Geospatial Data Visualization with Kepler.gl
Kepler.gl is a high-performance visualization tool and it is purely a client-side app. It can be easily used by technical and not technical people for visualization.it also supports the flexibility of 3-D visualization.
Uber made it an open-source in 2018, and its functionality is very impressive. You can easily drag and drop your dataset and tweak it immediately on the web to visualize large scale geospatial datasets with ease.
Method to Upload Dataset:
Kepler.gl supports mainly two types of data
- CSV format data
- GeoJSON format
Data can be uploaded from three different sources.
- Local file
- URL
- Sample data
Let's understand by example…
Let us import the dataset in Jupyter notebook by using the following command.
To import the Kepler tool in the notebook, run the following command given below.
Kepler.gl detect different data types
- Boolean type
- Int type
- Real data types
- GeoJSON
- Date
- Timestamp
- String
Filtering the data:
A filter is used to limit the data that you want to displayed.filtration is possible only on the bases of column names present in the dataset. filter panel display all the existing column names present in the dataset.
Type of filters in keplger.gl
- Time filter
- Range filter
- Single selection
- Multi-selection
- Time playback
Interaction with data:
Tooltip: Tooltip is used to display the metrics when hovering over the data points and choose the fields which you want to display from the tooltip config menu.
Brushing: Brush is used to highlight the area with a cursor. When the brush is turned on, then all layers will be dark and only portion will be illuminated. You hover the portion with the cursor.
Different type of layers:
Point: point layer is used to show the geospatial data location in form of point.to find the pickup and dropoff point only choose the point layer in the Kepler tool. choose the different colors to differentiate the pickup and dropoff points.
Line: The line layer is used to draw the line between two points to find the distance between them. The line layer is the 2-D representation between the two data set points.
Arc: Arc layer is also used to find the distance between two different data set points. The tallest arc represents the largest distance.it is the 3-D visual representation of the line layer.
Grid: The grid is used to show the density of points. It is similar to the heatmap and also shows the visual discrepancy where the multiple heatmap layer styles are present.to find out the 3-D map enables the 3D building option given in the map layer.
Polygon: Polygon layer is generally used to display the GeoJSON features.GeoJSON supports different geometry like Point, LineString, MultiLineString, etc.
Cluster: The cluster layer is used to visualize the aggregate data with different radius based on the geospatial data.
Icon: icon layer is used to represent the data points by different icons.
Hexbin: Hexbin layer is used to display the aggregate metrics such as min/max/avg/ mean/ sum/median of a numeric data.
Save and Export: Save your map as an image, export current map data, export the current map as a JSON file to be loaded back into kepler.gl.
- Export map as an image
- Export filtered or unfiltered data as CSV
- Export Map
- Share Public URL (Dropbox)
Reference: https://kepler.gl/
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