Lidar data visualization: Difference between revisions

From wikiluntti
Line 23: Line 23:


[[https://github.com/grantbrown/laspy Laspy Github]] [[https://pypi.org/project/laspy/ LasPy]]
[[https://github.com/grantbrown/laspy Laspy Github]] [[https://pypi.org/project/laspy/ LasPy]]
<syntaxhighlight lang="python">
las = pylas.read( fname )
#np.all(las.user_data == las['user_data'])
point_format = las.point_format
print( point_format )
print( point_format.id )
print( list(point_format.dimension_names) )
from mpl_toolkits import mplot3d
import matplotlib.pyplot as plt
fig = plt.figure()
ax = plt.axes(projection='3d')
N=5000
ax.scatter3D(las.X[:N], las.Y[:N], las.Z[:N], c=las.Z[:N], cmap='Greens');
</syntaxhighlight>


=== Interpolate Lidar Data ===
=== Interpolate Lidar Data ===


[[https://jblindsay.github.io/ghrg/WhiteboxTools/interpolate_lidar.html]]
[[https://jblindsay.github.io/ghrg/WhiteboxTools/interpolate_lidar.html]]

Revision as of 11:09, 30 January 2021

Introduction

Use Lidar data, post analyze it with Python/ Pandas? and use Blender to visualize it.

Theory

The free Lidar data set are available e.g. at Opentopography.org. We use both, the Tif data and LAS data of IT-Ren, Fluxnet site

LAS File Format

LAS@Wikipedia how to print lidar file format las

a) Headers.

b) VLR: Variable Length Record. Include 1) header and 2) payload.

c) Point records. Different point formats 0-10.

LAS in Python

[PyLAS Github]

[Laspy Github] [LasPy]


las = pylas.read( fname )
#np.all(las.user_data == las['user_data'])

point_format = las.point_format
print( point_format )
print( point_format.id )
print( list(point_format.dimension_names) )

from mpl_toolkits import mplot3d
import matplotlib.pyplot as plt
fig = plt.figure()
ax = plt.axes(projection='3d')

N=5000
ax.scatter3D(las.X[:N], las.Y[:N], las.Z[:N], c=las.Z[:N], cmap='Greens');

Interpolate Lidar Data

[[1]]