Building and managing local databases from Google Earth Engine with the geeLite R package

Google Earth Engine (GEE) has substantially expanded the scope of geospatial analysis by providing access to petabyte-scale satellite imagery and geospatial data together with cloud-based computation. This accessibility enables researchers to study large-scale environmental and socio-economic processes with high spatial and temporal coverage. In recent years, numerous R packages have emerged to leverage GEE’s functionalities. However, constructing and managing complex spatio-temporal databases for continuous monitoring of remotely sensed data remains challenging and often requires advanced coding skills. To bridge this gap, we introduce the geeLite R package (available on CRAN), which supports the construction and updating of local databases for GEE-derived outputs, enabling users to track their evolution over time. By storing results in SQLite format — a serverless, self-contained database solution requiring no additional setup — geeLite simplifies data collection. It also streamlines conversion to native R formats and provides functions to aggregate and process the resulting databases for downstream analysis. • Google Earth Engine provides vast satellite imagery and processing power. • The geeLite R package connects Google Earth Engine to local spatial data workflows. • Users can create and manage databases for real-time spatial tracking. • Data are stored in SQLite format for portability and offline accessibility. • The package streamlines aggregation and analysis of time series data.

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Publication Details

Journal
Environmental Modelling & Software
Published
2026-02-23
DOI
https://doi.org/10.1016/j.envsoft.2026.106909
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Building and managing local databases from Google Earth Engine with the geeLite R package

Environmental Modelling & Software
Geographic Information Systems Studies
article

Building and managing local databases from Google Earth Engine with the geeLite R package

article en

Abstract

Google Earth Engine (GEE) has substantially expanded the scope of geospatial analysis by providing access to petabyte-scale satellite imagery and geospatial data together with cloud-based computation. This accessibility enables researchers to study large-scale environmental and socio-economic processes with high spatial and temporal coverage. In recent years, numerous R packages have emerged to leverage GEE’s functionalities. However, constructing and managing complex spatio-temporal databases for continuous monitoring of remotely sensed data remains challenging and often requires advanced coding skills. To bridge this gap, we introduce the geeLite R package (available on CRAN), which supports the construction and updating of local databases for GEE-derived outputs, enabling users to track their evolution over time. By storing results in SQLite format — a serverless, self-contained database solution requiring no additional setup — geeLite simplifies data collection. It also streamlines conversion to native R formats and provides functions to aggregate and process the resulting databases for downstream analysis. • Google Earth Engine provides vast satellite imagery and processing power. • The geeLite R package connects Google Earth Engine to local spatial data workflows. • Users can create and manage databases for real-time spatial tracking. • Data are stored in SQLite format for portability and offline accessibility. • The package streamlines aggregation and analysis of time series data.

Environmental Modelling & SoftwareVol. 199
Institute of the Americas (US), University College London (GB), World Bank Group (US)
Openalex Percentile: Top 46%
Geographic Information Systems Studies
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