Michael Dorman – författare

A web map is an interactive display of geographic information, in the form of a web page, that you can use to tell stories and answer questions. Web maps have numerous advantages over traditional mapping techniques, such as the ability to display up-to-date or even real-time information, easy distribution to end users, and highly customized interactive content. Introduction to Web Mapping teaches you how to develop online interactive web maps and web mapping applications, using standard web technologies: HTML, CSS and JavaScript. The core technologies are introduced in Chapters 1-5, focusing on the specific aspects which are most relevant to web mapping. Chapters 6-13 then implement the material and demonstrate key concepts for building and publishing interactive web maps. The book: Gives an introduction to fundamental web technologies: HTML, CSS and JavaScript Covers Leaflet, the popular open-source JavaScript library for building web maps Describes the GeoJSON vector layer format and the Ajax technique for loading data Shows how spatial database APIs, such as the CARTO platform, can be combined with a web map to query and display large amounts of data Introduces client-side geoprocessing with the Turf.js JavaScript library, for applying spatial operators in the browser Demonstrates a complex web mapping application for collecting crowdsourced data, combining Leaflet, CARTO and the Leaflet.draw plugin Goes over 69 complete code examples and includes 9 solved exercises for building web maps and web pages (downloadable code is provided in the online supplement)The book is intended for beginners with no background in web technologies or programming. Nevertheless, some prior experience with computers and programming is beneficial. The book can be used for self-study, or as a textbook in a standard undergraduate "Web mapping" course in a Geography department, intended for students specializing in Geographic Information Systems (GIS).

A web map is an interactive display of geographic information, in the form of a web page, that you can use to tell stories and answer questions. Web maps have numerous advantages over traditional mapping techniques, such as the ability to display up-to-date or even real-time information, easy distribution to end users, and highly customized interactive content. Introduction to Web Mapping teaches you how to develop online interactive web maps and web mapping applications, using standard web technologies: HTML, CSS and JavaScript. The core technologies are introduced in Chapters 1-5, focusing on the specific aspects which are most relevant to web mapping. Chapters 6-13 then implement the material and demonstrate key concepts for building and publishing interactive web maps. The book: Gives an introduction to fundamental web technologies: HTML, CSS and JavaScript Covers Leaflet, the popular open-source JavaScript library for building web maps Describes the GeoJSON vector layer format and the Ajax technique for loading data Shows how spatial database APIs, such as the CARTO platform, can be combined with a web map to query and display large amounts of data Introduces client-side geoprocessing with the Turf.js JavaScript library, for applying spatial operators in the browser Demonstrates a complex web mapping application for collecting crowdsourced data, combining Leaflet, CARTO and the Leaflet.draw plugin Goes over 69 complete code examples and includes 9 solved exercises for building web maps and web pages (downloadable code is provided in the online supplement)The book is intended for beginners with no background in web technologies or programming. Nevertheless, some prior experience with computers and programming is beneficial. The book can be used for self-study, or as a textbook in a standard undergraduate "Web mapping" course in a Geography department, intended for students specializing in Geographic Information Systems (GIS).

A web map is an interactive display of geographic information, in the form of a web page, that you can use to tell stories and answer questions. Web maps have numerous advantages over traditional mapping techniques, such as the ability to display up-to-date or even real-time information, easy distribution to end users, and highly customized interactive content. Introduction to Web Mapping teaches you how to develop online interactive web maps and web mapping applications, using standard web technologies: HTML, CSS and JavaScript. The core technologies are introduced in Chapters 1-5, focusing on the specific aspects which are most relevant to web mapping. Chapters 6-13 then implement the material and demonstrate key concepts for building and publishing interactive web maps.

The book:

Gives an introduction to fundamental web technologies: HTML, CSS and JavaScript

Covers Leaflet, the popular open-source JavaScript library for building web maps

Describes the GeoJSON vector layer format and the Ajax technique for loading data

Shows how spatial database APIs, such as the CARTO platform, can be combined with a web map to query and display large amounts of data

Introduces client-side geoprocessing with the Turf.js JavaScript library, for applying spatial operators in the browser

Demonstrates a complex web mapping application for collecting crowdsourced data, combining Leaflet, CARTO and the Leaflet.draw plugin

Goes over 69 complete code examples and includes 9 solved exercises for building web maps and web pages (downloadable code is provided in the online supplement)

The book is intended for beginners with no background in web technologies or programming. Nevertheless, some prior experience with computers and programming is beneficial. The book can be used for self-study, or as a textbook in a standard undergraduate "Web mapping" course in a Geography department, intended for students specializing in Geographic Information Systems (GIS).

A web map is an interactive display of geographic information, in the form of a web page, that you can use to tell stories and answer questions. Web maps have numerous advantages over traditional mapping techniques, such as the ability to display up-to-date or even real-time information, easy distribution to end users, and highly customized interactive content. Introduction to Web Mapping teaches you how to develop online interactive web maps and web mapping applications, using standard web technologies: HTML, CSS and JavaScript. The core technologies are introduced in Chapters 1-5, focusing on the specific aspects which are most relevant to web mapping. Chapters 6-13 then implement the material and demonstrate key concepts for building and publishing interactive web maps.

The book:

Gives an introduction to fundamental web technologies: HTML, CSS and JavaScript

Covers Leaflet, the popular open-source JavaScript library for building web maps

Describes the GeoJSON vector layer format and the Ajax technique for loading data

Shows how spatial database APIs, such as the CARTO platform, can be combined with a web map to query and display large amounts of data

Introduces client-side geoprocessing with the Turf.js JavaScript library, for applying spatial operators in the browser

Demonstrates a complex web mapping application for collecting crowdsourced data, combining Leaflet, CARTO and the Leaflet.draw plugin

Goes over 69 complete code examples and includes 9 solved exercises for building web maps and web pages (downloadable code is provided in the online supplement)

The book is intended for beginners with no background in web technologies or programming. Nevertheless, some prior experience with computers and programming is beneficial. The book can be used for self-study, or as a textbook in a standard undergraduate "Web mapping" course in a Geography department, intended for students specializing in Geographic Information Systems (GIS).

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python's capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.Key features:Showcases the integration of vector and raster datasets operations.Provides explanation of each line of code in the book to minimize surprises.Includes example datasets and meaningful operations to illustrate the applied nature of geographic research.Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python's capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.Key features:Showcases the integration of vector and raster datasets operations.Provides explanation of each line of code in the book to minimize surprises.Includes example datasets and meaningful operations to illustrate the applied nature of geographic research.Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python''s capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.

Key features:

Showcases the integration of vector and raster datasets operations. Provides explanation of each line of code in the book to minimize surprises. Includes example datasets and meaningful operations to illustrate the applied nature of geographic research.

Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.

The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python''s capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.

Key features:

Showcases the integration of vector and raster datasets operations. Provides explanation of each line of code in the book to minimize surprises. Includes example datasets and meaningful operations to illustrate the applied nature of geographic research.

Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.

The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.