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<title>GRASS GIS 8: From Desktop to Big Data Cubes</title>
<meta name="description" content="GRASS GIS talk slides for Geo-harmonizer Workshop 2021 in Wageningen">
<meta name="author" content="Veronica Andreo, Vaclav Petras, Martin Landa, Anna Petrasova, Guido Riembauer, Māris Nartišs, Moritz Lennert, Markus Metz, Stefan Blumentrath, Huidae Cho and Markus Neteler">
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<section>
<h1>GRASS GIS 8: from Desktop to Big Data Cubes</h1>
<p style="margin-top: 0.5em">
<a href="https://veroandreo.gitlab.io/">Verónica Andreo</a>
<br>
& Vaclav Petras, Martin Landa, Anna Petrasova, Guido Riembauer,
Māris Nartišs, Moritz Lennert, Markus Metz, Stefan Blumentrath,
Huidae Cho, Markus Neteler
</p>
<img src="img/grass_gis.svg" class="stretch">
<p><small>Open Data Science Europe Workshop - Wageningen, 2021</small></p>
<p><small><a href="https://veroandreo.github.io/grass-gis-talks/wageningen2021.html">veroandreo.github.io/grass-gis-talks</a></small>
</section>
<section>
<h2>About the presenter...</h2>
<br>
<ul>
<li>PhD in Biology and MSc in Remote Sensing and GIS</li>
<img class="bio-img" src="img/vero_round_small.png">
<li>Researcher and lecturer at <a href="https://ig.conae.unc.edu.ar">Gulich Institute</a> from the <a href="https://www.argentina.gob.ar/ciencia/conae">Argentinean Space Agency - CONAE</a>, working on applications of RS & GIS for disease ecology</li>
<li><a href="https://grass.osgeo.org/">GRASS GIS</a> dev team and PSC Chair</li>
<li><a href="https://www.osgeo.org">OSGeo</a> Charter member</li>
<li><a href="https://2021.foss4g.org">FOSS4G</a> enthusiast and advocate</li>
</ul>
<p align="right" style="font-size:18px"><a href="https://veroandreo.gitlab.io/">https://veroandreo.gitlab.io/</a></p>
</section>
<section data-markdown
data-background-image="https://grass.osgeo.org//images/logos/banner.jpg"
data-background-opacity="0.6">
<textarea data-template>
## Overview of this talk
- Which GRASS?
- What's new in GRASS GIS 8?
- GRASS loves Remote Sensing
- GRASS ready for the cloud
- Application examples
- Resources
- Get involved
</textarea>
</section>
<section id="GRASS general">
<section>
<h2>Which GRASS?</h2>
<div class="columns">
<div class="column" style="width:59%">
<ul>
<li><b>GRASS GIS</b> (Geographic Resources Analysis Support System), a FOSS suite used for geospatial data management and analysis, image processing, spatial modeling, and visualization.</li>
<li>Originally developed by the U.S. Army CERL for land management and environmental planning (1982-1995).</li>
<li><a href="https://grass.osgeo.org/about/history/">38 years of continuous geospatial development</a></li>
</ul>
</div>
<div class="column" style="width:39%;text-align:center;padding-top:0.5em;">
<img src="img/grass_38_bday.png" width="100%">
</div>
</div>
</section>
<section data-background-image="img/grass_template.png"
data-background-position="bottom"
data-background-size="100% 20%">
<h2>A bit of (geek) GRASS GIS history...</h2>
<br>
<iframe width="560" height="315" scrolling="no" src="https://av.tib.eu/player/12963" frameborder="0" allowfullscreen></iframe>
<br><br>
<blockquote>In case you didn't notice, the video is narrated by William Shatner <i class="fa fa-rocket fa-2x"></i> </blockquote><br><br>
</section>
<section id="GRASS generalities" data-background-image="img/grass_template.png"
data-background-position="bottom"
data-background-size="100% 20%">
<h2>GRASS GIS general features</h2>
<ul>
<li>Free and open source, you can use, modify, improve, share</li>
<li>Large amount of tools: <b>+500</b> <a href="https://grass.osgeo.org/grass80/manuals/full_index.html">core modules</a>, <b>+300</b> <a href="https://grass.osgeo.org/grass78/manuals/addons/">addons</a></li>
<li>Graphical User Interface and command line</li>
<li>C API, Python API and libraries</li>
<li>Interface/connection with R, QGIS, WPS, etc.</li>
<li>Different data types supported:
<a href="https://grass.osgeo.org/grass-stable/manuals/rasterintro.html">raster</a>
(including <a href="https://grass.osgeo.org/grass-stable/manuals/imageryintro.html">satellite imagery</a>),
<a href="https://grass.osgeo.org/grass-stable/manuals/raster3dintro.html">3D raster or voxel</a>,
<a href="https://grass.osgeo.org/grass-stable/manuals/vectorintro.html">vector</a> and,
<a href="https://grass.osgeo.org/grass-stable/manuals/temporalintro.html">space-time datasets</a>.</li>
</ul>
</section>
<section>
<h2>Interfaces</h2>
<div style="position:relative; width:780px; height:480px; margin:0 auto;">
<img class="fragment fade-out" data-fragment-index="0" width="780" height="480" src="img/qgis_grass_plugin.png" style="position:absolute;top:0;left:0;"/>
<img class="fragment fade-in" data-fragment-index="0" width="780" height="480" src="img/qgis_processing.png" style="position:absolute;top:0;left:0;" />
</div>
</section>
<section>
<h2>Interfaces</h2>
<div style="position:relative; width:780px; height:480px; margin:0 auto;">
<img class="fragment fade-out" data-fragment-index="0" width="780" height="480" src="img/RwithinGRASS_and_Rstudio_from_grass.png" style="position:absolute;top:0;left:0;" />
<img class="fragment fade-in" data-fragment-index="0" width="780" height="480" src="https://ncsu-geoforall-lab.github.io/grass-as-a-platform/img/grass_pyedit.png" style="position:absolute;top:0;left:0;" />
</div>
</section>
<section>
<h2>All-in-one software suite</h2>
<ul>
<li>All matured tools available right away
<li>Download of experimental tools possible
<li>Network analysis, hydrology, remote sensing, OBIA, time series, …
</ul>
<br>
<img src="img/hexagons_3d_white_outlier.png" class="stretch">
</section>
<section>
<h1>Cool stuff that has been there for a while...</h1>
<img src="https://upload.wikimedia.org/wikipedia/commons/thumb/8/83/Noto_Emoji_Pie_1f60e.svg/512px-Noto_Emoji_Pie_1f60e.svg.png" width="30%">
</section>
<section>
<h2>64-bit and large file support in all Operating Systems</h2>
<img src="img/big_files.jpg" class="stretch">
<p><b>392 billion cells!</b></p>
</section>
<section>
<h2>Time series support</h2>
<div class="r-stack">
<img class="fragment" src="img/tgrass_flowchart.png" width="70%">
<img class="fragment" src="img/tplot.png" width="70%">
<img class="fragment" src="https://gitlab.com/veroandreo/grass-gis-conae/-/raw/master/assets/img/3month_lst_anim_small.gif" width="70%">
</div>
<p>by Sören Gebbert, Luca Delucchi, Anna Petrasova, …</p>
</section>
<section>
<h2>FUTURES</h2>
<p><em>r.futures</em> - set of tools for urban growth modeling</p>
<p>Improved scalability, new validation modules</p>
<img src="img/FUTURES_addon.png" class="stretch">
<p>by NC State Center for Geospatial Analytics</p>
<aside class="notes">
r.futures is a set of modules for urban growth modeling
based on historical land cover and population data.
New version is more scalable and includes validation modules.
</aside>
</section>
<section>
<h2>PoPS</h2>
<p><em>r.pops.spread</em> - Pest or Pathogen Spread simulation</p>
<img src="img/pops_version_1.png" class="stretch">
<p>by NC State Center for Geospatial Analytics
</section>
<section>
<h2>Tangible Landscape</h2>
<p>Geospatial tangible user interface</p>
<img src="img/cli_tangible.png" class="stretch">
<p>by NC State Center for Geospatial Analytics</p>
</section>
<section>
<h2>Community & Shared Improvements</h2>
<ul>
<li>Provides software to the public.</li>
<li>Shares its source code.</li>
<li>Includes latest additions.</li>
</ul>
<br>
<img src="img/grass_team.jpg" class="stretch">
<p><em>Credit goes to the whole community, not just this talk's authors</em></p>
</section>
<section>
<h2>Real Global Community</h2>
<ul>
<li>Open community of users and developers</li>
<li>Contributors to code, documentation, translations, …</li>
<li>Project Steering Committee</li>
</ul>
<br>
<img src="img/psc_meeting_2021.png" class="stretch">
</section>
<section>
<h2>Scientific Foundations</h2>
<ul>
<li>references to related scientific papers</li>
<li>references to papers associated with tools or libraries</li>
<li>tools used in open science</li>
</ul>
<br>
<img src="img/module_references.png" class="stretch">
<br>
<a href="https://scholar.google.com/citations?user=gJ0ZB0cAAAAJ">GRASS GIS google scholar profile</a>
</section>
<section>
<h2>Innovation with stability</h2>
<ul>
<li>Graphical user interface changes as needed.</li>
<li>Python API added in v6, extended in v7.</li>
<li>Basic things continue to work in the same way.</li>
</ul>
<br><br>
<p><em>Raster algebra expression from 2002 (v5) in 2021 (v8):</em></p>
<p>
<code>
depressions<em style="background-color: #f84040;"> </em>=<em style="background-color: #f84040;"> </em>
if((elevation - fill) < 0, 1, 0)
</code>
</p>
</section>
<section>
<h2>Support</h2>
<ul>
<li>Community support
<ul>
<li><a href="https://lists.osgeo.org/mailman/listinfo/grass-user">user mailing list</a> <small>(with vast archives since 1991)</small>
<li><a href="https://gis.stackexchange.com/questions/tagged/grass">GIS StackExchange</a>
<li><a href="https://github.com/OSGeo/grass/discussions">Discussions</a> on GitHub</li>
<li>…
</ul>
<li>Commercial support
<ul>
<li><a href="https://www.mundialis.de/en/open-source-gis/">mundialis</a>
<li><a href="https://www.northrivergeographic.com/">North River Geographic Systems</a>
<li><a href="https://geospatial.ncsu.edu/engage/service-center/">Center for Geospatial Analytics, NC State University</a>
<li>…
</ul>
</ul>
<br>
<img src="img/grass_gis.svg" alt="GRASS GIS logo" class="stretch">
</section>
</section>
<section id="GRASS 8">
<section>
<h2>GRASS GIS 8</h2>
<ul>
<li>Roadmap:
<ul>
<li>7.8.6 Fall 2021
<ul>
<li>Old but still good.</li>
</ul>
</li>
<li>8.0.0 Fall 2021
<ul>
<li>First release in a new era.</li>
</ul>
</li>
<li>8.0.1 Winter 2021
<ul>
<li>What did we miss?</li>
</ul>
</li>
<li>8.2.0 Spring 2022
<ul>
<li>Enjoy the GSoC 2021 results!</li>
</ul>
</li>
</ul>
</li>
</ul>
<br>
<img src="img/splash_screen.png" class="stretch">
</section>
<section>
<h1>Exciting new features in GRASS 8</h1>
<i class="fa fa-rocket fa-4x"></i>
</section>
<section>
<h2>Dark Theme Support</h2>
Interface respects system dark theme.
<br>
<img src="img/dark_theme_v_clip.png" class="stretch">
<p>by Anna Petrasova, Nicklas Larsson
</section>
<section>
<h2>Improved First-time User Experience</h2>
Initial project sets up automatically. Guidance provided for next steps.
<br>
<img class="stretch" src="img/first-time_user_world.png">
<p>
by Linda Kladivova &
rest of the community (many reviews, calls, user surveys, …)
</p>
</section>
<section>
<h2>Improved First-time User Experience</h2>
<div style="position:relative; width:640px; height:580px; margin:0 auto;">
<img class="fragment fade-out" data-fragment-index="0" width="640" height="580" src="https://veroandreo.github.io/grass_opengeohub2021/assets/img/start_grass.png" style="position:absolute;top:0;left:0;">
<img class="fragment fade-in" data-fragment-index="0" width="640" height="580" src="img/grass_startup_gone.png" style="position:absolute;top:0;left:0;">
</div>
</section>
<section>
<h2>Centralized Data Management</h2>
All data manipulation centered around revamped <em>Data</em> tab.
<br>
<img src="img/data_catalog_isolines.png" class="stretch">
<p>by Linda Kladivova, Anna Petrasova, Vaclav Petras
</section>
<section>
<h2>Raster band references and portable signature files</h2>
<ul>
<li>assign a band reference (semantic label) to any raster map</li>
<li>extended metadata for band reference</li>
<li>band references stored in classification signature files</li>
<li>signature files can be used for classification if band references match (raster values are semantically equal)</li>
</ul>
<br>
<img src="img/band_references_scheme.png" class="stretch">
<p>by Māris Nartišs and Martin Landa</p>
</section>
<section>
<h2>Faster External Data Links</h2>
<em>r.external</em> links (opens) external raster data (GeoTiffs, …) faster.
<br>
<small>(2-5× faster, or almost no time for some workflows)</small>
<br>
<img src="img/r_external.png" class="stretch">
<p>by Markus Metz</p>
<p>Great for workflows when only portion of the data is processed in GRASS GIS.</p>
</section>
<section>
<h2>LiDAR data import with PDAL</h2>
<ul>
<li>import of any point dimension (including user defined ones e.g. from PDAL filters)</li>
<li>support of 19 binning methods (including eigenvalues)</li>
<li>point filtering by values in any dimension</li>
</ul>
<img src="img/scan_angle.png" width="47%"><img src="img/elevation.png" width="50%">
<p>by Vaclav Petras and Māris Nartišs</p>
</section>
<section>
<h2>Skeletons and Centerlines</h2>
<em>v.voronoi</em> tool can now create area skeletons and centerlines.
<img src="img/lake_skeleton_naip.png" class="stretch">
<p>by Markus Metz
</section>
<section>
<h2>Latest PROJ and GDAL</h2>
<ul>
<li>Support for PROJ >=6 added.</li>
<li>Support for GDAL >=3 added.</li>
<li>WKT2 can be used for CRS definitions.</li>
<li>High-accuracy coordinate transformations supported.</li>
</ul>
<img src="img/natural_europe.png" class="stretch">
<p>by Markus Metz</p>
<aside class="notes">
GRASS is currently supporting the latest versions of PROJ and GDAL.
All the fancy new high-accuracy coordinate transformation methods are supported.
The WKT2 can be used to define a CRS and is printed as CRS info by g.proj.
Some new PROJ 8 functionality is not yet supported.
For example, automated download of datum transformation grids is yet missing.
</aside>
</section>
<section>
<h2>Improved and robust code quality checks</h2>
<ul>
<li>Python code formatted by Black.</li>
<li>Python code checked against Flake8.</li>
<li>Most of warnings in C code removed and now checked.</li>
<li>Code tested with CodeQL.</li>
<li>Flake8 and Black checks also for Addons.</li>
</ul>
<img src="img/code_in_vscodium.png" class="stretch">
<p>by Nicklas Larsson, Vaclav Petras, Anna Petrasova, Carmen Tawalika, ...
</section>
<section>
<h2>Google Summer of Code 2021</h2>
<h3>OpenMP parallelization by Aaron Saw Min Sern</h3>
<div class="container">
<div class="col">
<ul>
<li>r.series</li>
<li>r.univar</li>
<li>r.neighbors</li>
<li>r.patch</li>
<li>r.resamp.interp</li>
<li>r.resamp.filter</li>
<li>r.mfilter</li>
<li>r.slope.aspect</li>
</ul>
<p> + benchmarking library</p>
</div>
<div class="col">
<img src="img/gsoc/openmp.png">
</div>
</div>
<p>Coming in 8.2</p>
<aside class="notes">
<ul>
<li>Parallelization of multiple, often used raster modules, with benchmarks.</li>
<li>Especially useful for big data processing</li>
<li>Can work on all platforms, providing GRASS is compiled with OpenMP</li>
</ul>
</aside>
</section>
<section>
<h2>Google Summer of Code 2021</h2>
<h3>Single-Window GUI by Linda Kladivova</h3>
<img src="img/gsoc/proposal3.png" class="stretch">
<p>
Code refactoring to enable Single-Window GUI with dockable widgets.
</p>
<p>Coming in 8.2</p>
</section>
<section>
<h2>Google Summer of Code 2021</h2>
<h3>Integration of GRASS GIS and Jupyter Notebooks by Caitlin Haedrich</h3>
<img src="img/gsoc/InteractiveVectorMaps.PNG" class="stretch">
<p>
New Python library that simplifies the launch of GRASS GIS in Jupyter and the interactive display of raster/vector data.
</p>
<aside class="notes">
<ul>
<li>Simpler GRASS GIS initialization</li>
<li>More intuitive API for rendering</li>
<li>Classic rendering with d.* commands, rendering with webmap and zooming, also 3D rendering</li>
<li>Available now as experimental, coming in 8.2 officially</li>
</ul>
</aside>
</section>
<section>
<h1>Many new addons contributed by the community</h1>
<br>
<img src="img/bonn_osgeo_code_sprint_2018.jpg" width="55%">
</section>
<section>
<h2>Spatial Query of Projections</h2>
<em>g.projpicker</em> queries projections spatially using user-drawn geometries and set-theoretic logical operators.
It requires <a href="https://projpicker.readthedocs.io/">ProjPicker</a>.
<br>
<img src="img/g_projpicker_gui.png" class="stretch">
<p>by Huidae Cho</p>
</section>
<section>
<h2>Hydrologic Parameters Using a Flow Direction Raster</h2>
<em>r.accumulate</em> calculates weighted flow accumulation, subwatersheds, stream networks, and longest flow paths using a flow direction map.
<br>
<img src="img/r_accumulate_nc_lfp_example_subwatersheds.png" class="stretch">
<p>by Huidae Cho</p>
</section>
<section>
<h2>Creating a Gabor filter bank</h2>
<em>i.gabor</em> creates directional filters for image segmentation using i.segment. It requires NumPy and SciPy.
<br>
<img src="img/i_gabor_imaginary.png" width="45%">
<img src="img/i_gabor_segment.png" width="45%">
<p>by Owen Smith</p>
</section>
<section>
<h2>Ecological applications</h2>
<p><em>r.suitability.regions</em> allows to identify suitable regions, e.g., for species in danger, starting from suitability maps.</p>
<img src="https://ecodiv.earth/TutorialsNotes/SuitabilityRegions/images/suit002.png" class="stretch">
<p>by Paulo van Breugel</p>
</section>
<section>
<h2>Weighted layers for dasymetric mapping</h2>
<p><em>r.area.createweight</em> creates a weighting layer for dasymetric mapping using a random forest regression model.</p>
<img src="img/r.area.createweight_out.png" class="stretch">
<p>by Charlotte Flasse, Tais Grippa and Safa Fennia. <a href="https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-55-2021">DOI.</a></p>
</section>
<section>
<h2>Can you see that landslide??</h2>
<p><em>r.survey</em> allows to assess whether objects of certain size could be detected by an observer moving along roads or sitting on a flying object</p>
<img src="https://pbs.twimg.com/media/E5zqWcvXsAMKND5?format=jpg&name=4096x4096" class="stretch">
<p>by Ivan Marchesini</p>
</section>
<section>
<h2>Tap directly into FAIR data warehouses</h2>
<h4>GRASS GIS understands netCDF data that follows the CF-convention</h4>
<div class="container_flex">
<div class="column">
<small>
<ul>
<li><em>m.crawl.thredds</em>: Lists URLs for netCDF datasets on Thredds servers</li>
<li><em>t.rast.import.netcdf</em>: Makes Spatio-temporal data in netCDF format directly available for analysis in GRASS STRDS (also without downloading)</li>
</ul>
</small>
</div>
<div class="column">
<img src="img/netcdf_screenshot.jpg" width=100%>
</div>
</div>
<br>
<p>
<small>
Enjoy data delivered right into your GRASS GIS database from e.g.:
</small>
<img src="img/netcdf_sources.png" width=100% class="stretch">
</p>
<p><small>
by Stefan Blumentrath (Norwegian Institute for Nature Research - NINA) …
</small></p>
</section>
</section>
<section id="GRASS for Remote Sensing">
<section>
<h1>GRASS loves Remote Sensing</h1>
<br>
<img src="https://gitlab.com/veroandreo/curso-grass-gis-rioiv/-/raw/master/assets/img/image_flyer.png" class="stretch">
</section>
<section>
<h2>Dedicated tools for image processing and analysis</h2>
<div class="columns">
<div class="column" style="width:49%">
<ul>
<li>50+ core modules</li>
</ul>
<img src="img/imagery_core_modules.png" width="90%">
</div>
<div class="column" style="width:49%">
<ul>
<li>60+ addons, e.g., OBIA chain</li>
</ul>
<img width="90%" src="https://camo.githubusercontent.com/300a0e87e3ca6b170e8d48e681819e04dafc595c8df3e1caa01aeaaa9bb6d9b8/687474703a2f2f7777772e6d6470692e636f6d2f72656d6f746573656e73696e672f72656d6f746573656e73696e672d30392d30303335382f61727469636c655f6465706c6f792f68746d6c2f696d616765732f72656d6f746573656e73696e672d30392d30303335382d61672e706e67">
</div>
</div>
</section>
<section>
<h2>Sentinel, MODIS, Landsat, NED, NAIP</h2>
<p>
Automated download and import of common datasets
<small>i.sentinel, i.modis, i.landsat, r.in.usgs, r.in.nasadem, …</small>
</p>
<img src="img/usgs_ned_naip_3d.png" class="stretch">
<p>
<small>
by
Luca Delucchi (Fondazione Edmund Mach),
Martin Landa (OpenGeoLabs),
Anika Weinmann (mundialis),
Guido Riembauer (mundialis),
Roberta Fagandini (GSoC),
Zechariah Krautwurst (GSoC),
Anna Petrasova (NC State University),
Vaclav Petras (NC State University),
Veronica Andreo (CONICET), …
</small>
</p>
</section>
<section>
<h2>GRASS Sentinel Addons</h2>
<br>
<p>
<h4>Access & Downloading → Importing → Preprocessing → Analysis </h4>
<br>
<img src="img/example_s2_imagery.png" class="stretch">
<p><font size="1">Contains modified Copernicus Sentinel data (2021)</font></p>
</section>
<section>
<h2>Access & Downloading</h2>
<ul>
<li><b><em>i.sentinel.coverage</li>
<li>i.sentinel.download</b></em>
<ul>
<li>ESA Copernicus Open Access Hub</li>
<li>USGS Earth Explorer</li>
<li>Google Cloud Storage</li>
</ul>
</ul>
<br>
<img src="img/s2_search_and_download.gif" class="stretch">
</section>
<section>
<h2>Importing</h2>
<ul>
<li><b><em>i.sentinel.import</b></em>
<ul>
<li>selection of individual bands</li>
<li>import of metadata, band reference, cloud masks</li>
</ul>
<li><b><em>t.sentinel.import</b></em></li>
<li><b><em>r.s1.grd.import</li></b></em>
</ul>
<br>
<img src="img/s2_in_grass.png" class="stretch">
</section>
<section>
<h2>Importing</h2>
<ul>
<li>Importing into a space-time raster dataset with <b><em>t.sentinel.import</b></em>
</ul>
<br>
<img src="img/s2_importing_strds.gif" class="stretch">
</section>
<section>
<h2>Preprocessing</h2>
<ul>
<b><em><li>i.sentinel.mask</li>
<li>t.sentinel.mask</li>
<li>i.sentinel.preproc</li>
<li>i.sentinel-2.sen2cor</li>
<li>t.rast.mosaic</li>
<li>i.sar.speckle</li></b></em>
</ul>
</section>
<section>
<h2>Preprocessing: cloud masking with <b><em>i.sentinel.mask</b></em></h2>
<br>
<img src="img/cloudmasking.png" class="stretch">
</section>
<section>
<h2>Preprocessing: temporal mosaicking with <b><em>t.rast.mosaic</b></em></h2>
<br>
<img src="img/trastmosaic.png" class="stretch">
</section>
<section>
<h2>Preprocessing: Sentinel-1 data</h2>
<ul>
<li><b><em>r.s1.grd.import</b></em>
<ul>
<li>requires ESA's SNAP software</li>
<li>complete SAR preprocessing chain</li>
</ul>
</ul>
<br>
<img src="img/s1_in_grass.png" class="stretch">
</section>
</section>
<section id="GRASS is ready for the cloud">
<section>
<h1>GRASS is ready for the cloud</h1>
<img src="img/grass_in_the_clouds.png" width="50%">
</section>
<section>
<h2>GRASS in docker containers</h2>
<br>
<ul>
<li>Different flavours</li>
<li>Built and updated automatically</li>
<li>Can be deployed anywhere you need them</li>
</ul>
<img src="img/grass_docker.png" class="stretch">
<p>See <a href="https://grass.osgeo.org/download/docker/">https://grass.osgeo.org/download/docker/</a></p>
</section>
<section>
<h2><a href="https://actinia.mundialis.de/"><strong>actinia</strong></a>: The GRASS GIS REST API</h2>
<ul>
<img src="img/actinia.png" width="80px" style="float:right;pad-right:15px;">
<li>Open source REST API for scalable, distributed, high performance processing of geo data using GRASS GIS</li>
<li>More details in this <a href="https://mundialis.github.io/foss4g2019/">FOSS4G presentation</a></li>
<li>Wanna try? Follow this <a href="https://neteler.gitlab.io/actinia-introduction/">tutorial</a> for a demo user</li>
<li>Available on <i class="fa fa-github"></i>: <a href="https://github.com/mundialis/actinia_core">https://github.com/mundialis/actinia_core</a></li>
</ul>
<img src="img/ace_actinia_in_grass_session.jpg" class="stretch">
<small>by Markus Neteler, Carmen Tawalika, Anika Weinmann, …</small>
</section>
</section>
<section id="Applications">
<section>
<h1>Application examples</h1>
<h2>GRASS for remote sensing analysis in the cloud</h2>
<br>
<img src="img/lst_reconstruction.png" class="stretch">
<p><small>Daily LST space-time reconstruction done with GRASS - <a href="https://www.mdpi.com/2072-4292/9/12/1333/htm">Metz et al. 2017.</a></small></p>
</section>
<section>
<h2>Germany land-cover mapping based on Sentinel-2 data</h2>
<h6>GRASS modules in use (excerpt):</h6>
<ul>
<b><em><font size="3"><li>i.vi</li>
<li>t.rast.series</li>
<li>r.learn.ml2</li>
<li>r.change.info</li></font></b></em>
</ul>
<br>
<img src="img/incora_germany_2019_incl_subset.png" class="stretch"><br>
<small>For details, follow <a href="https://www.mundialis.de/en/deutschland-2020-landbedeckung-auf-basis-von-sentinel-2-daten/">this</a> blog post.</small>
</section>
<section>
<h2>Forest monitoring</h2>
<h6>GRASS modules in use (excerpt):</h6>
<ul>
<b><em><font size="3"><li>r.mapcalc</li>
<li>r.learn.ml2</li>
<li>r.texture</li>
<li>r.resamp.interp</li></font></b></em>
</ul>
<br>
<img src="img/hermosa1.png" width="49%"> <img src="img/hermosa2.png" width="46%">
<small>Register and try the HERMOSA demo at <a href="https://hermosa.earth/">https://hermosa.earth</a></small>
</section>
<section>
<h2>Flood Mapping in Ecuador based on Sentinel-1 data</h2>
<h6>GRASS modules in use (excerpt):</h6>
<ul>
<b><em><font size="3"><li>r.mapcalc</li>
<li>i.segment</li>
<li>t.rast.algebra</li>
<li>t.rast.series</li></font></b></em>
</ul>
<br>
<img src="img/s1_flood_example.jpg" width="50%"><img src="img/s1_flood_frequency.jpg" width="50%">
<small>For details, follow <a href="https://www.mundialis.de/en/sendai-flood-mapping-in-ecuador-based-on-sentinel-1-data/">this</a> blog post.</small>
</section>
</section>
<section id="Resources">
<section>
<h2>Plenty of resources</h2>
<ul>
<li>
<a href="https://grass.osgeo.org/learn/manuals/">Documentation</a>:
<ul>
<li>See <a href="https://grass.osgeo.org/grass-stable/manuals/graphical_index.html">full list of core tools</a>
<li>See <a href="https://grass.osgeo.org/grass-stable/manuals/addons">tools in Addons repository</a>
</ul>
<li>
<a href="https://grass.osgeo.org/learn/tutorials/">Tutorials and Courses</a>:
<ul>
<li><a href="https://grasswiki.osgeo.org/wiki/From_GRASS_GIS_novice_to_power_user_(workshop_at_FOSS4G_Boston_2017)">Introduction to GRASS GIS</a>
<li><a href="https://grasswiki.osgeo.org/wiki/Processing_lidar_and_UAV_point_clouds_in_GRASS_GIS_(workshop_at_FOSS4G_Boston_2017)">Processing lidar and UAV point clouds</a>
<li><a href="https://training.gismentors.eu/grass-gis-workshop-jena/">GRASS GIS course at Jena</a></li>
<li><a href="http://ncsu-geoforall-lab.github.io/grass-temporal-workshop/">Spatio-temporal data handling and visualization</a>
</ul>
<li>
<a href="https://grass.osgeo.org/learn/books/">Books</a>:
<ul>
<li>Open Source GIS: A GRASS GIS Approach
<li>Tangible Modeling with Open Source GIS
<li>Open Source Approaches to Spatial Data Handling
</ul>
</ul>
</section>
<section>
<h2>Access to Source Code</h2>
Documentation links to the source code.
<img src="img/module_author_source.png" class="stretch">
<p>by Luca Delucchi
</section>
</section>
<section id="Get involved">
<section>
<h1>Get involved! All contributions are welcome!</h1>
<img src="https://grass.osgeo.org/images/news/grass_sprint2018_bonn_fotowall_medium.jpg" class="stretch">
</section>
<section>
<h2>Code contributions</h2>
<br>
<h3>GRASS GIS development is GitHub-centered: core, addons, website</h3>
<ul>
<li>File bug reports or feature requests</li>
<li>All issues and PR's are publicly visible</li>
<li>Ask, comment, suggest also in Github <a href="https://github.com/OSGeo/grass/discussions">Discussions</a></li>
<li><em>"Fork me on <a href="https://github.com/OSGeo/grass">GitHub</a>"</em> and suggest changes or fix bugs via pull requests</li>
<li>Create your own addon! See this nice workshop for a guideline:
<a href="https://github.com/wenzeslaus/python-grass-addon">How to write a Python tool for GRASS</a>
</li>
</ul>
<img src="img/octocat.png" class="stretch">
</section>
<section>
<h2>Other contributions are relevant too!</h2>
<ul>
<li>Translation: we use <a href="https://www.transifex.com/grass-gis/">Transifex</a></li>
<li>Documentation: start by fixing typos in manual pages, add examples where missing, create cool screenshots, write tutorials in the <a href="https://grasswiki.osgeo.org/wiki/GRASS-Wiki">wiki</a>, etc.</li>
<li>Contribute material for our social media <a href="https://twitter.com/GRASSGIS"><i class="fa fa-twitter"></i></a>
<a href="https://www.facebook.com/groups/GRASS"><i class="fa fa-facebook"></i></a>
<a href="https://www.linkedin.com/groups/2718015/"><i class="fa fa-linkedin"></i></a></li>
<li>Write a blog post for our website</li>
<li>Bring your own ideas!</li>
</ul>
</section>
<section>
<h2>Sponsoring</h2>
<div class="columns">
<div class="column" style="width:63%">
<br>
<ul>
<li>Money donations are very important for GRASS GIS development. They allow us to:</li>
<ul>
<li>organize face-to-face coding sessions (sprints)</li>
<li>finance infrastucture needs (web site, etc)</li>
<li>pay developers to implement new features and fix specific important bugs</li>
</ul>
</ul>
</div>
<div class="column" style="width:35%">
<img src="https://grass.osgeo.org/images/other/Grass_osgeo_codesprint_2018.jpg">
</div>
</div>
</section>
<section>
<h2>Sponsoring</h2>
<img src="img/opencollective_page.png" width="40%" style="float:right">
<br><br>
<blockquote>
"One of the greatest benefits of GRASS GIS is that its
environments gives us a plethora of options for manipulating data and