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<p>This study assesses land suitability for apple horticulture in the Kashmir Valley, India, through an integrated application of the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). Aimed at promoting sustainable horticultural planning, the approach combines expert-driven weighting of key agro-climatic and biophysical criteria with spatial analysis. Seven factors, land use/land cover, elevation, slope, aspect, temperature, rainfall, and soil texture, were prioritized using AHP and integrated in a GIS environment through Weighted Overlay Analysis to generate a suitability map categorized into four classes: Highly Suitable, Suitable, Least Suitable, and Not Suitable. Validation was conducted through ground truthing, involving on-screen digitisation of high-resolution satellite imagery and field-verified orchard locations, showing strong concordance with geospatial model outputs. The results indicate that 49% of the valley falls within the Highly Suitable or Suitable classes, though large areas remain underutilised. The study highlights the utility of AHP-GIS integration in producing transparent, spatially explicit outputs to inform land-use decision-making. It contributes to spatial information science by demonstrating a scalable and replicable framework that supports data-driven horticultural planning, resource optimisation, and climate-resilient development.</p>

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Field-validated apple orchard land suitability mapping in Kashmir Valley using AHP-GIS and high-resolution satellite data

  • 期刊论文

  • 发表日期：

    2025年11月1日

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  • Munazah Maheen,
  • Shakil Ahmad Romshoo

摘要

This study assesses land suitability for apple horticulture in the Kashmir Valley, India, through an integrated application of the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). Aimed at promoting sustainable horticultural planning, the approach combines expert-driven weighting of key agro-climatic and biophysical criteria with spatial analysis. Seven factors, land use/land cover, elevation, slope, aspect, temperature, rainfall, and soil texture, were prioritized using AHP and integrated in a GIS environment through Weighted Overlay Analysis to generate a suitability map categorized into four classes: Highly Suitable, Suitable, Least Suitable, and Not Suitable. Validation was conducted through ground truthing, involving on-screen digitisation of high-resolution satellite imagery and field-verified orchard locations, showing strong concordance with geospatial model outputs. The results indicate that 49% of the valley falls within the Highly Suitable or Suitable classes, though large areas remain underutilised. The study highlights the utility of AHP-GIS integration in producing transparent, spatially explicit outputs to inform land-use decision-making. It contributes to spatial information science by demonstrating a scalable and replicable framework that supports data-driven horticultural planning, resource optimisation, and climate-resilient development.