⚠️ Note: The MODIS package is currently not fully functional due to recent changes in authentication mechanisms at LP DAAC and LAADS (Earthdata Login and token-based access). While some core features may still work, automated downloading and processing are affected. Users working with MODIS data are encouraged to explore alternative packages listed below.

While the MODIS package provides an integrated workflow for discovering, downloading, mosaicking, and processing MODIS satellite data, users may also find value in the following actively maintained alternatives—especially for workflows requiring compatibility with newer versions of R:

• Focus: Efficient access to MODIS subsets via the ORNL DAAC web service (MODIS Subsets API).
• Highlights: Streamlined for point-based time series extraction (e.g., vegetation indices at specific locations). Ideal for ecological or site-based studies.
• Limitations: Does not support full-tile downloading or mosaicking of spatial rasters.

• Focus: GUI and command-line tool for pre-processing MODIS time series.
• Highlights: Provides a user-friendly interface (also scriptable) to automate downloading, reprojecting, mosaicking, and time series creation.
• Best for: Batch processing of MODIS raster products across time and space with minimal coding.

• Focus: General framework for working with remote sensing time series from multiple platforms.
• Highlights: MODIS is supported alongside Sentinel, Landsat, and others. Designed for harmonized, cross-sensor workflows.
• Best for: Projects integrating MODIS with other remote sensing data sources in a unified workflow.

• Focus: Educational resource demonstrating MODIS data download and pre-processing using base R and terra.
• Highlights: Teaches how to manually script MODIS data access and preparation. Good for learning fundamentals and customizing your own pipeline.

If you continue to rely on MODIS for legacy workflows or specific utilities, we recommend documenting your environment carefully and checking for ongoing support issues (e.g., via GitHub). For new projects, consider evaluating the packages above to ensure long-term maintainability.

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MODIS can be installed via

remotes::install_github("fdetsch/MODIS")

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• https://stevemosher.wordpress.com/modis-tutorial/
• https://cornelllabofornithology.github.io/ebird-best-practices/covariates.html#covariates-dl

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Please file bug reports and feature requests at https://github.com/fdetsch/MODIS/issues.