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terrai-gbif/README.md

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#### Optional Prerequisites
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Do the following steps if you will want to run the GeoServer map server and WMS itself in your local PC or an external online server. For more information, see GeoServer's [installation](http://docs.geoserver.org/stable/en/user/installation/win_installer.html) instructions.
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Do the following steps if you will want to run the GeoServer map server and WMS itself in your local PC or an external online server. GeoServer has various installation methods for different OS platforms in this [link](http://docs.geoserver.org/stable/en/user/installation/win_installer.html) instructions.
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(GeoServer + Apache Tomcat 8.5)
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For this project, we installed GeoServer with Apache Tomcat. More of its installation methods can be read from [here](https://geoserver.geo-solutions.it/edu/en/install_run/gs_install.html).
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1. Install [GeoServer](http://geoserver.org/) locally in your machine or in your online server.
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2. Create a workspace in GeoServer named `terrai-gbif`.
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- Type the following for the *Namespace URI:* <br>`<PROJECT_NAME>.azurewebsites.net/geoserver/terrai-gbif`
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- Check the *Set as Default Workspace* checkbox
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3. Upload GeoServer styles for rasters from `sld-styles`, using their filenames as names for the styles themselves. Use the `terrai-gbif` for workspace.
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- terrai-base.sld
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- terrai-species.sld
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- terra-add.sld
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4. Upload the Geotiff files as **GeoTIFF Data Store**. For more information, see [Creating Geotiff Data Stores](https://geoserver.geo-solutions.it/edu/en/adding_data/add_geotiff.html).
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- Upload the GeoTiff files via FTP to <br> `/site/wwwroot/bin/apache-tomcat-8.5.24/webapps/geoserver/data/data/raster/`
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podocarpus_salignus.tif
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prumnopitys_andina.tif => p_andina.tif
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5. Change the following lines from `js/map.js`to enable reading rasters from the local GeoServer. Change `ONLINE: true` to `ONLINE: false`:
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5. Apply the uploaded *.sld styles* to the GeoTiffs. This can be accessed by setting the **Default Style** in the _**Publishing**_ tab. Detailed instructions can be read in the [publishing tutorial](http://docs.geoserver.org/latest/en/user/gettingstarted/shapefile-quickstart/index.html) tutorial. Set the following sld styles to their corresponding GeoTiffs:
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- `terrai-base.sld` = asia_Terra-I_resampled_fromedit, latin_terra_I_resamp_fromedit
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- `terra-add` = all rasters ending in \***\__add**_
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- `terrai-species` = the rest of the rasters
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6. Change the following lines from `js/map.js`to enable reading rasters from the local GeoServer. Change `ONLINE: true` to `ONLINE: false`:
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const SETTINGS = {
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// flag to use the online or local maps GeoServer

terrai-gbif/git-export.bat

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::---------------------------------------------------------------------
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:: A windows executable batch file that exports (checkout-index) the
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:: current HEAD of a git repository to a specified directory.
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:: - Uses relative directory access in case full path is not supplied.
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:: - Exports contents to an "/export" directory inside the repository if no
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:: argument is supplied
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:: - Creates the entered directory if it does not yet exist
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:: Dependencies: GitBash
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:: madbarua;20180920
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::---------------------------------------------------------------------
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@echo off
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:: Clear the input variable
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set "export_path="
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:: Get the user-input directory path or name
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set /p export_path="Enter the full directory path or internal folder on which to export:"
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if "%export_path%" == "" set export_path="./export/
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GOTO GitExport
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:GitExport
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if exist %export_path% (
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:: Check if full path (path contains ":")
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If NOT "%export_path%"=="%export_path::=%" (
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git checkout-index -f -a --prefix=%export_path%/
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) else (
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:: Export the current HEAD to specified internal relative path
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git checkout-index -f -a --prefix=./%export_path%/
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)
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echo Exporting HEAD contents to: %export_path%
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GOTO End
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) else (
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:: Create directory
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echo Creating directory %export_path%...
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mkdir %export_path%
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GOTO GitExport
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)
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:End
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set "export_path="
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pause;

terrai-gbif/index.html

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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
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<meta name="description" content="Here we present a methodology and a prototype tool powered by machine learning algorithms that allows for near real time threat (and loss) monitoring of vulnerable plant species, using open data (ground-truthed and remotely sensed). Improvements in machine learning algorithms and access to high quality remotely sensed data (top down) has enabled “remote” monitoring of the earth’s status. The applicability of insights obtained can be further improved by incorporating ground truthed (bottom up) data. The proposed tool leverages upon the ease at which one can access GBIF’s high quality spatialized data in a standardized format at scale, further augments this with remote sensing data and machine learning algorithms in order to monitor threat status of plant species. This tool mashes multiple datasets, merges geospatial layers, to generate new insights, and provides a new use case of open data, further supporting the call for FAIR (Findable, Accessible, Interoperable and Reusable) data. Biodiversity monitoring is central to Sustainable Development Agenda, we propose to use this case-study as an example to promote spatialization and FAIR access of national biodiversity records currently held by various government agencies.">
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<meta name="keywords" content="ciat, gbif, terrai-i, "/>
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<meta name="keywords" content="ciat, gbif, terrai, terra-i, earth observation data, big data, analytics, bda, ecological diversity "/>
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<meta name="author" content="CIAT, d.burra@cgiar.org, l.reymondin@cgiar.org, l.palao@cgiar.org, m.barua@cgiar.org, ciatph">
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<link rel="icon" href="images/icons/ciat-icon-48.ico">
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