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Paperback. Condizione: new. 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 sen…sing 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 multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Condizione: new. 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 sen…sing 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.
