MODISTools is an R package for retrieving and using MODIS data subsets using ORNL DAAC web service (SOAP) for subsetting from Oak Ridge National Laboratory (ORNL). It provides a batch method for retrieving subsets of MODIS http://modis.gsfc.nasa.gov/ remotely sensed data and processing them to a format ready for user-friendly application in R, such as statistical modelling.
The most important function is MODISSubsets, for requesting subsets from a given MODIS product for multiple time-series. Each time-series is defined by a coordinate location (WGS-1984), a surrounding area of interest, and a start and end date. Automating this as a batch process reduces time, effort, and human error. Alternatively, MODISTransects expands upon MODISSubsets by extracting MODIS data along a transect, and its surrounding neighbourhood. Downloaded subsets are saved in ASCII files, but can be converted to ASCII grid files for use in a GIS environment. MODISSummaries computes summary statistics of downloaded subsets and organises summarised data back with the original input dataset, creating a csv file that can be easily used for modelling; this provides efficient storage of data and a transparent process from data collection, to processing, to a form that is ready for final use.
The functions were originally used for downloading vegetation indices data, but have been generalised to provide a package that performs the same functionality for any MODIS data that available through the web service. For a list of available MODIS products, see http://daacweb-dev.ornl.gov/MODIS/MODIS-menu/products.html. Other minor functions -- including a lat-long coordinate conversion tool -- are included to aid this process.
Recent stable releases of this package have been checked and built on Windows, Mac, and Linux, and last checked on R 3.1.2 on 2014-12-22. MODISTools is written by Sean Tuck and Helen Phillips. This package can be used under the terms of the GNU GPLv3 license; feel free to use and modify as you wish, but please cite our work where appropriate. To cite MODISTools in publications, please use:
Tuck, S.L., Phillips, H.R.P., Hintzen, R.E., Scharlemann, J.P.W., Purvis, A. and Hudson, L.N. (2014) MODISTools -- downloading and processing MODIS remotely sensed data in R. Ecology and Evolution, 4 (24), 4658--4668. DOI: 10.1002/ece3.1273.
Some of the changes in recent updates:
- New function,
MODISGrid, that takes downloaded ASCII files and converts them into ASCII grid files, which can be used in a GIS environment. - Optional time-series plots for diagnostics as output from
MODISSummaries. MODISGridnow writes MODIS projection (PRJ) files for all ASCII raster grids, so their correct projection is defined. These files can now be loaded directly into a GIS environment.MODISGridnow more flexibly deals with data files that contain multiple products.- Citation for publication in Ecology and Evolution added.
- Documentation and 'Using MODISTools' vignette updated.
Changes coming soon:
- More product-specific time-series summaries in
MODISSummaries.
The most recent stable release can be installed from the CRAN repository, by running:
install.packages("MODISTools")
This is the recommended way to download.
Alternatively, the most up-to-date in-development version of MODISTools can be installed from this github repository. To do this, install the package devtools if you haven't already done so.
install.packages("devtools")
library(devtools)
Then use install_github, with this repository name, to install MODISTools straight from github.
install_github("seantuck12/MODISTools")