Geospatial Analysis is used in almost every field you can think of from medicine to defense, to farming. Learning Geospatial Analysis with Python, Third Edition would be a helpful guide to Geographic Information Systems and Remote Sensing Analysis using Python 3.7 without overwhelming the reader.
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Joel Lawhead is a PMI-certified Project Management Professional (PMP), a certified GIS Professional (GISP), and vice president of NVision Solutions, Inc., an award-winning firm specializing in geospatial technology integration and sensor engineering for NASA, FEMA, NOAA, the US Navy, and many other commercial and non-profit organizations. Joel began using Python in 1997 and started combining it with geospatial software development in 2000. He has authored multiple editions of Learning Geospatial Analysis with Python and QGIS Python Programming Cookbook, both from Packt. He is also the developer of the open source Python Shapefile Library (PyShp) and maintains a geospatial technical blog.
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Softcover. Condición: As New. Leichte Kratzer / Abnutzungen / Druckstellen. Learn the core concepts of geospatial data analysis for building actionable GIS applications. This guide introduces GIS solutions using the latest features in Python 3.7 and explores various GIS tools and libraries, including PostGIS, QGIS, and PROJ. You'll automate geospatial analysis workflows with Python and Jupyter, applicable across diverse domains like defense, farming, and medicine. The book covers GIS techniques, geodatabases, and geospatial raster data, utilizing built-in tools and libraries in Python 3.7. You'll gain insights into software packages, APIs, and algorithms suitable for various scenarios. Additionally, you'll learn to apply Python GIS processes to different challenges, including working with remote sensing data. By the end, you'll be equipped to create a generic corporate system for managing customer support requests and field personnel. Key learning outcomes include automating workflows, coding a basic GIS in just 60 lines, creating thematic maps with tools like PyShp and OGR, understanding geospatial data formats, producing elevation contours, and applying analysis to real-time data tracking. This book is ideal for Python developers, researchers, or analysts interested in geospatial modeling and GIS analysis, with a foundational knowledge of digital mapping and scripting languages being beneficial. Nº de ref. del artículo: ec52025f-2b4a-472c-89cd-6e413fbf6fcc
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