, using a Geometric Mean Algorithm (GMA) approach. A Digital Elevation Model (DEM) was used with Sentinel-2 satellite images and processed to generate digital soil and landform maps.
Results and discussion: The GMA results for Najran show a SQI range from 0.33 to 0.59, corresponding to “very low” to “very high” soil quality grades. Five categories of soil quality (SQ) – very low, low, moderate, high, and very high – were developed using the GMA model, and these cover 2.98, 45.69, 40.68, 8.98, and 1.65% of the land area, respectively. The small wadis in the area are nutrient-rich due to fluvial sediment deposition from the surrounding mountainous areas, and correlate to the higher SQ values. To validate the GMA model, a weighted additive (WA) model has been used; the coefficient of determination, R2, is 0.942. The proposed model achieves a high sensitivity index of 1.78, showing that the model performs well in assessing SQ in the selected area, and is therefore an effective tool for monitoring SQ.
Conclusion: This tool can support agricultural planning strategies in the Najran region and can also be used as an analogue for other dryland arid regions where there is a dearth of thorough soil research determining SQ. In addition, this integration improves the reliability of land suitability assessments and supports sustainable agricultural development.
Methods: This study uses the Soil Quality Index (SQI) in Najran, Saudi Arabia to conduct spatial modelling of the geomorphological, physical, chemical, and fertility parameters of soil, using a Geometric Mean Algorithm (GMA) approach. A Digital Elevation Model (DEM) was used with Sentinel-2 satellite images and processed to generate digital soil and landform maps.
Results and discussion: The GMA results for Najran show a SQI range from 0.33 to 0.59, corresponding to “very low” to “very high” soil quality grades. Five categories of soil quality (SQ) – very low, low, moderate, high, and very high – were developed using the GMA model, and these cover 2.98, 45.69, 40.68, 8.98, and 1.65% of the land area, respectively. The small wadis in the area are nutrient-rich due to fluvial sediment deposition from the surrounding mountainous areas, and correlate to the higher SQ values. To validate the GMA model, a weighted additive (WA) model has been used; the coefficient of determination, R2, is 0.942. The proposed model achieves a high sensitivity index of 1.78, showing that the model performs well in assessing SQ in the selected area, and is therefore an effective tool for monitoring SQ.
Conclusion: This tool can support agricultural planning strategies in the Najran region and can also be used as an analogue for other dryland arid regions where there is a dearth of thorough soil research determining SQ. In addition, this integration improves the reliability of land suitability assessments and supports sustainable agricultural development.
Date Issued
2026-06-10
Date Acceptance
2026-05-15
Citation
Frontiers in Sustainable Food Systems, 2026, 10
ISSN
2571-581X
Publisher
Frontiers Media S.A.
Journal / Book Title
Frontiers in Sustainable Food Systems
Volume
10
Copyright Statement
© 2026 Alqurashi, Lawrence, Mason and Ghail. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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Publication Status
Published
Article Number
1847272
Date Publish Online
2026-06-10