kibana/docs/maps/indexing-geojson-data-tutorial.asciidoc

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[[indexing-geojson-data-tutorial]]
== Indexing GeoJSON data tutorial

In this tutorial, you'll build a customized map that shows the flight path between 
two airports, and the lightning hot spots on that route. You'll learn to:

* Import GeoJSON files into Kibana
* Index the files in {es}
* Display the data in a multi-layer map

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=== Before you begin

This tutorial requires you to download the following GeoJSON sample data files.
These files are good examples of the types
of vector data that you can upload to Kibana and index in
Elasticsearch for display in *Elastic Maps*. 

* https://raw.githubusercontent.com/elastic/examples/master/Maps/Getting%20Started%20Examples/geojson_upload_and_styling/logan_international_airport.geojson[Logan International Airport]
* https://raw.githubusercontent.com/elastic/examples/master/Maps/Getting%20Started%20Examples/geojson_upload_and_styling/bangor_international_airport.geojson[Bangor International Airport]
* https://raw.githubusercontent.com/elastic/examples/master/Maps/Getting%20Started%20Examples/geojson_upload_and_styling/lightning_detected.geojson[Lightning detected]
* https://raw.githubusercontent.com/elastic/examples/master/Maps/Getting%20Started%20Examples/geojson_upload_and_styling/original_flight_path.geojson[Original flight path]
* https://raw.githubusercontent.com/elastic/examples/master/Maps/Getting%20Started%20Examples/geojson_upload_and_styling/modified_flight_path.geojson[Modified flight path]

The data represents two real airports, two fictitious flight routes, and 
fictitious lightning reports. You don't need to use all of
these files. Feel free to work with as many files as you'd like, or use valid GeoJSON
files of your own.

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=== Create and set up a map

. <<maps-create, Create a new map>>.
. Zoom in on the New England area in the northeast United States.
+
You're adding flight paths to this area, and this
sets up the map for a good view of the data.
+
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image::maps/images/fu_gs_new_england_map.png[]

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[[upload-and-index-geojson-file]]
=== Upload and index GeoJSON files
For each GeoJSON file you downloaded, complete the following steps:

. Below the map legend, click *Add layer*.
. From the list of layer types, click *Upload GeoJSON vector file*.
. Using the File Picker, upload the GeoJSON file.
+
Depending on the geometry type of your features, this will 
auto-populate *Index type* with either {ref}/geo-point.html[geo_point] or
 {ref}/geo-shape.html[geo_shape] and *Index name* with 
`<file name>`.

. Click *Import file* in the lower right.
+
You'll see activity as the GeoJSON Upload utility creates a new index
and index pattern for the data set. When the process is complete, you should
receive messages that the creation of the new index and index pattern
were successful. 

. Click *Add layer* in the bottom right.

. In *Layer settings*, adjust settings and <<maps-vector-style-properties, properties>> as needed.
. Click *Save & close*.
. Once you've added all of the sample files,
<<maps-save, save your map>>.
+
At this point, you could consider the map complete, 
but there are a few additions and tweaks that you can make to tell a
better story with your data.
+
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image::maps/images/fu_gs_flight_paths.png[]

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=== Add a heatmap aggregation layer

Looking at the `Lightning detected` layer, it's clear where lightning has
struck. What's less clear, is if there have been more lightning 
strikes in some areas than others, in other words, where the lightning 
hot spots are. An advantage of having indexed
{ref}/geo-point.html[geo_point] data for the 
lightning strikes is that you can perform aggregations on the data. 

. Below the map legend, click *Add layer*.
. From the list of layer types, click *Grid aggregation*.
+
Because you indexed `lightning_detected.geojson` using the index name and 
pattern `lightning_detected`, that data is available as a {ref}/geo-point.html[geo_point]
aggregation. 

. Select `lightning_detected`.
. Click *Show as* and select `heat map`.
. Click *Add layer* to add the heat map layer
"Lightning intensity".
+
The remaining default settings are good, but there are a couple of
settings that you might want to change. 

. Under *Source settings* > *Grid resolution*, select from the different heat map resolutions. 
+
The default "Coarse" looks
good, but feel free to select a different resolution.

. Play around with the *Layer Style* >
*Color range* setting. 
+
Again the default looks good, but feel free to choose a
different color range.

. When you're finished modifying settings, click *Save & close*.
+
With your new lightning heat map layer, your map should look
like this:
+
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image::maps/images/fu_gs_lightning_intensity.png[]


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=== Organize the layers

Consider ways you might improve the appearance of the final map.
Small changes in how and when layers are shown can help tell a 
better story with your data. Here are a few final tweaks
you might make:

* Update layer names
* Adjust styles for each layer
* Adjust the layer order
* Decide which layers to show at different zoom levels 

When you've finished, again be sure to <<maps-save, save your work >>.

Your final map might look like this:

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image::maps/images/fu_gs_final_map.png[]