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The First #Ecological Land Units #Map of the World | #opendata #dataviz

The First #Ecological Land Units #Map of the World | #opendata #dataviz | Public Datasets - Open Data - | Scoop.it
luiy's insight:

This map as well as the data layers used to create it can be explored in a new story map that introduces ecological land units. The data is available in the form of services and can enrich any GIS effort.

 

The collaborative partnership between Esri and USGS resulted in a dynamic online map representing the world’s ecological diversity at unprecedented detail and authority. This work leveraged quantitative methods, geographic science, and big data produced by government agencies and the scientific community.  To create this map the data were processed in Esri’s ArcGIS cloud computing environment. This map provides new knowledge and understanding of geographic patterns and relationships by distinguishing the geography of the planets’ ecosystems.

- See more at: http://blogs.esri.com/esri/esri-insider/2014/12/09/the-first-detailed-ecological-land-unitsmap-in-the-world/#sthash.Fm99R5lg.dpuf

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Mapping Data: A guide for making #geodata visualizations | #ddj #methods #tools

Mapping Data: A guide for making #geodata visualizations | #ddj #methods #tools | Public Datasets - Open Data - | Scoop.it
luiy's insight:

As an add-on to our presentation we produced two more things, that some of you out there mind find helpful too:

 

- Mappable Toolset: The number of tools to process data, make maps, interactive visualizations etc. is continuously growing. While we love new tools, this leads to a situation that makes it quite hard to keep an overview of which tools are good for a certain tasks, where to find them and how much they cost. To keep track of the tools we've used so far and as a guide for others we thus collected our toolset. Have a look at it here:English version, German version.


-  Mappable Cheat-Sheet: Making maps and other visualizations with a geospatial component is certainly not a trivial tasks. There are many pitfalls, take alone spatial reference systems as an example, that might completely mess up your visualization if you don't handle them correctly. We thus created a checklist for making geodata visualizations in (data-driven) journalism. You can find it here: English version, German version.

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