l4h_era5land() gains support for ERA5-Land climate
variables ("t2m", "d2m", "pr",
"soil", "pet") at daily or
monthly.
l4h_surface_temp() gains a by argument
("day"/"month") to extract LST values at
daily or monthly resolution. When
by = "month", cloud-masked pixels are excluded before the
temporal reduction, so low-quality observations do not bias the monthly
summary. The "day" option remains the default, so existing
code is unaffected.
✔ add l4h_malaria(), this function extracts modeled
malaria metrics (incidence rate, incidence count, parasite rate,
mortality rate, mortality count) for Plasmodium falciparum and
Plasmodium vivax from the Malaria Atlas Project GeoServer via
WCS 2.0.1. Automatically selects the latest release available.
✔ add l4h_dengue() ,downloads dengue case counts
from the OpenDengue Project, a harmonized, open-access
repository of dengue surveillance data from national ministries of
health. The function supports national, spatial, and temporal extracts
filtered by WHO region and country for a specified date range.
✔ add l4h_chirps(), this function extracts
precipitation values (daily, monthly, and annual) from CHIRPS v3. The user can
choose between IMERG-based (product = "sat") or ERA5-based
(product = "rnl") daily products.
✔ add l4h_surface_temp(),extracts daytime or
nighttime Land Surface Temperature (LST) for a user-defined region and
time range using the MODIS MOD11A1.061 product
✔ add l4h_night_lights(), extracts global night‑time
lights using harmonized DMSP‑OLS and VIIRS data.
✔ add l4h_urban_rural_area(), calculates the surface
area (in km2) of urban, rural, or all settlement classes every 5 years
between 1985 and 2030 using the GHS-SMOD R2023A dataset.
✔ add l4h_human_built(), extracts built‑up surface
area from GHSL Built‑Up Surface dataset.
✔ add l4h_co_column(), extracts carbon monoxide (CO)
concentration from Sentinel-5P TROPOMI.
✔ add l4h_urban_heat_index(), calculates the Surface
Urban Heat Island (SUHI) index using MODIS LST and GHS-SMOD.
l4h_ee_extract() like an alternative to some
problems withee_extractl4h_water_proportion(). The MapBiomas Peru
water dataset does not yet have a stable API or consistent versioning
for reliable programmatic access.This initial release of land4health lays the foundation for the core functionality and defines the structure of the main functions, as outlined in issue #3.
l4h_forest_loss()l4h_rural_access_index()l4h_travel_time()l4h_water_proportion()l4h_sebal_modis()l4h_install()l4h_list_metrics()l4h_packages()Upgraded assets and databases using GHA
using pipelines with R #4
add lifecycle badges to all exported functions.
Introduced a new progress bar ( ████████ 100% ) for all functions to enhance the user experience. #6
Initial CRAN submission.