Spatial Data Science: Advance Your Analytics Class Resources

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• Lesson 1: Building a Foundation for Spatial Data Science
• Lesson 2: Data Engineering
• Lesson 3: Clustering
• Lesson 4: Space-time analysis
• Lesson 5: Regression
• Lesson 6: Multiscale Geographically Weighted regression
• Lesson 7: Presence Only Prediction
• Lesson 8: Geostatistical interpolation

Take your analytics projects to the next level by incorporating the power of location and place-based context. This course introduces spatial statistical techniques and methods used to uncover patterns and relationships in data, unlocking insights that help organizations solve complex problems. You’ll explore a variety of scenarios and build skills with powerful ArcGIS tools used by analysts, researchers, and data scientists around the world.

Lesson 1: Building a Foundation for Spatial Data Science

• ArcGIS Pro Help:

  • What is a z-score? What is a p-value?

  • Best practices for selecting a fixed distance band value

• Spatial Statistics Resources: The latest from the Esri Spatial Statistics team

• Video: From Means, to Machine Learning: Spatial Statistics Basics and Innovations

• The Esri Guide to GIS Analysis Volumes 2, Andy Mitchell, Esri Press

• Textbook: Statistics in Geography: A practical approach , David Ebdon 1977

•  Esri GIS Analysis Workshop, David Attaway

• Video: Spatial Data Mining I: Essentials of Cluster Analysis

• Video: Spatial Data Science in ArcGIS: An Overview

• Applying Spatial Data Science: A Complete Workflow

• Learning Plan: Spatial Analysis and Data Science Fundamentals

• Book: Lauren Bennett, Flora Vale. Spatial Statistics Illustrated, Esri Press 2023

• Book: Andy Mitchel. The Esri Guide to GIS Analyisis, Volume 2: Spatial Measurements and Statistics, second edition. Esri Press, 2021

Lesson 2: Data Engineering

• ArcGIS Pro Help:

  •  Introduction to Data Engineering

  • Get started with Data Engineerig

  • Open Data Engineering View

  • Explore fields

  • Interact with statistics

  • Prepare data

• Web Course: Introduction to Data Engineering

• Web Course: Data Science Workflows Using ArcGIS Notebooks

• Tutorials: Data Engineering in ArcGIS Pro

• Tutorials: Examine racial disparities in police stops

• Blog: Spatial data science using ArcGIS Notebook Part 2: Data Fusion, wrangling and preparation

• Blog Spatial data science using ArcGIS Notebooks Part 3: Data validation and data engineering

• Video: Data Engineering and Visualization for Spatial Data Science

• Videos on mediaspace.esri.com: Seach tag: Data Engineering

Lesson 3 : Clustering

• ArcGIS Pro Help:

  • Hot Spot Analysis

  • How Optimized Hot Spot Analysis works

  • How Optimized Outlier Analysis works

  • Modeling spatial relationships

• Web Course: Mapping Clusters: Introduction to Statistical Cluster Analysis

• Learning Plan: Identifying Clusters Using ArcGIS

• Blog: Machine Learning: Cluster analysis using Python and ArcGIS, Part 5

• Video: From Means, to Machine Learning: Spatial Statistics Basics and Innovations

• Video: Spatial Data Mining I: Essential of Cluster Analysis

• Video: Spatial Statistics : Statistical Cluster Analysis

• Video: Spatial Statistics: Machine Learning Based Clustering

• Videos on mediaspace.esri.com: Search tag: Cluster analysis

• Book: Spencer Chainey, Understanding Crime: Analyzing the Geography of Crime , Esri Press 2021

Lesson 4 : Space-time analysis

• ArcGIS Pro Help:

  • An overview of the Space Time Pattern Mining toolbox

  • An overview of the Space Time Cube Creation toolset

  • An overview of the Space Time Cube Visualization toolset

  • An overview of the Space Time Pattern Analysis toolset

  • Space-time cluster analysis

• ArcGIS Blog: Introducing a New Space Time Cube Visualization Experience in ArcGIS Pro

• Web Course: Introduction to Space-Time Analysis

• Web Course: Time Series Clustering

• Web Course: Creating a Space-Time Cube

• Web Course: Space-Time Analysis: Finding Temporal Trends

• Tutorial: Explore a space-time cube

• Tutorial: Identify popular places with spatiotemporal data science

• Tutorial: Investigate pollution patterns with space-time analysis

• Learning Plan: Identifying Clusters Using ArcGIS

• Video: Spatial Statistics: Analyzing Space Time Data

• Video: Spatial Data Mining II: A Deep Dive Into Space-Time Analysis

• Video: Space-Time Analysis: Exploring Spatiotemporal Patterns and Forecasting

Lesson 5 : Regression

• ArcGIS Pro Help:

  • Regression Analysis basics

  • How Generalized Linear Regression works

  • How OLS regression works

  • How Exploratory Regression works

  • Exploratory Regression

  • What they don’t tell you about regression analysis

  • Multicollinearity

  • Heteroscedastisity

• ArcUser article: Finding a Meaningful Model, a checklist to evaluate regression models

• Learning Plan: Regression Analysis Essentials

• Tutorial: Determine how location impacts interest rates

• Tutorial: Predict home prices with regression analysis and machine learning.

• Tutorial: Estimate biomass using GEDI and Landsat data

• Video: Beyond Where: Modeling Spatial Relationships and Making Predictions

• Video: Predictive Analysis: Exploring Relationships with Regression and Causal Analysis

Lesson 6: Multiscale Geographically Weighted regression

• ArcGIS Pro Help:

  • How Multiscale Geographically Weighted Regression (MGWR) works

  • Multiscale Geographically Weighted Regression (MGWR) (Spatial Statistics)

  • How Geographically Weighted Regression works

• Blog: Discovering spatial relationships with Multiscale Geographically Weighted Regression

• Web Course: Geographically Weighted Regression Analysis Using ArcGIS Pro

• Video: Dive Into ArcGIS Pro 3.0 - Introduction to Multiscale Geographically Weighted Regression Analysis

• Textbook:: A. Stewart Fotheringham, Taylor M. Oshan, Ziqi Li 2024. Multiscale Geographically Weighted Regression Theory and  Practice

Lesson 7: Presence Only Prediction

• ArcGIS Pro Help:

  • How Presence-only Prediction works

  • Presence-only Prediction (MaxEnt) (Spatial Statistics)

• Blog: Presence-Only Prediction (MaxEnt) 101: Using GIS to model species distribution

• Blog: Eight tips to help you make better presence prediction models with Presence-only Prediction (MaxEnt)

• 2025 Esri UC presentation: Predictive Analysis: Modeling data Using Statistics and Machine Learning

• Tutorial: Perform species distribution modeling

• Video: Presence Only Prediction of Coral Ecosystems

• Video: An Explanation of MaxEnt for Ecologists

• Video: The Forest for the Trees: Making Predictions using Forest Based Classification and Regression

Lesson 8: Geostatistical interpolation

• ArcGIS Pro Help:

  • What are geostatistical interpolation techniques?

  • Understanding geostatistical analysis

  • Kriging in Geostatistical Analyst

  • Random processes with dependence

  • What is empirical Bayesian Kriging?

  • What is Empirical Bayesian Kriging 3D?

• Web Course: Geostatistical Interpolation: Introduction

• Web Course: Geostatistical Interpolation: Using Empirical Baysian Kriging and EBK Regression Prediction

• Video: ArcGIS Geostatistical Analyst: Spatial Interpolation Using Kriging

• Video: Geostatistical Analyst: Concepts and Applications of Kriging

• Video: 2018 Esri Ocean Forum: 3D Interpolation of In Situ Ocean Observations

• Tutorial: Interpolate 3D oxygen measurements in Monterey Bay

• Tutorial: Model water quality using interpolation

• Tutorial: Learning path: Geostatistics in ArcGIS Pro