Book Image

Learning Geospatial Analysis with Python - Fourth Edition

By : Joel Lawhead
4 (1)
Book Image

Learning Geospatial Analysis with Python - Fourth Edition

4 (1)
By: Joel Lawhead

Overview of this book

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. In this special 10th anniversary edition, you'll embark on an exhilarating geospatial analysis adventure using Python. This fourth edition starts with the fundamental concepts, enhancing your expertise in geospatial analysis processes with the help of illustrations, basic formulas, and pseudocode for real-world applications. As you progress, you’ll explore the vast and intricate geospatial technology ecosystem, featuring thousands of software libraries and packages, each offering unique capabilities and insights. This book also explores practical Python GIS geospatial applications, remote sensing data, elevation data, and the dynamic world of geospatial modeling. It emphasizes the predictive and decision-making potential of geospatial technology, allowing you to visualize complex natural world concepts, such as environmental conservation, urban planning, and disaster management to make informed choices. You’ll also learn how to leverage Python to process real-time data and create valuable information products. By the end of this book, you'll have acquired the knowledge and techniques needed to build a complete geospatial application that can generate a report and can be further customized for different purposes.
Table of Contents (18 chapters)
1
Part 1:The History and the Present of the Industry
5
Part 2:Geospatial Analysis Concepts
11
Part 3:Practical Geospatial Processing Techniques

Limitations of real-time data

The term real-time data typically means near-real-time. Some tracking devices capture real-time data and may update as often as several times a second. However, the limitations of the infrastructure that broadcasts that data may constrain the output to every 10 seconds or longer. Weather radar is a perfect example. A Doppler Weather Radar (DWR) sweeps continuously but data is typically available online every 5 minutes. But given the contrast with traditional geospatial data updates, a refresh of a few minutes is real-time enough. Its limitations can be summarized as follows:

  • Network bandwidth limitations restricting data size
  • Network latency limiting the data update frequency
  • Availability of the data source due to restrictions such as battery life
  • Lack of quality control due to data being instantly available to consumers
  • Security vulnerabilities due to the rapid ingestion of unverified data

Real-time data opens up additional...