Effective large-scale monitoring is needed as photovoltaic (PV) systems expand across urban and rural areas. Remote sensing provides a practical approach for wide-area PV detection; however, variations in panel materials, climatic conditions, and background surfaces may affect detection performance. Spectral indices may be region-specific or require empirical calibration, restricting their applicability across different settings. This study introduces the Physics-Adaptive Reflectance Harmonization Index (PARHI), a spectral index for cross-regional PV localization using multispectral satellite imagery. PARHI distinguishes PV installations from surrounding surfaces using physically motivated spectral relationships and adaptive weighting of visible, near-infrared (NIR), and short-wave infrared (SWIR) responses. PV localization is performed by applying an empirically selected decision threshold to the PARHI response. Experimental evaluation across the examined locations demonstrated 96.42% accuracy, 95.87% precision, 94.96% recall, a 95.41% F1-score, and a 91.23% Intersection over Union (IoU). Threshold-sensitivity, ablation, seasonal, illumination, and cross-sensor assessments further evaluated performance under the investigated conditions. Thus, PARHI provides an interpretable, training-independent spectral approach for rapid PV localization across the evaluated environments and acquisition conditions. Further validation across broader climatic and geographic settings is required to establish wider generalizability.
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M et al. (2026) studied this question.
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