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Learning Geospatial Analysis with Python-Second Edition

You're reading from   Learning Geospatial Analysis with Python-Second Edition An effective guide to geographic information systems and remote sensing analysis using Python 3

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Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Toc

Table of Contents (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python FREE CHAPTER 2. Geospatial Data 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modeling 9. Real-Time Data 10. Putting It All Together Index

Parsing the GPX

Now, we'll parse the GPX file, which is just XML, using the built-in xml.dom.minidom module. We'll extract the latitude, longitude, elevation, and timestamps. We'll store them in a list for later use. The timestamps are converted to struct_time objects using Python's time module, which makes them easier to work with:

# Parse the gpx file and extract the coordinates
log.info("Parsing GPX file: {}".format(gpx))
xml = minidom.parse(gpx)
# Grab all of the "trkpt" elements
trkpts = xml.getElementsByTagName("trkpt")
# Latitude list
lats = []
# Longitude list
lons = []
# Elevation list
elvs = []
# GPX timestamp list
times = []
# Parse lat/long, elevation and times
for trkpt in trkpts:
    # Latitude
    lat = float(trkpt.attributes["lat"].value)
    # Longitude
    lon = float(trkpt.attributes["lon"].value)
    lats.append(lat)
    lons.append(lon)
    # Elevation
    elv = trkpt.childNodes[0].firstChild.nodeValue...
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