55 lidar

LiDAR data analysis and visualization with whitebox and leafmap

Create a new conda env to install required packages:

conda create -n geo python
conda activate geo
conda install -c conda-forge mamba
mamba install -c conda-forge pygis
pip install laspy[lazrs]

Uncomment the following line to install packages in Google Colab.

In [1]:

# !pip install leafmap

# !pip install leafmap

In [2]:

# !pip install laspy[lazrs]

# !pip install laspy[lazrs]

Import libraries¶

In [3]:

import os
import leafmap
import whitebox

import os import leafmap import whitebox

Set up whitebox¶

In [4]:

wbt = whitebox.WhiteboxTools()
wbt.set_working_dir(os.getcwd())
wbt.set_verbose_mode(False)

wbt = whitebox.WhiteboxTools() wbt.set_working_dir(os.getcwd()) wbt.set_verbose_mode(False)

Out[4]:

0

Download sample data¶

In [5]:

url = 'https://open.gishub.org/data/lidar/madison.zip'
filename = 'madison.las'

url = 'https://open.gishub.org/data/lidar/madison.zip' filename = 'madison.las'

In [6]:

leafmap.download_file(url, 'madison.zip', unzip=True)

leafmap.download_file(url, 'madison.zip', unzip=True)

madison.zip already exists. Skip downloading. Set overwrite=True to overwrite.

Out[6]:

'/home/runner/work/leafmap/leafmap/docs/notebooks/madison.zip'

Read LAS/LAZ data¶

In [7]:

laz = leafmap.read_lidar(filename)

laz = leafmap.read_lidar(filename)

In [8]:

laz

laz

Out[8]:

<LasData(1.3, point fmt: <PointFormat(1, 0 bytes of extra dims)>, 4068294 points, 2 vlrs)>

In [9]:

str(laz.header.version)

str(laz.header.version)

Out[9]:

'1.3'

Upgrade file version¶

In [10]:

las = leafmap.convert_lidar(laz, file_version='1.4')

las = leafmap.convert_lidar(laz, file_version='1.4')

In [11]:

str(las.header.version)

str(las.header.version)

Out[11]:

'1.4'

Write LAS data¶

In [12]:

leafmap.write_lidar(las, 'madison.las')

leafmap.write_lidar(las, 'madison.las')

Histogram analysis¶

In [13]:

wbt.lidar_histogram('madison.las', 'histogram.html')

wbt.lidar_histogram('madison.las', 'histogram.html')

Out[13]:

0

Visualize LiDAR data¶

In [14]:

leafmap.view_lidar('madison.las')

leafmap.view_lidar('madison.las')

Remove outliers¶

In [15]:

wbt.lidar_elevation_slice("madison.las", "madison_rm.las", minz=0, maxz=450)

wbt.lidar_elevation_slice("madison.las", "madison_rm.las", minz=0, maxz=450)

Out[15]:

0

Visualize LiDAR data after removing outliers¶

In [16]:

leafmap.view_lidar('madison_rm.las', cmap='terrain')

leafmap.view_lidar('madison_rm.las', cmap='terrain')

Create DSM¶

In [17]:

wbt.lidar_digital_surface_model(
    'madison_rm.las', 'dsm.tif', resolution=1.0, minz=0, maxz=450
)

wbt.lidar_digital_surface_model( 'madison_rm.las', 'dsm.tif', resolution=1.0, minz=0, maxz=450 )

Out[17]:

0

In [18]:

leafmap.add_crs("dsm.tif", epsg=2255)

leafmap.add_crs("dsm.tif", epsg=2255)

Visualize DSM¶

In [19]:

m = leafmap.Map()
m.add_raster('dsm.tif', palette='terrain', layer_name='DSM')
m

m = leafmap.Map() m.add_raster('dsm.tif', palette='terrain', layer_name='DSM') m

Out[19]:

Create DEM¶

In [20]:

wbt.remove_off_terrain_objects('dsm.tif', 'dem.tif', filter=25, slope=15.0)

wbt.remove_off_terrain_objects('dsm.tif', 'dem.tif', filter=25, slope=15.0)

Out[20]:

0

Visualize DEM¶

In [21]:

m.add_raster('dem.tif', palette='terrain', layer_name='DEM')
m

m.add_raster('dem.tif', palette='terrain', layer_name='DEM') m

Out[21]:

Create CHM¶

In [22]:

chm = wbt.subtract('dsm.tif', 'dem.tif', 'chm.tif')

chm = wbt.subtract('dsm.tif', 'dem.tif', 'chm.tif')

In [23]:

m.add_raster('chm.tif', palette='gist_earth', layer_name='CHM')
m

m.add_raster('chm.tif', palette='gist_earth', layer_name='CHM') m

Out[23]:

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Last update: 2023-09-22
Created: 2023-09-22