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Book

GeoAI with Python

A Practical Guide to Open-Source Geospatial AI

by Qiusheng Wu · creator profile

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Satellites capture massive volumes of imagery every day, but turning pixels into insight requires AI. This book teaches you to build, train, and apply deep learning models to real satellite imagery using Python and open-source tools, with 23 chapters of executable code you can run today.

Table of contents

Part I: Foundations

  1. Introduction to GeoAI
  2. Setting Up Your Environment
  3. Geospatial Data Essentials

Part II: Data Acquisition and Preparation

  1. Downloading Remote Sensing Data
  2. Interactive Mapping and Visualization
  3. Preparing Training Data

Part III: Core AI Tasks

  1. Image Recognition
  2. Object Detection
  3. Semantic Segmentation
  4. Instance Segmentation
  5. Image Translation
  6. Change Detection
  7. Pixel-Level Regression

Part IV: Foundation Models and Satellite Embeddings

  1. SAM for Geospatial Applications
  2. Vision-Language Models
  3. Satellite Embeddings

Part V: QGIS Plugins

  1. Setting Up the GeoAI QGIS Plugin
  2. Tree Segmentation in QGIS
  3. Water Segmentation in QGIS
  4. Vision-Language Models in QGIS
  5. Segment Anything in QGIS
  6. Semantic Segmentation in QGIS
  7. Instance Segmentation in QGIS
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