Vegetation Mitigation of Surface Urban Heat Islands in Three South American Cities: A Multi-Method Analysis

This study quantifies long-term surface urban heat island (SUHI) dynamics (2001–2016) in three climatically diverse South American metropolises—Buenos Aires (temperate), Bogotá (tropical highland), and Lima (arid coastal)—using MODIS data (0.05° resolution), comparing Streutker’s Gaussian model with a quantile-based approach (SUHI = 95th urban LST percentile—rural LST median). Method performance varied with surface heterogeneity: Gaussian modeling underestimated SUHI in coastal cities (nocturnal bias = +1.5 °C in Buenos Aires; R2 ≤ 0.17 in Lima) due to non-Gaussian LST distributions driven by oceanic moisture advection, while quantile-based estimation proved robust in complex terrains (Bogotá agreement: day R2 = 0.67, night R2 = 0.53). Distinct SUHI signatures emerged: Buenos Aires exhibited stronger nocturnal SUHI (max 3.79 °C, linked to reduced rural evaporative cooling), Lima showed winter daytime Urban Cool Islands (−1.5 °C) from higher heat absorption in semi-desert surroundings, and Bogotá peaked in October (7.27 °C daytime SUHI) with altitudinal suppression of convective rainfall. Vegetation strongly modulated surface fluxes, with urban NDVI/EVI correlations (R2 ≤ 0.29) confirming evaporative regulation’s role in halving thermal amplitudes (10 °C urban vs. 5 °C rural), while rural coupling varied with moisture availability (R2 ≤ 0.65). Coastal proximity and elevation were key divergence drivers, disrupting surface energy partitioning. We recommend quantile methods for moisture-heterogeneous regions and advocate hydrometeorologically informed mitigation: optimizing green infrastructure for latent heat flux (Buenos Aires), leveraging nocturnal drainage flows (Bogotá), and integrating natural cool-island dynamics into water-sensitive design (Lima).