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Learning Geospatial Analysis with Python

Joel Lawhead

Harness the powerful Python programming language to navigate the realms of Geographic Information Systems, Remote Sensing, Topography, and more, while embracing a guiding framework for effective geospatial analysis Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. In this new edition, you'll embark on an exhilarating geospatial analysis adventure using Python This fourth edition will guide you through various GIS techniques, geodatabases, remote sensing, point clouds, elevations, and Anaconda installation. You will delve into an array of geospatial data aspects, including types, formats, structures, metadata, vectors, rasters, lidar, and web services. You will gain proficiency in fundamental tools such as GDAL/OGR, PROJ, PDAL, PostGIS, QGIS, Leaflet, and more. Unleashing the potential of the geospatial Python toolbox, you will master QGIS, Anaconda, Jupyter, Shapely, GeoPandas, and similar tools. Practical Python GIS techniques, including distance measurement, polygon area calculation, coordinate conversions, thematic mapping, and geocoding, will be covered. Additionally, you will engage with remote sensing data, elevation models, and point clouds. The book will guide you into advanced geospatial modeling using Python and address real-time data challenges. Lastly, you will construct advanced geospatial products and automate GIS workflows By the end of this book, you'll acquire the knowledge and techniques needed to build an entire geospatial application that outputs a report and can be further customized for different purposes This book is for Python developers, researchers, or analysts who want to perform geospatial modeling and GIS analysis with Python. Basic knowledge of digital mapping and analysis using Python or other scripting languages will be helpful.

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