Calculates the Surface Urban Heat Island (SUHI) index using MODIS LST and GHS-SMOD

Computes the SUHI (Surface Urban Heat Island) index as the difference between the mean land surface temperature (LST) in urban and rural areas for each date in a user-defined region and time range.

Usage

l4h_urban_heat_index(
  from,
  to,
  region,
  band = "day",
  level = "strict",
  stat = "max",
  scale = 1000,
  sf = TRUE,
  quiet = FALSE,
  force = FALSE,
  ...
)

Arguments

from: Character or Date. Start date (format: "YYYY-MM-DD").
to: Character or Date. End date (format: "YYYY-MM-DD").
region: Spatial object (sf, sfc, or SpatVector) defining the region.
band: Character. "day" or "night" LST from MODIS. Default is "day".
level: Character. "strict" or "moderate" quality filter for MODIS. Default is "strict".
stat: Character. Aggregation statistic, e.g. "mean" or "median". Default is "mean".
scale: Numeric. Resolution in meters. Default is 1000.
sf: Logical. If TRUE, returns an sf; if FALSE, returns a tibble. Default is TRUE.
quiet: Logical. If TRUE, suppress messages. Default is FALSE.
force: Logical. If TRUE, skip representativity check. Default is FALSE.
...: Extra arguments passed to ee_extract().

Value

A tibble or sf object with columns: date, variable = "SUHI", and value (°C).

Credits

Pioneering geospatial health analytics and open‐science tools. Developed by the Innovalab Team, for more information send a email to imt.innovlab@oficinas-upch.pe

Examples

if (FALSE) { # \dontrun{
library(land4health)
ee_Initialize()

# Define a bounding box region (Ucayali, Peru)
region <- st_as_sf(st_sfc(
  st_polygon(list(matrix(c(
    -74.1, -4.4,
    -74.1, -3.7,
    -73.2, -3.7,
    -73.2, -4.4,
    -74.1, -4.4
  ), ncol = 2, byrow = TRUE))),
  crs = 4326
))

# Calculate SUHI using daytime LST (mean temperature difference)
suhi_day <- l4h_urban_heat_index(
  from = "2020-01-01",
  to = "2020-12-31",
  region = region,
  band = "day",
  stat = "mean"
)
head(suhi_day)

# Calculate SUHI using nighttime LST (max difference)
suhi_night <- l4h_urban_heat_index(
  from = "2020-01-01",
  to = "2020-12-31",
  region = region,
  band = "night",
  stat = "max"
)
head(suhi_night)
} # }