GeoAI with ArcGIS Pro 3.7: Build Intelligent Spatial Workflows with Machine Learning, Deep Learning, Imagery, and Foundation Models

Name: GeoAI with ArcGIS Pro 3.7: Build Intelligent Spatial Workflows with Machine Learning, Deep Learning, Imagery, and Foundation Models
Brand: Independently Published
SKU: 9798194677726
Price: 2085.0 INR
Availability: InStock

by Michael Bell

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ISBN13: 9798194677726
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: August 24, 2026
Pages: 164
Original Price: GBP 18.31
Language: English
Edition: N/A
Item Weight: 395 grams
BISAC Subject(s): Remote Sensing & Geographic Information Systems

About The Book

GeoAI with ArcGIS Pro 3.7

A Practical Guide to Spatial Machine Learning, Deep Learning, Remote Sensing, and Intelligent Geographic Analysis

Artificial intelligence is changing the way geographic data is analyzed-but using AI with spatial data requires more than simply training a model and putting the results on a map.

GeoAI with ArcGIS Pro 3.7 provides a practical, project-focused introduction to applying machine learning, deep learning, remote sensing, spatial forecasting, foundation models, and 3D analysis to real geographic problems.

Starting with the fundamentals, Michael Bell takes you from organizing your first GeoAI project in ArcGIS Pro through increasingly advanced workflows involving spatial machine learning, imagery, object detection, segmentation, time-series forecasting, geospatial embeddings, LiDAR, and automation.

You will learn how to:

Prepare raster and vector data for machine learning
Engineer useful spatial features
Build classification, regression, and clustering workflows
Understand spatial autocorrelation and spatial leakage
Perform more reliable spatial validation
Train deep-learning models with geospatial imagery
Detect buildings and other objects in aerial and satellite imagery
Perform image segmentation and land-cover classification
Analyze multispectral imagery and geographic change
Build spatial time-series and forecasting workflows
Explore foundation models and geospatial embeddings
Work with LiDAR and 3D point clouds
Automate GeoAI workflows with ModelBuilder and ArcPy
Evaluate model accuracy and investigate failure cases
Understand bias, uncertainty, explainability, and reproducibility
Turn individual analyses into complete GeoAI pipelines

The book also emphasizes something that is often overlooked in AI tutorials: a prediction that looks convincing is not necessarily a prediction that should be trusted.

Throughout the workflows, you will learn to examine model errors, avoid spatial leakage, validate predictions geographically, compare AI approaches with simpler alternatives, and connect model outputs to actual GIS decisions.

Whether you are a GIS analyst learning machine learning, a student building geospatial projects, a remote-sensing practitioner, or a developer exploring AI-powered geographic applications, this book provides a practical path from GIS data to evaluated GeoAI results.

Learn the tools. Build the models. Test the predictions. Understand where they fail.

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