Python Geospatial Analysis Essentials Process Analyze And Display Geospatial Data Using Python Libraries And Related Tools
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Author | : Erik Westra |
Publisher | : Packt Publishing Ltd |
Total Pages | : 200 |
Release | : 2015-06-23 |
Genre | : Computers |
ISBN | : 1783553898 |
Python is a highly expressive language that makes it easy to write sophisticated programs. Combining high-quality geospatial data with Python geospatial libraries will give you a powerful toolkit for solving a range of geospatial programming tasks. The book begins with an introduction to geospatial analysis and programming and explains the ideas behind geospatial data. You will explore Python libraries for building your own geospatial applications. You will learn to create a geospatial database for your application using PostGIS and the psycopg2 library, and see how the Mapnik library can be used to create attractive and useful maps. Finally, you will learn to use the Shapely and NetworkX libraries to create, analyze, and manipulate complex geometric objects, before implementing a system to match GPS recordings against a database of roads to produce a heatmap of the most frequently used roads.
Author | : Christine Garrard |
Publisher | : Simon and Schuster |
Total Pages | : 558 |
Release | : 2016-05-05 |
Genre | : Computers |
ISBN | : 163835314X |
Summary Geoprocessing with Python teaches you how to use the Python programming language, along with free and open source tools, to read, write, and process geospatial data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology This book is about the science of reading, analyzing, and presenting geospatial data programmatically, using Python. Thanks to dozens of open source Python libraries and tools, you can take on professional geoprocessing tasks without investing in expensive proprietary packages like ArcGIS and MapInfo. The book shows you how. About the Book Geoprocessing with Python teaches you how to access available datasets to make maps or perform your own analyses using free tools like the GDAL, NumPy, and matplotlib Python modules. Through lots of hands-on examples, you’ll master core practices like handling multiple vector file formats, editing geometries, applying spatial and attribute filters, working with projections, and performing basic analyses on vector data. The book also covers how to manipulate, resample, and analyze raster data, such as aerial photographs and digital elevation models. What's Inside Geoprocessing from the ground up Read, write, process, and analyze raster data Visualize data with matplotlib Write custom geoprocessing tools Three additional appendixes available online About the Reader To read this book all you need is a basic knowledge of Python or a similar programming language. About the Author Chris Garrard works as a developer for Utah State University and teaches a graduate course on Python programming for GIS. Table of Contents Introduction Python basics Reading and writing vector data Working with different vector file formats Filtering data with OGR Manipulating geometries with OGR Vector analysis with OGR Using spatial reference systems Reading and writing raster data Working with raster data Map algebra with NumPy and SciPy Map classification Visualizing data Appendixes A - Installation B - References C - OGR - online only D - OSR - online only E - GDAL - online only
Author | : Karim Bahgat |
Publisher | : Packt Publishing Ltd |
Total Pages | : 192 |
Release | : 2015-06-17 |
Genre | : Computers |
ISBN | : 1782174419 |
This book provides you with the resources to successfully develop your own GIS application in Python. The book begins by walking you through the loading and saving of data structures before you start to build the look and feel of your application and create its interactive map window. You'll then move on to managing, editing, and analyzing spatial data from within the application and finish with instructions for packaging the application for distribution. By the end of the book, you should be able to use your GIS application as a template for further development, with the potential to expand and customize it to suit your needs.
Author | : Eva H. Dodsworth |
Publisher | : Rowman & Littlefield |
Total Pages | : 491 |
Release | : 2018-09-22 |
Genre | : Reference |
ISBN | : 1538100843 |
The interdisciplinary uses of traditional cartographic resources and modern GIS tools allow for the analysis and discovery of information across a wide spectrum of fields. A Research Guide to Cartographic Resources navigates the numerous American and Canadian cartographic resources available in print and online, offering researchers, academics and students with information on how to locate and access the large variety of resources, new and old. Dozens of different cartographic materials are highlighted and summarized, along with lists of map libraries and geospatial centers, and related professional associations. A Research Guide to Cartographic Resources consists of 18 chapters, two appendices, and a detailed index that includes place names, and libraries, structured in a manner consistent with most reference guides, including cartographic categories such as atlases, dictionaries, gazetteers, handbooks, maps, plans, GIS data and other related material. Almost all of the resources listed in this guide are categorized by geography down to the county level, making efficient work of the type of material required to meet the information needs of those interested in researching place-specific cartographic-related resources. Additionally, this guide will help those interested in not only developing a comprehensive collection in these subject areas, but get an understanding of what materials are being collected and housed in specific map libraries, geospatial centers and their related websites. Of particular value are the sections that offer directories of cartographic and GIS libraries, as well as comprehensive lists of geospatial datasets down to the county level. This volume combines the traditional and historical collections of cartography with the modern applications of GIS-based maps and geospatial datasets.
Author | : Silas Toms |
Publisher | : Packt Publishing Ltd |
Total Pages | : 431 |
Release | : 2018-04-27 |
Genre | : Computers |
ISBN | : 1788293819 |
Explore GIS processing and learn to work with various tools and libraries in Python. Key Features Analyze and process geospatial data using Python libraries such as; Anaconda, GeoPandas Leverage new ArcGIS API to process geospatial data for the cloud. Explore various Python geospatial web and machine learning frameworks. Book Description Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API. What you will learn Manage code libraries and abstract geospatial analysis techniques using Python 3. Explore popular code libraries that perform specific tasks for geospatial analysis. Utilize code libraries for data conversion, data management, web maps, and REST API creation. Learn techniques related to processing geospatial data in the cloud. Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and SpatiaLite. Who this book is for The audience for this book includes students, developers, and geospatial professionals who need a reference book that covers GIS data management, analysis, and automation techniques with code libraries built in Python 3.
Author | : Erik Westra |
Publisher | : |
Total Pages | : 0 |
Release | : 2013 |
Genre | : Computers |
ISBN | : 9781782161523 |
This is a tutorial style book that will teach usage of Python tools for GIS using simple practical examples and then show you how to build a complete mapping application from scratch. The book assumes basic knowledge of Python. No knowledge of Open Source GIS is required.Experienced Python developers who want to learn about geospatial concepts, work with geospatial data, solve spatial problems, and build map-based applications.This book will be useful those who want to get up to speed with Open Source GIS in order to build GIS applications or integrate Geo-Spatial features into their existing applications.
Author | : Michael Diener |
Publisher | : Packt Publishing Ltd |
Total Pages | : 310 |
Release | : 2015-11-30 |
Genre | : Computers |
ISBN | : 1783555084 |
Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python About This Book Explore the practical process of using geospatial analysis to solve simple to complex problems with reusable recipes Concise step-by-step instructions to teach you about projections, vector, raster, overlay, indoor routing and topology analysis Create a basic indoor routing application with geodjango Who This Book Is For If you are a student, teacher, programmer, geospatial or IT administrator, GIS analyst, researcher, or scientist looking to do spatial analysis, then this book is for you. Anyone trying to answer simple to complex spatial analysis questions will get a working demonstration of the power of Python with real-world data. Some of you may be beginners with GIS, but most of you will probably have a basic understanding of geospatial analysis and programming. What You Will Learn Discover the projection and coordinate system information of your data and learn how to transform that data into different projections Import or export your data into different data formats to prepare it for your application or spatial analysis Use the power of PostGIS with Python to take advantage of the powerful analysis functions Execute spatial analysis functions on vector data including clipping, spatial joins, measuring distances, areas, and combining data to new results Create your own set of topology rules to perform and ensure quality assurance rules in Python Find the shortest indoor path with network analysis functions in easy, extensible recipes revolving around all kinds of network analysis problems Visualize your data on a map using the visualization tools and methods available to create visually stunning results Build an indoor routing web application with GeoDjango to include your spatial analysis tools built from the previous recipes In Detail Geospatial development links your data to places on the Earth's surface. Its analysis is used in almost every industry to answer location type questions. Combined with the power of the Python programming language, which is becoming the de facto spatial scripting choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems. This book begins by tackling the installation of the necessary software dependencies and libraries needed to perform spatial analysis with Python. From there, the next logical step is to prepare our data for analysis; we will do this by building up our tool box to deal with data preparation, transformations, and projections. Now that our data is ready for analysis, we will tackle the most common analysis methods for vector and raster data. To check or validate our results, we will explore how to use topology checks to ensure top-quality results. This is followed with network routing analysis focused on constructing indoor routes within buildings, over different levels. Finally, we put several recipes together in a GeoDjango web application that demonstrates a working indoor routing spatial analysis application. The round trip will provide you all the pieces you need to accomplish your own spatial analysis application to suit your requirements. Style and approach Easy-to-follow, step-by-step recipes, explaining from start to finish how to accomplish real-world tasks.
Author | : Anthony Molinaro |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 632 |
Release | : 2006 |
Genre | : Computers |
ISBN | : 0596009763 |
A guide to SQL covers such topics as retrieving records, metadata queries, working with strings, data arithmetic, date manipulation, reporting and warehousing, and hierarchical queries.
Author | : Silas Toms |
Publisher | : Packt Publishing Ltd |
Total Pages | : 224 |
Release | : 2015-02-26 |
Genre | : Computers |
ISBN | : 1783988673 |
If you are a GIS student or professional who needs an understanding of how to use ArcPy to reduce repetitive tasks and perform analysis faster, this book is for you. It is also a valuable book for Python programmers who want to understand how to automate geospatial analyses.
Author | : Abdishakur Hassan |
Publisher | : Packt Publishing Ltd |
Total Pages | : 165 |
Release | : 2019-05-31 |
Genre | : Computers |
ISBN | : 1789809339 |
Discover the power of location data to build effective, intelligent data models with Geospatial ecosystems Key FeaturesManipulate location-based data and create intelligent geospatial data modelsBuild effective location recommendation systems used by popular companies such as UberA hands-on guide to help you consume spatial data and parallelize GIS operations effectivelyBook Description Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses. This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more. By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease. What you will learnLearn how companies now use location dataSet up your Python environment and install Python geospatial packagesVisualize spatial data as graphsExtract geometry from spatial dataPerform spatial regression from scratchBuild web applications which dynamically references geospatial dataWho this book is for Data Scientists who would like to leverage location-based data and want to use location-based intelligence in their data models will find this book useful. This book is also for GIS developers who wish to incorporate data analysis in their projects. Knowledge of Python programming and some basic understanding of data analysis are all you need to get the most out of this book.