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This package streamlines the process of building, managing, and
updating local 'SQLite' databases that contain geospatial
features extracted from ‘Google Earth Engine’ (‘GEE’).
For a full description of the methodology, implementation, and use cases, see the accompanying World Bank Policy Research Working Paper: Kurbucz, Marcell T.; Andrée, Bo Pieter Johannes. (2025). Building and Managing Local Databases from Google Earth Engine with the geeLite R Package. Policy Research Working Paper 11115, World Bank. http://hdl.handle.net/10986/43165. License: CC BY 3.0 IGO.
# install.packages("devtools")
devtools::install_github("mtkurbucz/geeLite")
geeLite::gee_install()library(geeLite)path <- "path/to/db"
set_config(path = path,
regions = c("SO", "YE"),
source = list(
"MODIS/061/MOD13A2" = list(
"NDVI" = c("mean", "sd")
)
),
resol = 3,
start = "2020-01-01")run_geelite(path = path)
#>
#> ────────────────────────────────────────────────────────────────────────────────
#> geeLite R Package
#> ────────────────────────────────────────────────────────────────────────────────
#>
#> ── rgee 1.1.7 ─────────────────────────────────────── earthengine-api 0.1.370 ──
#> ✔ User: not defined
#> ✔ Initializing Google Earth Engine: DONE!
#> ✔ Earth Engine account: user
#> ✔ Python path: C:/.../AppData/Local/r-miniconda/envs/rgee/python.exe
#> ────────────────────────────────────────────────────────────────────────────────
#>
#> ℹ Database built successfully.modify_config(path = path,
keys = list(
c("source", "MODIS/061/MOD13A2", "NDVI"),
c("source", "MODIS/061/MOD13A2", "EVI")
),
new_values = list(
c("mean", "min", "max"),
c("mean", "sd")
))run_geelite(path = path)
#>
#> ────────────────────────────────────────────────────────────────────────────────
#> geeLite R Package
#> ────────────────────────────────────────────────────────────────────────────────
#>
#> ── rgee 1.1.7 ─────────────────────────────────────── earthengine-api 0.1.370 ──
#> ✔ User: not defined
#> ✔ Initializing Google Earth Engine: DONE!
#> ✔ Earth Engine account: user
#> ✔ Python path: C:/.../AppData/Local/r-miniconda/envs/rgee/python.exe
#> ────────────────────────────────────────────────────────────────────────────────
#>
#> ℹ Database updated successfully.# Fetch SQLite database:
# 1) Convert data to daily format and apply default linear interpolation ('prep_fun').
# 2) Aggregate data to default monthly frequency ('freq') using mean and standard deviation aggregation ('aggr_funs').
db <- read_db(path = path, aggr_funs = list(
function(x) mean(x, na.rm = TRUE),
function(x) sd(x, na.rm = TRUE))
)To efficiently handle large data requests, 'geeLite'
provides a 'drive' mode. In this mode, data are exported
from ‘Google Earth Engine’ to ‘Google Drive’ in parallel batches and
then imported into your local ‘SQLite’ database. Ensure sufficient
available storage on your linked Google Drive account before using this
mode.
# Collect and store data using drive mode
run_geelite(path = path, mode = "drive")The geeLite package includes a command-line interface
(CLI) for advanced users and automation workflows. All major operations
can be performed directly from the terminal using
Rscript.
The following example demonstrates how to configure and manage a database using the CLI:
# Set the CLI files
Rscript /path/to/geeLite/cli/set_cli.R --path "path/to/db"
# Navigate to the directory where the database will be generated
cd "path/to/db"
# Create a configuration file
Rscript cli/set_config.R --regions "SO YE" --source "list('MODIS/061/MOD13A2' = list('NDVI' = c('mean', 'min')))" --resol 3 --start "2020-01-01"
# Run the data collection based on the configuration
Rscript cli/run_geelite.R
# Modifying the configuration file
Rscript cli/modify_config.R --keys "list(c('source', 'MODIS/061/MOD13A2', 'NDVI'), c('source', 'MODIS/061/MOD13A2', 'EVI'))" --new_values "list(c('mean', 'min', 'max'), c('mean', 'sd'))"
# Update the database with the modified configuration
Rscript cli/run_geelite.RIf you use geeLite in your research, please cite:
Kurbucz, Marcell T.; Andrée, Bo Pieter Johannes. (2025). Building and Managing Local Databases from Google Earth Engine with the geeLite R Package. Policy Research Working Paper 11115. © World Bank. http://hdl.handle.net/10986/43165. License: CC BY 3.0 IGO.
Additional documentation and usage examples are available at: https://github.com/mtkurbucz/geeLite/tree/main/docs
All geospatial datasets are retrieved from the Google Earth Engine public data catalog. Users must have a registered Google account with GEE access. No proprietary or restricted data are used in this package.
Funding by the World Bank’s Food Systems 2030 (FS2030) Multi-Donor Trust Fund program (TF0C0728 and TF0C7822) is gratefully acknowledged. We thank Andres Chamorro and Ben P. Stewart for code testing and comments, as well as Steve Penson, David Newhouse and Alia J. Aghjanian for helpful comments and input. This paper reflects the views of the authors and does not reflect the official views of the World Bank, its Executive Directors, or the countries they represent.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.