Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
Arrow right icon
View More author details
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

Elevation data

A Digital Elevation Model (DEM) is a three-dimensional representation of a planet's terrain. In the context of this book, this planet is the Earth. The history of digital elevation models is far less complicated than remotely-sensed imagery but no less significant. Before computers, representations of elevation data were limited to topographic maps created through traditional land surveys. Technology existed to create three-dimensional models from stereoscopic images or physical models from materials such as clay or wood, but these approaches were not widely used for geography.

The concept of digital elevation models began in 1986 when the French space agency, Centre national d'études spatiales (CNES), launched its SPOT-1 satellite, which included a stereoscopic radar. This system created the first usable DEM. Several other U.S. and European satellites followed this model with similar missions. In February, 2000, the Space Shuttle Endeavour conducted the Shuttle Radar Topography Mission (SRTM), which collected elevation data over 80% of the Earth's surface using a special radar antenna configuration that allowed a single pass. This model was surpassed in 2009 by the joint U.S. and Japanese mission using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor aboard NASA's Terra satellite. This system captured 99% of the Earth's surface but has proven to have minor data issues. As the Space Shuttle's orbit did not cross the Earth's poles, it did not capture the entire surface. SRTM remains the gold standard. The following image from the USGS shows a colorized DEM known as a hillshade. Greener areas are lower elevations while yellow and brown areas are mid-range to high elevations:

Elevation data

Recently, more ambitious attempts at a worldwide elevation dataset are underway in the form of TerraSAR-X and TanDEM-X satellites launched by Germany in 2007 and 2010, respectively. These two radar elevation satellites worked together to produce a global DEM called WorldDEM that was released on April 15, 2014. This dataset has a relative accuracy of two meters and an absolute accuracy of four meters.

You have been reading a chapter from
Learning Geospatial Analysis with Python-Second Edition
Published in: Dec 2015
Publisher: Packt
ISBN-13: 9781783552429
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime