Advanced Python GIS Engineering (Paperback)

Alira Vexel

ISBN 13: 9798294590468

Published by Independently Published, 2025

About this Item

Paperback. Advanced Python GIS EngineeringCloud-Native, Open-Source Spatial Workflows for Remote Sensing & Scalable ApplicationsBuild production-ready, cloud-native GIS applications using modern Python tools and open-source workflows.Whether you're a geospatial developer, data scientist, or remote sensing engineer, this hands-on guide will take you from local shapefiles to scalable cloud deployments using the most powerful spatial tools available in 2025.This is not a theory book. You'll build, automate, and deploy real-world geospatial pipelines step by step - using Python, GeoPandas, Rasterio, Earth Engine, Leafmap, STAC, TiTiler, FastAPI, Streamlit, AWS, and Docker.What You'll Master Inside This Book: Engineering-ready Python GIS stack setup using Conda, pipx, and DockerProcessing shapefiles, GeoJSON, and raster data at scale with GeoPandas & RasterioCloud-based remote sensing pipelines using Google Earth Engine Python APIServing COGs and dynamic tiles with TiTiler, STAC, and CloudFrontBuilding interactive dashboards with Streamlit, Deck.gl, and FoliumAutomating spatial ETL pipelines with Prefect and AirflowDeploying FastAPI-based geospatial services on AWS Lambda & GCP FunctionsCreating production-ready workflows with CI/CD, GitHub Actions, and TerraformReal-world projects: Land use detection, asset tracking, urban growth mapping & moreTools & Technologies CoveredPython 3.10+, GeoPandas, Rasterio, Xarray, Leafmap, DaskCloud Platforms: AWS S3, Google Cloud Storage, STAC, TiTilerVisualization: ipyleaflet, Pydeck, Mapbox GL JSAutomation: Docker, Prefect, GitHub Actions, TerraformAPIs & Apps: FastAPI, Streamlit, Heroku, Serverless FrameworkWho This Book Is ForGIS Developers & EngineersRemote Sensing AnalystsGeospatial Data ScientistsFreelancers & Technical ConsultantsProfessionals migrating from desktop GIS to modern Python and cloud-first workflowsWhat Makes This Book Different?This book goes beyond GeoPandas tutorials - it gives you engineering-grade, modern GIS pipelines that scale from your laptop to cloud infrastructure. Every chapter builds toward real deployment, automation, and production-readiness - no fluff, no theory, just results.Includes: Full reproducible Code Representations in Courier New and red formattingReal-world open datasets with COGs, STAC, GeoParquet, and metadataDocker, CI/CD, and deployment recipes for Heroku, Lambda, and Streamlit CloudPortfolio-ready projects for GitHub and freelance applicationsDon't just analyze maps - build systems that serve them.If you're ready to future-proof your GIS skillset and deploy real applications, this is the book you've been looking for. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9798294590468

Bibliographic Details

• Title: Advanced Python GIS Engineering (Paperback)
• Publisher: Independently Published
• Publication Date: 2025
• Language: English
• ISBN 13: 9798294590468
• Binding: Paperback
• Condition: new

About this title

Synopsis

Advanced Python GIS Engineering
Cloud-Native, Open-Source Spatial Workflows for Remote Sensing & Scalable Applications

Build production-ready, cloud-native GIS applications using modern Python tools and open-source workflows.
Whether you're a geospatial developer, data scientist, or remote sensing engineer, this hands-on guide will take you from local shapefiles to scalable cloud deployments using the most powerful spatial tools available in 2025.

This is not a theory book. You'll build, automate, and deploy real-world geospatial pipelines step by step — using Python, GeoPandas, Rasterio, Earth Engine, Leafmap, STAC, TiTiler, FastAPI, Streamlit, AWS, and Docker.

What You’ll Master Inside This Book:

• Engineering-ready Python GIS stack setup using Conda, pipx, and Docker
• Processing shapefiles, GeoJSON, and raster data at scale with GeoPandas & Rasterio
• Cloud-based remote sensing pipelines using Google Earth Engine Python API
• Serving COGs and dynamic tiles with TiTiler, STAC, and CloudFront
• Building interactive dashboards with Streamlit, Deck.gl, and Folium
• Automating spatial ETL pipelines with Prefect and Airflow
• Deploying FastAPI-based geospatial services on AWS Lambda & GCP Functions
• Creating production-ready workflows with CI/CD, GitHub Actions, and Terraform
• Real-world projects: Land use detection, asset tracking, urban growth mapping & more

Tools & Technologies Covered

• Python 3.10+, GeoPandas, Rasterio, Xarray, Leafmap, Dask
• Cloud Platforms: AWS S3, Google Cloud Storage, STAC, TiTiler
• Visualization: ipyleaflet, Pydeck, Mapbox GL JS
• Automation: Docker, Prefect, GitHub Actions, Terraform
• APIs & Apps: FastAPI, Streamlit, Heroku, Serverless Framework

Who This Book Is For

• GIS Developers & Engineers
• Remote Sensing Analysts
• Geospatial Data Scientists
• Freelancers & Technical Consultants
• Professionals migrating from desktop GIS to modern Python and cloud-first workflows

What Makes This Book Different?

This book goes beyond GeoPandas tutorials — it gives you engineering-grade, modern GIS pipelines that scale from your laptop to cloud infrastructure. Every chapter builds toward real deployment, automation, and production-readiness — no fluff, no theory, just results.

Includes:

• Full reproducible Code Representations in Courier New and red formatting
• Real-world open datasets with COGs, STAC, GeoParquet, and metadata
• Docker, CI/CD, and deployment recipes for Heroku, Lambda, and Streamlit Cloud
• Portfolio-ready projects for GitHub and freelance applications

Don’t just analyze maps — build systems that serve them.
If you're ready to future-proof your GIS skillset and deploy real applications, this is the book you’ve been looking for.