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Solar farm suitability mapping for the Contiguous United States using the fuzzy analytic hierarchy process and geospatial analysis

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  • Ilhan, Emine
  • Samadi, Forooza
  • Karimi, Hazhir

Abstract

Large-scale photovoltaic deployment requires a national assessment of suitable lands for utility-scale facilities. This study presents a Geographic Information System-based Fuzzy Analytic Hierarchy Process to map photovoltaic suitability across the Contiguous United States at 90-m resolution. Ten criteria, including climate, environmental limitations, topographic conditions, and accessibility-related factors, were normalized using fuzzy membership functions and combined with Fuzzy Analytical Hierarchy Process-weighted overlay. High–very high suitability totals 2.51 million km2 (32.1 %), concentrated in the U.S. Southwest. Low suitability occurs mainly in mountainous and densely populated regions. Compared with 5680 existing installations and 55,977 background points, presence scores are higher (mean/median 0.60/0.62 vs 0.50/0.57), and 81 % of facilities fall in high–very high classes (≥0.60). Installations are strongly clustered (nearest-neighbor ratio 0.346; z = −94.34; p < 0.01); Getis–Ord Gi∗ identifies persistent Southwest hot spots across percentile thresholds (top 10–20 %). Receiver Operator Characteristic analysis yields the Area Under the Curve of 0.59, reflecting screening-scale discrimination; unmodeled economic and regulatory factors remain important. Sensitivity ranks irradiance as the dominant driver, followed by slope and transmission proximity. These maps support strategic planning, transmission upgrades, and site screening.

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  • Ilhan, Emine & Samadi, Forooza & Karimi, Hazhir, 2026. "Solar farm suitability mapping for the Contiguous United States using the fuzzy analytic hierarchy process and geospatial analysis," Renewable Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:renene:v:260:y:2026:i:c:s0960148126000546
    DOI: 10.1016/j.renene.2026.125229
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