Understanding the spacial reference/How to get latitude and longitude from a .las LiDAR file

Question

I have downloaded some .las files from a LiDAR project listed on the USGS website. I am hoping to process them in Python. I was able to get the set of X,Y, and Z points using the following snippit in the documentation.

import laspy as lp
import numpy as np

las_file = r'lidar.las'
inFile = lp.file.File(las_file)

dataset = np.vstack([inFile.X, inFile.Y, inFile.Z]).transpose() #X, Y, Z data

The problem I was running into is that I didn't understand how to get a subset of the data using Latitude and Longitude coordinates. I have explored the data in the header and I see that the data is scaled by scaling factors but I still was confused how to scale this to a coordinate system that I would expect to see on a map.

>>>inFile.header.min
[504110.62, 4828500.0, 2728.0]
>>>inFile.header.max
[505499.99, 4829999.99, 3142.9900000000002]
>>>inFile.header.scale
[0.01, 0.01, 0.001]

I looked at the information sheet that was also downloaded with the .las file and it included the following information. I think this is trying to tell me how to convert the X,Y,Z data to Latitude,Longitude, and elevation but I didn't understand how to make this transformation in python.

Is there a package or library or custom function that I can implement that can assist me to make the conversion to latitude and longitude coordinates so that I will be able to select points from this LiDAR point cloud that are inside of a polygon defined as a series of latitude/longitude points?

Answer 1

I am sharing what I ended up doing here in case it helps someone else.

I realized that I needed a coordinate transformation tool and I found one that seemed quite lightweight here

To use it on my dataset I did the following:

lat_lon = utm.to_latlon(grid[:,0]*0.01, grid[:,1]*0.01, 12, nothern=True)

This worked well enough for my needs.