{"id":32206918,"url":"https://github.com/spatialstatisticsupna/rgistools","last_synced_at":"2026-02-19T23:01:18.559Z","repository":{"id":56936298,"uuid":"189408663","full_name":"spatialstatisticsupna/RGISTools","owner":"spatialstatisticsupna","description":"Tools for Downloading, Customizing, and Processing Time Series of Satellite Images from Landsat, MODIS, and Sentinel","archived":false,"fork":false,"pushed_at":"2023-02-09T17:48:51.000Z","size":4724,"stargazers_count":50,"open_issues_count":10,"forks_count":16,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-10-22T05:46:38.096Z","etag":null,"topics":["gap-filling","satellite-data","satellite-imagery","smoothing"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/spatialstatisticsupna.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2019-05-30T12:19:26.000Z","updated_at":"2025-03-22T08:14:07.000Z","dependencies_parsed_at":"2023-09-22T07:25:14.520Z","dependency_job_id":null,"html_url":"https://github.com/spatialstatisticsupna/RGISTools","commit_stats":{"total_commits":302,"total_committers":6,"mean_commits":"50.333333333333336","dds":"0.41721854304635764","last_synced_commit":"4d1c72ff0ba6ddac86671175e1d358570cd61a81"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/spatialstatisticsupna/RGISTools","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spatialstatisticsupna%2FRGISTools","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spatialstatisticsupna%2FRGISTools/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spatialstatisticsupna%2FRGISTools/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spatialstatisticsupna%2FRGISTools/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/spatialstatisticsupna","download_url":"https://codeload.github.com/spatialstatisticsupna/RGISTools/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spatialstatisticsupna%2FRGISTools/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29636035,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-19T22:32:43.237Z","status":"ssl_error","status_checked_at":"2026-02-19T22:32:38.330Z","response_time":117,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["gap-filling","satellite-data","satellite-imagery","smoothing"],"created_at":"2025-10-22T05:39:43.768Z","updated_at":"2026-02-19T23:01:18.551Z","avatar_url":"https://github.com/spatialstatisticsupna.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# RGISTools \nHandling multiplatform satellite images.\n```diff\n- CAUTION!!! this package is deprecated, a redefinition of it has been reprogramed under the name rsat. \n- Get it from here https://github.com/ropensci/rsat.\n```\n[![CRAN version](https://www.r-pkg.org/badges/version/RGISTools)](https://cran.r-project.org/web/packages/RGISTools/)\n[![Lifecycle:maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)\n[![Total downloads](https://cranlogs.r-pkg.org/badges/grand-total/RGISTools)](https://cran.r-project.org/web/packages/RGISTools/)\n## Table of contents\n\n- [The package](#the-package)\n- [Installation](#installation)\n- [Credentials for downloading satellite images](#credentials-for-downloading-satellite-images)\n- [Copyright and license](#copyright-and-license)\n\n\n# The package\nThis package enables you downloading, customizing, and processing time series of\nsatellite images from Landsat, MODIS and Sentinel in a standardized way. Some\nfunctions download and convert automatically the platform-specific file formats\ninto GTiff, so they can be loaded in R. The customization functions support tile\nmosaicking, cropping, cloud masking and deriving new variables of interest,\nsuch as the NDVI, EVI, etc. Tile mosaicking is required when the region of\ninterest extends over several tiles, so they can be combined into a single\nimage. Cropping involves removing the pixels outside the region of interest,\nmaking any analysis more computationally and memory efficient. Cloud masking\neliminates cloud reflectance that would otherwise be erroneously attributed\nto land surface features. Cloud removal and (measurement or processing) errors\ntrigger data gaps and outliers, decreasing the quality and quantity of \nmeasurements. Hence, the package includes a set of function for filling and\nsmoothing the satellite imagery. The combination of functions in RGISTools\nresults in a stack of satellite images ready-to-use. Due to the wide variety\nof procedures and sources of information being handled in RGISTools, the\nfunctions are divided into 7 categories, which are identified by the first 3\ncharacters of the function names; \n\n1. ```mod``` identifies Modis Terra and Aqua satellite functions.\n2. ```sen``` identifies Sentinel functions.\n3. ```ls7``` identifies Landsat 7 functions.\n4. ```ls8``` identifies Landsat 8 functions.\n5. ```ls``` identifies both Landsat 7 and 8 functions.\n6. ```gen``` identifies function for being used in any of the three platforms.\n7. ```var``` identifies function for deriving variables in any of the three platforms.\n\nBelow, there is a list of the most important functions grouped by platform,\nand listed in operational order. These functions include searching, previewing,\ndownloading, mosaicking, deriving new variables, compositing, cloud masking\nand filling/smoothing satellite imagery.\n\n## I. Landsat functions\nThe Landsat program is currently releasing imagery captured by two satellites;\nthe Landsat-7 and Lansat-8. Both satellites are treated separately in coding\nterms due to discrepancies in their spectral coverages and data formats. To\ndownload Landsat imagery with the following functions, a USGS's EarthExplorer\naccount is required. Please, register [here](https://ers.cr.usgs.gov/register/).\n\n### Landsat-7\n\n* ```ls7LoadMetadata``` Loads the Landsat-7 metadata file.\n* ```ls7Search``` Seeks a time series of Landsat-7 images.\n* ```lsPreview``` Previews Landsat satellite images.\n* ```lsDownSearch``` Downloads a time series of Landsat images.\n* ```lsMosaic``` Mosaics Landsat images.\n* ```ls7FolderToVar``` Computes new variables from Landsat-7 multispectral images.\n* ```lsCloudMask``` Creates cloud masks for Landsat images.\n* ```genSaveTSRData``` Saves a time series of images.\n\n### Landsat-8\n* ```ls8LoadMetadata``` Loads the Landsat-7 metadata file.\n* ```ls8Search``` Seeks a time series of Landsat-7 images.\n* ```lsPreview``` Previews Landsat satellite images.\n* ```lsDownSearch``` Downloads a time series of Landsat images.\n* ```lsMosaic``` Mosaics Landsat images.\n* ```ls8FolderToVar``` Computes new variables from Landsat-7 multispectral images.\n* ```lsCloudMask``` Creates cloud masks for Landsat images.\n* ```genSaveTSRData``` Saves a time series of images.\n\n## II. MODIS functions\nFunctions in RGISTools download all land products from Terra and Aqua \nsatellites, but the processing focuses on the multispectral images. Be aware\nthat an EarthData account is required to use NASA's web service so, please,\nregister [here](https://urs.earthdata.nasa.gov/users/new).\n\n* ```modSearch``` Seeks a time series of MODIS images.\n* ```modPreview``` Previews MODIS satellite images.\n* ```modDownSearch``` Downloads a time series of MODIS images.\n* ```modMosaic``` Mosaics MODIS images.\n* ```modFolderToVar``` Computes new variables from MODIS multispectral images.\n* ```modCloudMask``` Creates cloud masks for MODIS images.\n* ```genSaveTSRData``` Saves a time series of images.\n\n## III. Sentinel functions\nSentinel archives provide a wide variety of products based on a 5-satellite\nconstellation. The functions to download Sentinel images can cope with any\nproduct available in ESA's SciHub web service. However, image processing is\nfocused on Sentinel-2 multispectal images. SciHub credentials are required to\ndownload Sentinel imagery and can be obtained \n[here](https://scihub.copernicus.eu/dhus/#/self-registration).\n\n* ```senSearch``` Seeks a time series of Sentinel images.\n* ```senPreview``` Previews Sentinel images.\n* ```senDownSearch``` Downloads a time series of Sentinel images.\n* ```senMosaic```  Mosaics Sentinel images.\n* ```senCloudMask```  Creates cloud masks for Sentinel images.\n* ```senFolderToVar``` Computes new variables from Sentinel-2 multispectral images.\n* ```genSaveTSRData``` Saves a time series of images.\n\n## IV. Important general functions\nIn addition to functions above, the package provides some general functions\nfor a better data handling:\n\n* ```genCompositions``` Creates image compositions from a time series of satellite images.\n* ```genSmoothingIMA``` Fills the gaps and smooths outliers in a time series of satellite images.\n* ```genSmoothingCovIMA``` Fills the gaps and smooths outliers in a time series of satellite images using covariates.\n* ```genPlotGIS```  Plots satellite images with a proper GIS format.\n* ```genGetDates``` Gets the capturing date of an image from the name of a raster layer.\n\n\n## V. Remote sensing variables \nNew variables can be derived from multispectral images. The most common\nvariables in the scientific literature are pre-programmed in RGISTools. They\ncan be identified by the prefix \"var\".\n\n* ```varEVI``` Calculates the enhanced vegetation index (EVI).\n* ```varMSAVI2``` Calculates the modified soil-adjusted vegetation index (MSAVI2).\n* ```varNBR``` Calculates the normalized burn ratio (NBR).\n* ```varNBR2``` Calculates the normalized burn ratio 2 (NBR2).\n* ```varNDMI``` Calculates the normalized difference moisture index (NDMI).\n* ```varNDVI``` Calculates the normalized difference vegetation index (NDVI).\n* ```varNDWI```  Calculates the normalized difference water index (NDWI).\n* ```varRGB```  Calculates an RGB image from 3 spectral bands.\n* ```varSAVI```  Calculates the soil-adjusted vegetation index (SAVI).\n\n\n# Installation\n## Install from CRAN\n```\n# Install RGISTools package\ninstall.packages(\"RGISTools\")\n\n# load RGISTools library\nlibrary(RGISTools)\n```\n\n## Install from GitHub\n```\n# Install devtools package from cran repository\ninstall.packages(\"devtools\")\n\n# load devtools library\nlibrary(devtools)\n\n# Install RGISTools from GitHub repositoy\ninstall_github(\"spatialstatisticsupna/RGISTools\")\n```\n## Dependencies for linux\nThe package depends on some R packages that in Linux requires the installation of some libraries before the installation in R. Here you have the command to install all the applications from repository for Debian/Ubuntu and RedHat/Fedora.\n### Debian/Ubuntu\n```\nsudo apt update\nsudo apt install r-cran-rcpp gdal-bin libgdal-dev libproj-dev libssl libssl-dev xml2 libxml2-dev libmagick++-dev\n```\n### RedHat/Fedora\n```\nsudo dnf install gdal gdal_devel proj_devel xml2 libxml2_devel libcurl_devel openssl_devel ImageMagick-c++_devel\n```\n\n# Credentials for downloading satellite images\n### Modis\nCredentials [EarthData](https://ers.cr.usgs.gov/register/) \n\n### Landsat\nCredentials [EarthData](https://ers.cr.usgs.gov/register/) \n\n### Sentinel\nCredentials [SciHub](https://scihub.copernicus.eu/dhus/#/self-registration) \n\n## Copyright and license\nLicensed under the GPL-3 License. [Full license here](/LICENSE.md).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fspatialstatisticsupna%2Frgistools","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fspatialstatisticsupna%2Frgistools","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fspatialstatisticsupna%2Frgistools/lists"}