Book Image

Learning Geospatial Analysis with Python

By : Joel Lawhead
Book Image

Learning Geospatial Analysis with Python

By: Joel Lawhead

Overview of this book

Geospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software. Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data. This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don’t become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.
Table of Contents (17 chapters)
Learning Geospatial Analysis with Python Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Metadata management


Internet distribution of data has increased the importance of metadata. Data custodians are able to release a dataset to the entire world for download without any personal interaction. The metadata record of a geospatial dataset can follow that to help ensure that the integrity and accountability for that data is maintained. Properly formatted metadata also allows for automated cataloguing, search indexing, and integration of datasets. Metadata has become so important that a common mantra within the geospatial community is Data without metadata isn't data, meaning that a geospatial dataset cannot be fully utilized and understood without metadata. The following section will list some of the common metadata tools that are available. The OGC standard for metadata management is the Catalog Service for the Web (CSW), which creates a metadata-based catalog system and an API for distributing and discovering datasets.

Tip

For an excellent example of a CSW and client built using...