Fig 1.
A map of the study area, Miami-Dade County, in Southeast Florida, USA and its Köppen-Geiger Climate Zones [63].
The county’s urban development boundary separates developed, urban Miami-Dade from the rural, Everglades wetlands to the west. USA shapefile: U.S. Census Bureau [64]. Miami-Dade County boundary shapefile, Urban development boundary shapefile: Miami-Dade County [65]. Climate zone map: GloH2O [66].
Fig 2.
Monthly SAT (°C), surface solar irradiance (W/m2), and rainfall (mm) for Miami-Dade County.
Box and whiskers display the 1st, 25th, 75th, and 99th percentiles of each variable for each month. The box line represents the median. (a) Plotted values represent hourly SAT observations averaged by month for seven weather stations (6 WeatherSTEM [70] and Miami International Airport) during 2015–2022 (n = 56 values per month). (b) Plotted values represent hourly solar irradiance observations (daytime, 7 am to 7 PM ET/EST) averaged by month for six WeatherSTEM stations during 2015–2022 (n = 48 values per month). (c) Plotted values represent monthly model estimates from PRISM [71, 72] of local rainfall totals within a 4-km grid centered at Miami International Airport (KMIA) for each month during 2000–2020 (n = 21 values per month).
Fig 3.
Seven weather stations utilized for SAT observations.
Miami-Dade County shapefile: Miami-Dade County [65]. Basemap: ESRI [78, 79].
Fig 4.
A flowchart of the study’s three primary steps: (1) develop LST climatology, (2) spatially analyze the LST record, and (3) examine the relationship between LST and SAT.
Table 1.
Landsat 8 metadata.
Fig 5.
Urban and rural Miami-Dade County census block groups (CBGs).
Urban CBGs (left) have greater than or equal to 5% mean imperviousness, while rural CBGs (right) have less than 5% mean imperviousness. Census block group shapefiles: U.S. Census Bureau [64]. Basemaps: ESRI [78, 79].
Fig 6.
Monthly LST (red) for Miami-Dade County and SAT (black) at KMIA.
For each monthly boxplot, LST pixels were averaged by month (2013–2022). Box and whiskers display the 1st, 25th, 75th, and 99th percentiles of monthly mean LST pixels, and the box line represents the median value. Each black dot represents monthly mean SAT at KMIA (2013–2022).
Fig 7.
Monthly LST for each weather station census block group (box plots) and SAT (diamonds) at weather stations (Fig 3).
For each monthly boxplot, LST pixels in each census block group in which there is a weather station were averaged across all monthly images (2013–2022). Box and whiskers display the 1st, 25th, 75th, and 99th percentiles of monthly mean LST pixels for each weather station census block group, and the box line represents the median value. Colored diamond shapes represent the average monthly SAT observed for the WeatherSTEM station within the respective census block group.
Fig 8.
Mean LST (°C) and NDVI for Miami-Dade County (2013–2022).
(a) Each 30-by-30m pixel represents the mean LST value for all imagery (98 images) across the study period. The Miami-Dade SUHI is represented by yellow-to-red colors along the eastern portion of the county, as compared to more natural, preserved landscape where greener colors are observed. (b) Each 30-by-30m pixel represents the mean NDVI value for all imagery across the study period. Imagery data: USGS [75].
Fig 9.
Seasonal LST for the rural (green) and urban (red) region of Miami-Dade County (2013–2022).
For each boxplot, LST pixels were averaged by season within rural and urban regions of the county. Box and whiskers display the 1st, 25th, 75th, and 99th percentiles of seasonal rural and urban LST pixels. The box line represents the median.
Fig 10.
Miami-Dade County mean LST per census block group (n = 1748) by mean biophysical variable percentile.
For each box plot, annual mean LST pixels (2013–2022) were aggregated to the mean census block group value and binned (n ≈ 175 census block groups) by mean census block group percent impervious surface, NDVI, and percent tree canopy percentiles. Box and whiskers display the 1st, 25th, 75th, and 99th percentiles across annual mean census block group LST. The box line represents the median value.
Fig 11.
Monthly mean LST by monthly tenth (red, low greenness) and monthly ninetieth (green, high greenness) NDVI percentiles.
LST and NDVI pixels were aggregated to their mean values within census block groups (n = 1748) for each month (2013–2022). Data points represent the monthly mean LST values of Miami-Dade County census block groups at the monthly tenth NDVI percentile (red) and the monthly ninetieth NDVI percentile (green).
Table 2.
LST vs biophysical variables in Miami-Dade County.
The relationships between mean census block group (CBG) LST and mean CBG NDVI (including by season), mean CBG percent tree canopy, and mean CBG percent impervious surface are given for 1748 CBGs across the county. The coefficient can be interpreted as degree Celsius change per unit increase for a variable coefficient (e.g., a unit increase in mean impervious surface indicates a mean ~0.05 degree increase in LST).
Fig 12.
Daily mean LST (within a 100-meter buffer) versus daily weather station SAT (°C) (2013–2022).
LST imagery was captured at 11 AM ET/12 PM EST and was compared to 11 AM/12 PM EST SAT observations collected across seven weather stations (Fig 3) within Miami-Dade County [70, 77]. Each dot represents a single day and location.