The lidar method conveys another yet complex level of data visualization as it is widely used in demanding industries that require to plot, e.g., topographic or cartography 3D data.
But the use of Lidar goes further as it is also used for navigation monitoring of vehicles autonomy and spatial exploration.
By now, you may already have an idea of how Lidar data visualization may look like, and understanding how new state-of-the-art technologies are improving the way Lidar data is visualized in 2021.
So, what is lidar data visualization? Lidar data visualization is the method of exploration and analysis of different landscapes being represented as 3D dynamically colored visualizations.
Lidar data visualization
Analyzing and visualizing Lidar data is complex as it involves large data sets that require advanced data visualization solutions capable of rendering millions of data points and in some cases, billions.
The need for data visualization solutions comes from the nature of the data which involves more complex sources that require optimal UI interactions which can support a clear understanding of the visualizations.
Understanding and analyze a visualization of Lidar requires identifying any human-made or naturally caused errors.
As the Lidar data analysis continues, it becomes more difficult to discern from the real objects of interest from those that are not.
Objects that are not the main focus of the analysis only add irrelevant noise. Moreover, it becomes more difficult to understand the analysis when the amount of data points rendered is extremely low, which happens when using low-performance charting solutions.
For instance, think about a land field visualization that has been downsampled that (inevitably) includes surrounding vegetation, which is not of the research interest.
It is then necessary to be able to manipulate the lidar data visualization with high-performing UI interactions, e.g., panning and zooming, in order to isolate only the features of interest within the plot.
The next image shows the visualization of a 7.5km x 7.5km area in London, with an accuracy of 2m. This chart visualizes 56 million data points, which additionally involves highly precise interactions such as real-time zooming.
We’ve seen how the complexity of Lidar visualizations. Lidar is used in the world’s most demanding industries that need to visualize not only 2D data but also 3D.
Lidar is also used for agriculture for collecting and visualizing data points from the agricultural procedures.
Autonomous vehicles application
Macro corporations such as Tesla have been exhaustively developing autonomous technology and implement it within smart vehicles.
The importance of Lidar in this field is therefore vital. Lidar data helps to improve the way autonomous vehicles recognize road obstacles and how smart vehicles navigate within different streets, roads, highways, terrains, etc.
Physics for observatories application
Lidar is commonly used within observatories around the world. The reason why Lidar is used in observatories relies on being an effective method to measure certain variables.
A common variable measured with Lidar is the distance that exists between the light of a laser that hits a certain object situated up in the sky.
Lidar also helps to measure the time it takes for the laser light to come back after hitting the object.
That’s how observatories can perform Lunar Laser Ranging experiments and measure the variable distances between triggered lights and reflectors situated on the moon.
Lunar Laser Ranging Experiment from the Apollo 11 mission. Source
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