Bibliography

Introduction

This bibliography offers a starting point for exploring GeoAI research, encompassing key publications, textbooks, and online resources. Consider it a living document, constantly evolving as the field progresses.

Core Books

Core Articles

Harrie, L. et al. Machine learning in cartography. 2024

Map Distinction

Map Localisation

Feature Extraction (Points)

Feature Extraction (Lines)

Feature Extraction (Polygons)

Feature Extraction (Labels)

Feature Extraction (Fuzzy Elements)

Pattern Detection (Lines)

Pattern Detection (Polygons)

Content Description

Metadata Retrieval

Design Analysis

Similarity Search

Text-to-Map

Neural Rendering (Relief Shading)

Style Transfer

Generalization (Lines)

Generalization (Polygons)

Abstraction

Karamatsu, T. et al. Iconify: Converting Photographs into Icons. 2020

Displacement (Labels)

Georeferencing and Map Registration

Inpainting (Lines)

Inpainting (Raster)

3D Reconstruction

Geolocalisation

Geographic Entity Extraction

Object and Phenomenon Detection

Remote Sensing

Cleaning and Conflation

Processing Workflows

Record Linkage (Addresses)

Record Linkage (Toponyms)

Data Structures

Wayfinding and Routing

Recommender Systems

Risk Prevention

Modeling and Simulations (Physical Geography)

Modeling and Simulations (Human Geography)

Ethics

Remember, this is just a starting point. Explore these resources, search for specific topics within GeoAI, and contribute your own findings to broaden the knowledge base of this rapidly evolving field!

So far, only research works applying deep learning architectures have been considered but not any traditional machine learning algorithms.

Journals