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Development","sub_category":"Environmental Satellites","monthly_downloads":2118,"total_dependent_repos":17,"total_dependent_packages":2,"readme":"# MODISTools \u003ca href='https://github.com/bluegreen-labs/MODISTools'\u003e\u003cimg src='https://raw.githubusercontent.com/bluegreen-labs/MODISTools/master/MODISTools-logo.png' align=\"right\" height=\"139\" /\u003e\u003c/a\u003e\n\n[![R build\nstatus](https://github.com/bluegreen-labs/MODISTools/workflows/R-CMD-check/badge.svg)](https://github.com/bluegreen-labs/MODISTools/actions)\n[![codecov](https://codecov.io/gh/bluegreen-labs/MODISTools/branch/main/graph/badge.svg)](https://app.codecov.io/gh/bluegreen-labs/MODISTools/tree/main/R)\n![Status](https://www.r-pkg.org/badges/version/MODISTools)\n![Downloads](https://cranlogs.r-pkg.org/badges/grand-total/MODISTools)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7551165.svg)](https://doi.org/10.5281/zenodo.7551165)\n\nProgrammatic interface to the [‘MODIS Land Products Subsets’ web\nservices](https://modis.ornl.gov/data/modis_webservice.html). Allows for\neasy downloads of [‘MODIS’](https://modis.gsfc.nasa.gov/) time series\ndirectly to your R workspace or your computer. When using the package\nplease cite the manuscript as referenced below. Keep in mind that the\noriginal manuscript describes versions prior to release 1.0 of the\npackage. Functions described in this manuscript do not exist in the\ncurrent package, please consult [the\ndocumentation](https://bluegreen-labs.github.io/MODISTools/) to find\nmatching functionality.\n\nPlease cite the package in your work as: \n\n\u003e Koen Hufkens. (2023). bluegreen-labs/MODISTools: MODISTools v1.1.5. Zenodo. https://doi.org/10.5281/zenodo.7551164\n\n## Installation\n\n### stable release\n\nTo install the current stable release use a CRAN repository:\n\n``` r\ninstall.packages(\"MODISTools\")\nlibrary(\"MODISTools\")\n```\n\n### development release\n\nTo install the development releases of the package run the following\ncommands:\n\n``` r\nif(!require(remotes)){install.package(\"remotes\")}\nremotes::install_github(\"bluegreen-labs/MODISTools\")\nlibrary(\"MODISTools\")\n```\n\nVignettes are not rendered by default, if you want to include additional\ndocumentation please use:\n\n``` r\nif(!require(remotes)){install.package(\"remotes\")}\nremotes::install_github(\"bluegreen-labs/MODISTools\", build_vignettes = TRUE)\nlibrary(\"MODISTools\")\n```\n\n## Use\n\n### Downloading MODIS time series\n\nTo extract a time series of modis data for a given location and its\ndirect environment use the mt_subset() function.\n\n\u003cdetails\u003e\n\u003csummary\u003e\ndetailed parameter description (click to expand)\n\u003c/summary\u003e\n\u003cp\u003e\n\n| Parameter | Description                                                                                                                     |\n|-----------|---------------------------------------------------------------------------------------------------------------------------------|\n| product   | a MODIS product                                                                                                                 |\n| band      | a MODIS product band (if NULL all bands are downloaded)                                                                         |\n| lat       | latitude of the site                                                                                                            |\n| lon       | longitude of the site                                                                                                           |\n| start     | start year of the time series (data start in 1980)                                                                              |\n| end       | end year of the time series (current year - 2 years, use force = TRUE to override)                                              |\n| internal  | logical, TRUE or FALSE, if true data is imported into R workspace otherwise it is downloaded into the current working directory |\n| out_dir   | path where to store the data when not used internally, defaults to tempdir()                                                    |\n| km_lr     | force “out of temporal range” downloads (integer)                                                                               |\n| km_ab     | suppress the verbose output (integer)                                                                                           |\n| site_name | a site identifier                                                                                                               |\n| site_id   | a site_id for predefined locations (not required)                                                                               |\n| progress  | logical, TRUE or FALSE (show download progress)                                                                                 |\n\n\u003c/p\u003e\n\u003c/details\u003e\n\n``` r\n# load the library\nlibrary(MODISTools)\n\n# download data\nsubset \u003c- mt_subset(product = \"MOD11A2\",\n                    lat = 40,\n                    lon = -110,\n                    band = \"LST_Day_1km\",\n                    start = \"2004-01-01\",\n                    end = \"2004-02-01\",\n                    km_lr = 1,\n                    km_ab = 1,\n                    site_name = \"testsite\",\n                    internal = TRUE,\n                    progress = FALSE)\nprint(str(subset))\n```\n\nThe output format is a *tidy* data frame, as shown above. When witten to\na csv with the parameter `internal = FALSE` this will result in a flat\nfile on disk.\n\nNote that when a a region is defined using km_lr and km_ab multiple\npixels might be returned. These are indexed using the `pixel` column in\nthe data frame containing the time series data. The remote sensing\nvalues are listed in the `value` column. When no band is specified all\nbands of a given product are returned, be mindful of the fact that\ndifferent bands might require different multipliers to represent their\ntrue values. To list all available products, bands for particular\nproducts and temporal coverage see function descriptions below.\n\n### Batch downloading MODIS time series\n\nWhen a large selection of locations is needed you might benefit from\nusing the batch download function `mt_batch_subset()`, which provides a\nwrapper around the `mt_subset()` function in order to speed up large\ndownload batches. This function has a similar syntax to `mt_subset()`\nbut requires a data frame defining site names (site_name) and locations\n(lat / lon) (or a comma delimited file with the same structure) to\nspecify a list of download locations.\n\nBelow an example is provided on how to batch download data for a data\nframe of given site names and locations (lat / lon).\n\n``` r\n# create data frame with a site_name, lat and lon column\n# holding the respective names of sites and their location\ndf \u003c- data.frame(\"site_name\" = paste(\"test\",1:2))\ndf$lat \u003c- 40\ndf$lon \u003c- -110\n  \n# test batch download\nsubsets \u003c- mt_batch_subset(df = df,\n                     product = \"MOD11A2\",\n                     band = \"LST_Day_1km\",\n                     internal = TRUE,\n                     start = \"2004-01-01\",\n                     end = \"2004-02-01\")\n\nprint(str(subsets))\n```\n\n### Listing products\n\nTo list all available products use the mt_products() function.\n\n``` r\nproducts \u003c- mt_products()\nhead(products)\n```\n\n### Listing bands\n\nTo list all available bands for a given product use the mt_bands()\nfunction.\n\n``` r\nbands \u003c- mt_bands(product = \"MOD11A2\")\nhead(bands)\n```\n\n### listing dates\n\nTo list all available dates (temporal coverage) for a given product and\nlocation use the mt_dates() function.\n\n``` r\ndates \u003c- mt_dates(product = \"MOD11A2\", lat = 42, lon = -110)\nhead(dates)\n```\n\n## References\n\nKoen Hufkens. (2023). bluegreen-labs/MODISTools: MODISTools v1.1.5. Zenodo. https://doi.org/10.5281/zenodo.7551164\n\n## Acknowledgements\n\nOriginal development was supported by the UK Natural Environment\nResearch Council (NERC; grants NE/K500811/1 and NE/J011193/1), and the\nHans Rausing Scholarship. Refactoring was supported through the Belgian\nScience Policy office COBECORE project (BELSPO; grant\nBR/175/A3/COBECORE). Logo design elements are taken from the FontAwesome\nlibrary according to [these terms](https://fontawesome.com/license),\nwhere the globe element was inverted and intersected.\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.5281/zenodo.7551165","https://doi.org/10.5281/zenodo.7551164"],"works":{"https://doi.org/10.5281/zenodo.7551165":null,"https://doi.org/10.5281/zenodo.7551164":null},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/5537","html_url":"https://ost.ecosyste.ms/projects/5537"}