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Tool Up! Become a data management superstar with tools from the Geospatial Data Abstraction Library (GDAL). This book is a reference guide for quickly finding the right syntax and example usage of all GDAL/OGR commands. Used behind most of the open source geospatial applications, as well as leading proprietary GIS applications, GDAL is the preeminent spatial data access library. GDAL comes with several powerful command line utilities including tools for examining, converting, transforming, building and analyzing raster and vector data. Included within is substantial new content, supplementing the GDAL documentation which makes up the rest of the book. Look up a workflow concept like "Translate Vectors" and quickly find examples designed to get you going right away. Digital versions of the book are fully linked with bookmarks between topics and command names, making it easier than ever to follow from an example to more detailed documentation. Tooling up your skills with this book will allow you to confidently tackle future raster and vector data management challenges!
Decision makers, such as government officials, need to better understand human activity in order to make informed decisions. With the ability to measure and explore geographic space through the use of geospatial intelligence data sources including imagery and mapping data, they are better able to measure factors affecting the human population. As a broad field of study, geospatial research has applications in a variety of fields including military science, environmental science, civil engineering, and space exploration. Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications explores multidisciplinary applications of geographic information systems to describe, assess, and visually depict physical features and to gather data, information, and knowledge regarding human activity. Highlighting a range of topics such as geovisualization, spatial analysis, and landscape mapping, this multi-volume book is ideally designed for data scientists, engineers, government agencies, researchers, and graduate-level students in GIS programs.
Addresses a range of analytical techniques that are provided within modern Geographic Information Systems and related geospatial software products. This guide covers: the principal concepts of geospatial analysis; core components of geospatial analysis; and, surface analysis, including surface form analysis, gridding and interpolation methods.
Create custom applications with the Google Maps API Featuring step-by-step examples, this practical resource gets you started programming the Google Maps API with JavaScript in no time. Learn how to embed maps on web pages, annotate the embedded maps with your data, generate KML files to store and reuse your map data, and enable client applications to request spatial data through web services. Google Maps: Power Tools for Maximizing the API explains techniques for visualizing masses of data and animating multiple items on the map. You’ll also find out how to embed Google maps in desktop applications to combine the richness of the Windows interface with the unique features of the API. You can use the numerous samples included throughout this hands-on guide as your starting point for building customized applications. Create map-enabled web pages with a custom look Learn the JavaScript skills required to exploit the Google Maps API Create highly interactive interfaces for mapping applications Embed maps in desktop applications written in .NET Annotate maps with labels, markers, and shapes Understand geodesic paths and shapes and perform geodesic calculations Store geographical data in KML format Add GIS features to mapping applications Store large sets of geography data in databases and perform advanced spatial queries Use web services to request spatial data from within your script on demand Automate the generation of standalone web pages with annotated maps Use the Geocoding and Directions APIs Visualize large data sets using symbols and heatmaps Animate items on a map Bonus online content includes: A tutorial on The SQL Spatial application A bonus chapter on animating multiple airplanes Three appendices: debugging scripts in the browser; scalable vector graphics; and applying custom styles
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/.
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.
With planning support software, citizen planners can move buildings from block to block, tear them down, build complete subdivisions, run new highways in and around town, analyze any number of scenarios, and see with their own eyes the consequences of each action. This reference offers new possibilities and discusses the most important aspects of computer-aided land-use planning.
The emerging field of using geospatial technology to teach science and environmental education presents an excellent opportunity to discover the ways in which educators use research-grounded pedagogical commitments in combination with their practical experiences to design and implement effective teacher professional development projects. Often missing from the literature are in-depth, explicit discussions of why and how educators choose to provide certain experiences and resources for the teachers with whom they work, and the resulting outcomes. The first half of this book will enable science and environmental educators to share the nature and structure of large scale professional development projects while discussing the theoretical commitments that undergird their work. Many chapters will include temporal aspects that present the ways in which projects change over time in response to evaluative research and practical experience. In the second half of the book, faculty and others whose focus is on national and international scales will share the ways in which they are working to meet the growing needs of teachers across the globe to incorporate geospatial technology into their science teaching. These efforts reflect the ongoing conversations in science education, geography, and the geospatial industry in ways that embody the opportunities and challenges inherent to this field. This edited book will serve to define the field of teacher professional development for teaching science using geospatial technology. As such, it will identify short term and long term objectives for science, environmental, and geography educators involved in these efforts. As a result, this book will provide a framework for future projects and research in this exciting and growing field.
'Web Mapping Illustrated' shows readers how to create maps, even interactive maps, with free tools, including MapServer, OpenEV, GDAL/OGR, and PostGIS. It also explains how to find, collect, understand, use, and share mapping data
Having the ability to measure and explore the geographic space that surrounds us provides endless opportunities for us to utilize and interact with the world. As a broad field of study, geospatial research has applications in a variety of fields including military science, environmental science, civil engineering, and space exploration. Geospatial Research: Concepts, Methodologies, Tools, and Applications is a multi-volume publication highlighting critical topics related to geospatial analysis, geographic information systems, and geospatial technologies. Exploring multidisciplinary applications of geographic information systems and technologies in addition to the latest trends and developments in the field, this publication is ideal for academic and government library inclusion, as well as for reference by data scientists, engineers, government agencies, researchers, and graduate-level students in GIS programs.