joss-paper/paper.md
In ptaconet/opendapr: Fast and Efficient Access to MODIS Earth Observation Data
title: 'modisfast: An R package for fast and efficient access to MODIS, VIIRS and GPM Earth Observation data'
tags:
- R
- MODIS
- VIIRS
- GPM
- Earth observation
- Datacubes
- Remote sensing
- OPeNDAP
authors:
- name: Paul Taconet
corresponding: true
orcid: "0000-0001-7429-7204"
affiliation: 1
- name: Nicolas Moiroux
orcid: "0000-0001-6755-6167"
affiliation: 1
affiliations:
- name: MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France
index: 1
date: 24 October 2024
bibliography: paper.bib
Summary
modisfast is an R package designed for easy and fast downloads of various Earth Observation (EO) data, including the Moderate Resolution Imaging Spectroradiometer (MODIS) Land products, the Visible Infrared Imaging Radiometer Suite (VIIRS) Land products, and the Global Precipitation Measurement mission (GPM) products. It enables users to subset the data directly at the download phase using spatial, temporal, and dimensional filters and supports parallelized downloads. It also streamlines the process of importing the downloaded data into R. Overall, modisfast offers R users a cost-effective, time-efficient, and energy-saving approach to accessing a set of key EO datasets with R.
Statement of need
EO satellite data are invaluable for monitoring and understanding our planet, with NASA's datasets like MODIS [@JUSTICE20023], VIIRS [@ROMAN2024113963], and GPM [@SkofronickJackson2017] among the most important. These collections have provided crucial data for over 20 years, supporting research in areas such as climate change, disaster response, biodiversity, public health, and more [@modis-applications].
However, despite the increasing availability of EO data, accessing and utilizing them remains challenging [@AGNOLI2023122357]. The large file sizes and complex multidimensional layers make it difficult to access and handle long time series, especially in regions with limited internet infrastructure. This complexity often leads to underutilization of data, fragmented workflows, and reliance on proprietary, energy-intensive tools like Google Earth Engine, which can hinder transparent and reproducible Open Science.
To address these challenges, we developed modisfast, an R [@R] package designed to simplify and speed-up the download and import of MODIS, VIIRS, and GPM time series for R users. Built on the OPeNDAP protocol [@opendap1; @opendap2; @opendap3], modisfast enhances the existing R ecosystem of tools for accessing MODIS data by introducing new features and supporting additional data sources. It allows users to apply spatial, temporal, and band/layer filters during the download phase, optimizing data retrieval and processing while promoting open-source international standards for data access.
Target audience
modisfast is suitable to any R user looking to use MODIS, VIIRS or GPM Earth Observation data, either for research, education, or operational purposes.
modisfast is particularly suited for :
- Retrieving MODIS, VIIRS or GPM data over long time series and large areas,
- Embedding data extraction within complex R workflows,
- Users in regions with limited internet access,
- Promoting international data access standards and Open Science in general,
- Users who are concerned about digital sobriety.
Main features
Data collections available with modisfast
Currently modisfast supports download of 77 data collections, extracted from MODIS land products, VIIRS land products, and Global Precipitation Measurement.
This list may change over time. The function mf_list_collections() enables to get the latest list of available data collections.
Typical workflow with modisfast
The typical workflow to access and import MODIS, VIIRS or GPM data in R with modisfast is presented in \autoref{fig:wf_modisfast}, along with a toy example.
{width="100%"}
Vignettes and examples
modisfast provides three vignettes and examples to learn more about the package :
- a Get started vignette describing the core features of the package;
- a Get data on several regions or periods of interest simultaneously vignette detailing advanced functionalities of
modisfast (for multi-time frame or multi-regions data access);
- a Full use case vignette showcasing an example of use of the package in a scientific context (geo-epidemiology).
Alternatives
Besides modisfast, there are several open-source R packages available for accessing MODIS or VIIRS Land products. Table 1 summarizes the main features of these packages. A thorough comparison of modisfast with these R packages (including data access time) can be found in the package documentation.
| | modisfast | appeears | MODIS | MODIStsp | MODIStools | rgee |
|-----------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
| EO Data collections accessible | MODIS, VIIRS, GPM | MODIS, VIIRS, and many others | MODIS | MODIS | MODIS, VIIRS | MODIS, VIIRS, GPM, and many others |
| Last updated | August 2024 | March 2024 | January 2023 | July 2024 | December 2022 | August 2024 |
| License | GPL-3.0 | AGPL-3 | NA | GPL-3.0 | AGPL-3 | Apache License v.2.0 |
| Available on CRAN ? | yes | yes | no | no | yes | yes |
| Utilizes open standards for data access protocols | yes | yes | no | NA | no | no |
| Enables spatial subsetting at the download phase | yes | yes | no | no | yes | yes |
| Enables dimensional subsetting at the download phase | yes | yes | no | yes | yes | yes |
| Maximum area size allowed for download | unlimited | unlimited | NA | unlimited | 200 km x 200 km | unlimited |
| Website | GitHub | GitHub | GitHub | GitHub | GitHub | GitHub |
| Reference | @modisfast | @appeears | NA | @MODIStsp | @modistools | @rgee |
Table 1: Comparison of modisfast with other alternatives.
Acknowledgements
We thank NASA and its partners for making all their Earth science data freely available, and financing and implementing open data access protocols such as OPeNDAP. We also thank the non-profit OPeNDAP, Inc. for developing and maintaining the eponym tool, and the developers of the R packages modisfast depends on.
This work has been developed over the course of several research projects (REACT 1, REACT 2, ANORHYTHM and DIV-YOO) funded by Expertise France and the French National Research Agency (ANR).
References
ptaconet/opendapr documentation built on Nov. 20, 2024, 10:04 p.m.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
title: 'modisfast: An R package for fast and efficient access to MODIS, VIIRS and GPM Earth Observation data' tags: - R - MODIS - VIIRS - GPM - Earth observation - Datacubes - Remote sensing - OPeNDAP authors: - name: Paul Taconet corresponding: true orcid: "0000-0001-7429-7204" affiliation: 1 - name: Nicolas Moiroux orcid: "0000-0001-6755-6167" affiliation: 1 affiliations: - name: MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France index: 1 date: 24 October 2024 bibliography: paper.bib
Summary
modisfast is an R package designed for easy and fast downloads of various Earth Observation (EO) data, including the Moderate Resolution Imaging Spectroradiometer (MODIS) Land products, the Visible Infrared Imaging Radiometer Suite (VIIRS) Land products, and the Global Precipitation Measurement mission (GPM) products. It enables users to subset the data directly at the download phase using spatial, temporal, and dimensional filters and supports parallelized downloads. It also streamlines the process of importing the downloaded data into R. Overall, modisfast offers R users a cost-effective, time-efficient, and energy-saving approach to accessing a set of key EO datasets with R.
Statement of need
EO satellite data are invaluable for monitoring and understanding our planet, with NASA's datasets like MODIS [@JUSTICE20023], VIIRS [@ROMAN2024113963], and GPM [@SkofronickJackson2017] among the most important. These collections have provided crucial data for over 20 years, supporting research in areas such as climate change, disaster response, biodiversity, public health, and more [@modis-applications].
However, despite the increasing availability of EO data, accessing and utilizing them remains challenging [@AGNOLI2023122357]. The large file sizes and complex multidimensional layers make it difficult to access and handle long time series, especially in regions with limited internet infrastructure. This complexity often leads to underutilization of data, fragmented workflows, and reliance on proprietary, energy-intensive tools like Google Earth Engine, which can hinder transparent and reproducible Open Science.
To address these challenges, we developed modisfast, an R [@R] package designed to simplify and speed-up the download and import of MODIS, VIIRS, and GPM time series for R users. Built on the OPeNDAP protocol [@opendap1; @opendap2; @opendap3], modisfast enhances the existing R ecosystem of tools for accessing MODIS data by introducing new features and supporting additional data sources. It allows users to apply spatial, temporal, and band/layer filters during the download phase, optimizing data retrieval and processing while promoting open-source international standards for data access.
Target audience
modisfast is suitable to any R user looking to use MODIS, VIIRS or GPM Earth Observation data, either for research, education, or operational purposes.
modisfast is particularly suited for :
- Retrieving MODIS, VIIRS or GPM data over long time series and large areas,
- Embedding data extraction within complex R workflows,
- Users in regions with limited internet access,
- Promoting international data access standards and Open Science in general,
- Users who are concerned about digital sobriety.
Main features
Data collections available with modisfast
Currently modisfast supports download of 77 data collections, extracted from MODIS land products, VIIRS land products, and Global Precipitation Measurement.
This list may change over time. The function mf_list_collections() enables to get the latest list of available data collections.
Typical workflow with modisfast
The typical workflow to access and import MODIS, VIIRS or GPM data in R with modisfast is presented in \autoref{fig:wf_modisfast}, along with a toy example.
{width="100%"}
Vignettes and examples
modisfast provides three vignettes and examples to learn more about the package :
- a Get started vignette describing the core features of the package;
- a Get data on several regions or periods of interest simultaneously vignette detailing advanced functionalities of
modisfast(for multi-time frame or multi-regions data access); - a Full use case vignette showcasing an example of use of the package in a scientific context (geo-epidemiology).
Alternatives
Besides modisfast, there are several open-source R packages available for accessing MODIS or VIIRS Land products. Table 1 summarizes the main features of these packages. A thorough comparison of modisfast with these R packages (including data access time) can be found in the package documentation.
| | modisfast | appeears | MODIS | MODIStsp | MODIStools | rgee |
|-----------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
| EO Data collections accessible | MODIS, VIIRS, GPM | MODIS, VIIRS, and many others | MODIS | MODIS | MODIS, VIIRS | MODIS, VIIRS, GPM, and many others |
| Last updated | August 2024 | March 2024 | January 2023 | July 2024 | December 2022 | August 2024 |
| License | GPL-3.0 | AGPL-3 | NA | GPL-3.0 | AGPL-3 | Apache License v.2.0 |
| Available on CRAN ? | yes | yes | no | no | yes | yes |
| Utilizes open standards for data access protocols | yes | yes | no | NA | no | no |
| Enables spatial subsetting at the download phase | yes | yes | no | no | yes | yes |
| Enables dimensional subsetting at the download phase | yes | yes | no | yes | yes | yes |
| Maximum area size allowed for download | unlimited | unlimited | NA | unlimited | 200 km x 200 km | unlimited |
| Website | GitHub | GitHub | GitHub | GitHub | GitHub | GitHub |
| Reference | @modisfast | @appeears | NA | @MODIStsp | @modistools | @rgee |
Table 1: Comparison of modisfast with other alternatives.
Acknowledgements
We thank NASA and its partners for making all their Earth science data freely available, and financing and implementing open data access protocols such as OPeNDAP. We also thank the non-profit OPeNDAP, Inc. for developing and maintaining the eponym tool, and the developers of the R packages modisfast depends on.
This work has been developed over the course of several research projects (REACT 1, REACT 2, ANORHYTHM and DIV-YOO) funded by Expertise France and the French National Research Agency (ANR).
References
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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