ANALYSING URBAN SPRAWL OF THE MUMBAI METROPOLITAN REGION USING REMOTE SENSING AND SOCIOECONOMIC DATA

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2. Bias corrections in reanalyzed daily maximum and minimum temperatures for the metropolitan environments in Western India S. Iyer et al. https://doi.org/10.1007/s00382-026-08104-4
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