{"id":16732264,"url":"https://github.com/veroandreo/grass_opengeohub2021","last_synced_at":"2026-01-28T07:33:31.429Z","repository":{"id":134904804,"uuid":"395014058","full_name":"veroandreo/grass_opengeohub2021","owner":"veroandreo","description":"This repo holds the slides, data and code for the presentation \"Analyzing space-time satellite data for disease ecology applications with GRASS GIS and R\" at the OpenGeoHub Summer School 2021","archived":false,"fork":false,"pushed_at":"2021-11-25T00:38:26.000Z","size":45098,"stargazers_count":6,"open_issues_count":0,"forks_count":4,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-01-22T08:35:36.044Z","etag":null,"topics":["grass","lst","rstats","sdm","time-series"],"latest_commit_sha":null,"homepage":"https://veroandreo.github.io/grass_opengeohub2021/presentation.html","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/veroandreo.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-08-11T14:18:02.000Z","updated_at":"2023-07-13T12:45:43.000Z","dependencies_parsed_at":null,"dependency_job_id":"5d99e423-3c40-4007-abb0-0345bcfe70a9","html_url":"https://github.com/veroandreo/grass_opengeohub2021","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/veroandreo%2Fgrass_opengeohub2021","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/veroandreo%2Fgrass_opengeohub2021/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/veroandreo%2Fgrass_opengeohub2021/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/veroandreo%2Fgrass_opengeohub2021/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/veroandreo","download_url":"https://codeload.github.com/veroandreo/grass_opengeohub2021/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243778764,"owners_count":20346611,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["grass","lst","rstats","sdm","time-series"],"created_at":"2024-10-12T23:40:28.574Z","updated_at":"2026-01-28T07:33:31.379Z","avatar_url":"https://github.com/veroandreo.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Analyzing space-time satellite data for disease ecology applications with GRASS GIS and R\n\nIn this session we will explore the combined use of GRASS GIS and R following an example of habitat suitability modeling. We will use a daily time series of LST to extract relevant environmental variables for a mosquito species that transmits West Nile virus in Northern Italy. Particularly, we will use TGRASS to estimate bioclimatic variables such as those from Worldclim, autumnal cooling, spring warming, number of consecutive days with a certain LST value, number of potential mosquito generations, etc. We will then import our vector and raster maps into R and proceed with the habitat suitability modeling and prediction.\n\n## Software\n\n### GRASS GIS\n\nWe will use **GRASS GIS 7.8+**. It can be installed either \nthrough standalone installers/binaries or through\n[OSGeo-Live](https://live.osgeo.org/en/index.html) \n(a linux based virtual machine which includes all OSGeo software and packages).\n\n##### MS Windows\n\nThere are two different options:\n1. [Standalone installer 64-bit](https://grass.osgeo.org/grass78/binary/mswindows/native/x86_64/WinGRASS-7.8.5-2-Setup-x86_64.exe) \n2. [OSGeo4W 64-bit](http://download.osgeo.org/osgeo4w/v2/osgeo4w-setup.exe) \n\nFor Windows users, **we strongly recommend installing GRASS GIS through the OSGeo4W package** (second option), \nsince it allows to install all OSGeo software. See this \n[**installation guide**](https://gitlab.com/veroandreo/grass-gis-conae/-/blob/master/pdf/00_installation.pdf) \nfor details (Follow only the GRASS GIS part).\n\n##### Ubuntu Linux\n\nInstall GRASS GIS 7.8.5 from the \"unstable\" package repository:\n\n```\nsudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable\nsudo apt-get update\nsudo apt-get install grass grass-gui grass-dev\n```\n\n##### Fedora, openSuSe Linux\n\nFor other Linux distributions including **Fedora** and **openSuSe**, simply install GRASS GIS with the respective package manager. See also [here](https://grass.osgeo.org/download/)\n\n##### Mac OS\n\nHave a look at: http://grassmac.wikidot.com/downloads\n\n#### GRASS GIS Add-on that will be used during the demo\n\n* [r.bioclim](https://grass.osgeo.org/grass7/manuals/addons/r.bioclim.html): Calculates bioclimatic indices as those in [WorldClim](https://www.worldclim.org/bioclim).\n\nInstall with `g.extension extension=name_of_addon`\n\n**Attention UNIX-like users:** `g.extension` is currently failing in GRASS. See\nalternative solutions \n[here](https://grass.osgeo.org/news/2021_08_01_g_extension_currently_not_working/) or \n[download](https://github.com/OSGeo/grass-addons/archive/refs/heads/grass7.zip) the addons\nrepo and use: `g.extension extension=name_of_addon url=path/to/addon/folder`.\n\n## R and R-Studio\n\nWell, you know and you'll have it installed for sure :smile: \nThe following packages should be installed beforehand:\n\n```r\n  install.packages(c(\"rgrass7\",\"raster\",\"sf\",\"mapview\",\"biomod2\"))\n```\n\n## Other software\n\nWe will use the software **MaxEnt** to model habitat suitability. The software can be downloaded from: https://biodiversityinformatics.amnh.org/open_source/maxent/\n\n## Data\n\nPlease, create a folder in your `$HOME` directory, or under `Documents` if in Windows, and name it **grassdata_ogh**. Then, download the following ready to use *location* and unzip  within `grassdata_ogh`:\n\n* [Northern Italy (1.7 Gb)](https://drive.google.com/file/d/1z1b2NLC4Z6yzz_57RddTdRRK_gUkd7fU/view?usp=sharing)\n\nIn the end, your `grassdata` folder should look like this:\n\n```\n  grassdata/\n  └── eu_laea\n      ├── italy_LST_daily\n      └── PERMANENT\n```\n\n\n## Bio\n\n[**Verónica Andreo**](https://veroandreo.gitlab.io/) is a biologist. She holds a PhD in\nBiological Sciences and an MSc in Remote Sensing and GIS applications. She works as a \nresearcher for [CONICET](https://www.conicet.gov.ar/) and lecturer at\n[Gulich Institute](http://ig.conae.unc.edu.ar/) - Argentinian Space\nAgency [(CONAE)](https://www.argentina.gob.ar/ciencia/conae) in Córdoba, Argentina.\nHer research is focused on uncovering **environmental drivers of vector-borne disease outbreaks**. \nShe is mostly interested in those environmental features that can be derived \n**by means of satellite image analysis, remote sensing time series and GIS-based techniques**. \n\nVerónica is part of the [GRASS GIS](https://grass.osgeo.org/) Development team and has \nrecently become [the new PSC chair](https://grass.osgeo.org/news/2021_02_05_new_grass_psc/). \nShe is a strong advocate for [OSGeo](https://www.osgeo.org/) and free and open \nsource software for geo-spatial (FOSS4G), currently serving as Program Committee chair \nfor [**FOSS4G 2021**](2021.foss4g.org/). Among other things, she has volunteered as a \nmentor for GRASS GIS in the [Google Code-In contest](https://codein.withgoogle.com/)\nintroducing high school students into the Open Source world.\n\n## GRASS References\n\n- Neteler, M. and Mitasova, H. (2008): *Open Source GIS: A GRASS GIS Approach*. Third edition. ed. Springer, New York. [Book site](https://grassbook.org/)\n- Neteler, M., Bowman, M.H., Landa, M. and Metz, M. (2012): *GRASS GIS: a multi-purpose Open Source GIS*. Environmental Modelling \u0026 Software, 31: 124-130 [DOI](http://dx.doi.org/10.1016/j.envsoft.2011.11.014)\n- Gebbert, S. and Pebesma, E. (2014). *A temporal GIS for field based environmental modeling*. Environmental Modelling \u0026 Software, 53, 1-12. [DOI](https://doi.org/10.1016/j.envsoft.2013.11.001)\n- Gebbert, S. and Pebesma, E. (2017). *The GRASS GIS temporal framework*. International Journal of Geographical Information Science, 31, 1273-1292. [DOI](http://dx.doi.org/10.1080/13658816.2017.1306862)\n- Gebbert, S., Leppelt, T. and Pebesma, E. (2019). *A Topology Based Spatio-Temporal Map Algebra for Big Data Analysis*. Data, 4, 86. [DOI](https://doi.org/10.3390/data4020086)\n\n## License\n\nAll the course material is under \n[![Creative Commons License](assets/img/ccbysa.png)](http://creativecommons.org/licenses/by-sa/4.0/) Creative Commons Attribution-ShareAlike 4.0 International License\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fveroandreo%2Fgrass_opengeohub2021","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fveroandreo%2Fgrass_opengeohub2021","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fveroandreo%2Fgrass_opengeohub2021/lists"}