While this is a very simple example, visualization is a crucial aspect of working with geospatial data. Once your errata are verified, your submission will be accepted and the errata will be uploaded on our website, or added to any list of existing errata, under the Errata section of that title. He has worked in academia, government, and natural resources but now mainly consults for the start-up community in Silicon Valley. Additional attributes such as temperature, soil type, height, or the name of a landmark are also often present. This is a great resource for anyone wishing to advance their skills in Geospatial programming using Python. In recent years, Erik has been involved in the design and implementation of systems matching seekers with providers of goods and services across a range of geographical areas, as well as real-time messaging, payment, and identity systems.
Python Geospatial Development teaches you everything you need to know about writing geospatial applications using Python. Please note that this is not a tutorial on how to use the Python language; Python is easy to learn, but the details are beyond the scope of this book. Since geographical data can be expensive another chapter describes freely available data on the Internet, making it possible for a Python developer to test geospatial coding without having to spend too much money to buy data. We'll learn more about this in the next chapter. Code words in text are shown as follows: The pyproj Geod class allows you to perform various geodetic calculations based on points on the Earth's surface. If you find a mistake in one of our books—maybe a mistake in the text or the code—we would be grateful if you would report this to us. While the Python language itself makes programming quick and easy, allowing you to focus on the task at hand, the Python Standard Libraries make programming even more efficient.
Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book. Errata Although we have taken every care to ensure the accuracy of our content, mistakes do happen. We then examine a number of Python libraries and use these with freely-available geospatial data to accomplish a variety of tasks. The results would be a series of timestamps, latitude and longitude values as follows: 2010-03-21 9:15:23 -38. Finally, geospatial data by itself is not very interesting. Python has been used to write web-based systems, desktop applications, games, scientific programming, and even utilities and other higher-level parts of various operating systems. Questions You can contact us at if you are having a problem with any aspect of the book, and we will do our best to address it.
There can be many thousands or even millions of data points for a single set of geospatial data. Here, you can access, read and search across Packt's entire library of books. Uniquely amongst the major publishers, we seek to develop and publish the broadest range of learning and information products on each technology. This work has included the creation of real-time geocoders and map-based views of constantly changing data. Customer support Now that you are the proud owner of a Packt book, we have a number of things to help you to get the most from your purchase. This can include, for example, the position of a cell phone tower, the shape of a road, or the outline of a country: Geospatial data often associates some piece of information with a particular location. A long list of coordinates tells you almost nothing; it isn't until those numbers are used to draw a picture that you can make sense of it.
What is more, everything ran on the desktop—the concept of working with geospatial data across the Internet was no more than a distant dream. I have a feeling that it is mainly a list of a number of libraries and technologies, and some examples, and that it is a bit light on strong opinions and recommendations. While Python is generally considered to be an interpreted language, and is occasionally criticized for being slow compared to compiled languages such as C, the use of byte-compilation and the fact that much of the heavy lifting is done by library code means that Python's performance is often surprisingly good. The book guides you through the process of installing and using various toolkits, obtaining geospatial data for use in your programs, and building complete and sophisticated geospatial applications in Python. However, Packt Publishing cannot guarantee the accuracy of this information.
Since Python is a powerful programming language with high-level toolkits, it is well-suited to geospatial development. Who this book is for Experienced Python developers who want to learn about geospatial concepts, work with geospatial data, solve spatial problems, and build map-based applications. It investigates the performance of this application and then works to optimize it using best-practice techniques. Just like a distance value of 2. Open source tools, where they were available, were obscure and hard to use. However, the information contained in this book is sold without warranty, either express or implied. Note These latitude and longitude values are in decimal degrees.
It's a bit hard for me to judge how good this book is for people without my experience though. Reader feedback is important for us to develop titles that you really get the most out of. Programming in Python is straightforward, efficient, and, dare I say it, fun. One of the first things a developer notices about Python compared with other languages such as Java or C++ is how expressive the language is: what may take 20 or 30 lines of code in Java can often be written in half a dozen lines of code in Python. By the end of the book, you will be able to integrate spatial features into your applications and build a complete mapping application from scratch. It is often used as a scripting language, automating and simplifying tasks at the operating system level, but it is equally suitable for building large and complex programs.
We appreciate your help in protecting our authors, and our ability to bring you valuable content. Conventions In this book, you will find a number of styles of text that distinguish between different kinds of information. To compare or combine two sets of geospatial data, it is often necessary to convert the data from one projection to another. Here are some examples of these styles, and an explanation of their meaning. Python is eminently suitable for all sorts of programming, from quick one-off scripts to building huge and complex systems. For this reason, we won't be using Python 3 in this book.