41 Working with KML data

KML is a file format used to display geographic data in an Earth browser such as Google Earth. KML uses a tag-based structure with nested elements and attributes and is based on the XML standard.

Source: https://developers.google.com/kml/documentation/kml_tut

Set File Paths and download Tutorial Data

If you downloaded the latest GemGIS version from the Github repository, append the path so that the package can be imported successfully. Otherwise, it is recommended to install GemGIS via pip install gemgis and import GemGIS using import gemgis as gg. In addition, the file path to the folder where the data is being stored is set. The tutorial data is downloaded using Pooch (https://www.fatiando.org/pooch/latest/index.html) and stored in the specified folder. Use pip install pooch if Pooch is not installed on your system yet.

import gemgis as gg

file_path ='data/41_working_with_kml_data/'

WARNING (theano.configdefaults): g++ not available, if using conda: `conda install m2w64-toolchain`
C:\Users\ale93371\Anaconda3\envs\test_gempy\lib\site-packages\theano\configdefaults.py:560: UserWarning: DeprecationWarning: there is no c++ compiler.This is deprecated and with Theano 0.11 a c++ compiler will be mandatory
  warnings.warn("DeprecationWarning: there is no c++ compiler."
WARNING (theano.configdefaults): g++ not detected ! Theano will be unable to execute optimized C-implementations (for both CPU and GPU) and will default to Python implementations. Performance will be severely degraded. To remove this warning, set Theano flags cxx to an empty string.
WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions.

gg.download_gemgis_data.download_tutorial_data(filename="41_working_with_kml_data.zip", dirpath=file_path)

Downloading file '41_working_with_kml_data.zip' from 'https://rwth-aachen.sciebo.de/s/AfXRsZywYDbUF34/download?path=%2F41_working_with_kml_data.zip' to 'C:\Users\ale93371\Documents\gemgis\docs\getting_started\tutorial\data\41_working_with_kml_data'.

Loading the data

The data used for demonstration purposes here was downloaded from https://developers.google.com/kml/documentation/KML_Samples.kml. The different layers the KML consists of can be listed using fionas listlayers(...) function. When using GeoPandas, the KML driver has to be activated using gpd.io.file.fiona.drvsupport.supported_drivers['KML'] = 'rw'. When loading a layer with GeoPandas, the driver needs to be provided as well as the layer name. If no layer is provided, only the first element will be loaded.

import geopandas as gpd
import fiona

gpd.io.file.fiona.drvsupport.supported_drivers['KML'] = 'rw'

layer_list = fiona.listlayers(file_path + 'KML_Samples.kml')
layer_list

['Placemarks',
 'Highlighted Icon',
 'Paths',
 'Google Campus',
 'Extruded Polygon',
 'Absolute and Relative']

Loading Placemarks

gdf_placemarks = gpd.read_file(filename=file_path+'KML_Samples.kml', driver='KML' , layer='Placemarks')
gdf_placemarks

	Name	Description	geometry
0	Simple placemark	Attached to the ground. Intelligently places i...	POINT Z (-122.08220 37.42229 0.00000)
1	Floating placemark	Floats a defined distance above the ground.	POINT Z (-122.08407 37.42200 50.00000)
2	Extruded placemark	Tethered to the ground by a customizable "tail"	POINT Z (-122.08577 37.42157 50.00000)

Loading Icon

gdf_highlight = gpd.read_file(filename=file_path+'KML_Samples.kml', driver='KML' , layer='Highlighted Icon')
gdf_highlight

	Name	Description	geometry
0	Roll over this icon		POINT Z (-122.08565 37.42243 0.00000)

Loading Paths

gdf_paths = gpd.read_file(filename=file_path+'KML_Samples.kml', driver='KML' , layer='Paths')
gdf_paths

	Name	Description	geometry
0	Tessellated	If the <tessellate> tag has a value of 1, the ...	LINESTRING Z (-112.08142 36.10678 0.00000, -11...
1	Untessellated	If the <tessellate> tag has a value of 0, the ...	LINESTRING Z (-112.08062 36.10673 0.00000, -11...
2	Absolute	Transparent purple line	LINESTRING Z (-112.26565 36.09448 2357.00000, ...
3	Absolute Extruded	Transparent green wall with yellow outlines	LINESTRING Z (-112.25508 36.07955 2357.00000, ...
4	Relative	Black line (10 pixels wide), height tracks ter...	LINESTRING Z (-112.25328 36.09887 645.00000, -...
5	Relative Extruded	Opaque blue walls with red outline, height tra...	LINESTRING Z (-112.26566 36.09445 630.00000, -...

Loading Google Campus

gdf_campus = gpd.read_file(filename=file_path+'KML_Samples.kml', driver='KML' , layer='Google Campus')
gdf_campus

	Name	Description	geometry
0	Building 40		POLYGON Z ((-122.08489 37.42257 17.00000, -122...
1	Building 41		POLYGON Z ((-122.08574 37.42227 17.00000, -122...
2	Building 42		POLYGON Z ((-122.08579 37.42136 25.00000, -122...
3	Building 43		POLYGON Z ((-122.08444 37.42177 19.00000, -122...

Loading Polygon

gdf_polygon = gpd.read_file(filename=file_path+'KML_Samples.kml', driver='KML' , layer='Extruded Polygon')
gdf_polygon

	Name	Description	geometry
0	The Pentagon		POLYGON Z ((-77.05788 38.87253 100.00000, -77....

Loading Absolute and Relative

gdf_absolute = gpd.read_file(filename=file_path+'KML_Samples.kml', driver='KML' , layer='Absolute and Relative')
gdf_absolute

	Name	Description	geometry
0	Absolute		POLYGON Z ((-112.33725 36.14889 1784.00000, -1...
1	Absolute Extruded		POLYGON Z ((-112.33966 36.14638 1784.00000, -1...
2	Relative		POLYGON Z ((-112.33495 36.14989 100.00000, -11...
3	Relative Extruded		POLYGON Z ((-112.33488 36.15140 100.00000, -11...

Plotting the Data

The data was just simply plotted to visualize the content of the KML file.

import matplotlib.pyplot as plt

gdf_placemarks.plot(aspect='equal')
plt.grid()

gdf_highlight.plot(aspect='equal')
plt.grid()

gdf_paths.plot(aspect='equal')
plt.grid()

gdf_campus.plot(aspect='equal')
plt.grid()

gdf_polygon.plot(aspect='equal')
plt.grid()

gdf_absolute.plot(aspect='equal')
plt.grid()