LiDAR Survey Data Processing and Rendering: Tree Canopy Analysis in MapInfo Pro and ProRaster
In MapInfo Pro 2021 Advanced there is a “Tree Canopy Analysis” tool that you can use to process LiDAR survey data in LAS or LAZ file format. The tool will compute vegetation height, density, and coverage. It is not limited to processing vegetation – you can also use it to examine building heights or powerline height, for example. The tool is very easy to use, but to get you started a video demonstration might help.
The first video (below) demonstrates the use of this tool in MapInfo Pro.
I demonstrate how to use the Tree Canopy Analysis tools in MapInfo Pro 2021. To access these tools you will require the raster processing plug-in (MapInfo Pro Advanced).
With these tools, you can generate rasters of tree canopy height, density, and coverage from classified LiDAR survey data. You can also apply these tools to other classified features like buildings or power lines.
Starting with LiDAR survey data in one or more files in LAS or LAZ format, you can easily generate rasters that measure the height of the vegetation canopy above the ground surface in a single step and with minimal user interaction. There is no limit on the number of returns you can process, nor is there any limit on the size of the output raster. Generating tree canopy coverage and density rasters is also a simple one-step process, and I provide some tips on balancing performance and output data quality.
The second video (below) shows you how to render the raster products (DTM, Canopy Height, Canopy Density, and Canopy Coverage in ProRaster.
I demonstrate how to use ProRaster to render the Tree Canopy Height, Density, and Coverage rasters that I generated using MapInfo Pro Advanced in the previous video.
Firstly, I show how to create an algorithm for the LiDAR-derived terrain and bathymetry rasters, using an atlas-style color table that also maps elevation to color.
Then, I build an algorithm for the Height raster and drape it on the high-resolution DTM. I discuss interpolation techniques and the “valid cell by component” rule and then look at simple ways to transform the height data to color.
I use clipping to focus on the data I am interested in rendering and go looking for the tallest tree on the Central Coast.
Then, I build a multi-layered algorithm containing topographic map sheets draped on terrain underneath the tree canopy height layer.
I demonstrate how to use transparency between layers and then how to use transparency modulation to blend the topographic imagery with the height raster smoothly.
Finally, I introduce the concept of using the Density raster as the source for the opacity modulation to examine the correlation between tree height and vegetation density. Using these algorithms, I explore the bushfire risk that properties on the central coast face. Combining the terrain slope with the canopy height and density can lead to insights into the likelihood of crown fires in the vicinity of homes and other infrastructure.