Creating Choropleth Maps by Artificial Intelligence—Case Study on ChatGPT-4

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F25%3A73634076" target="_blank" >RIV/61989592:15310/25:73634076 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2220-9964/14/12/486" target="_blank" >https://www.mdpi.com/2220-9964/14/12/486</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/ijgi14120486" target="_blank" >10.3390/ijgi14120486</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Creating Choropleth Maps by Artificial Intelligence—Case Study on ChatGPT-4

Popis výsledku v původním jazyce

This study explores the potential of ChatGPT-4, an AI-powered large language model, to generate thematic maps and compare its outputs to the traditional method in which maps are produced manually by humans using GIS software. Prompt engineering is a crucial methodology of large language models that can enhance output quality. The main objective of this study is to assess the capability of AI-generated maps and to compare the quality with a traditional method. The study evaluates two prompt patterns: basic (zero-shot prompts) and advanced (Cognitive Verifier and Question Refinement). The performance of AI-generated maps is assessed based on attempts, errors, incorrect results, and map completeness. The final stage involved evaluating AI-generated maps against cartographic rules to assess their suitability. ChatGPT-4 performs well in generating suitable choropleth maps but faced challenges in understanding the prompts and potential errors in the generated code. Advanced prompts reduced errors and improved the quality of outputs, particularly for complex map elements. This paper enhances the understanding of AI’s role in cartography and further research in automated cartography. The study assesses cartographic aspects, offering insights into the strengths and limitations of AI in cartography, illustrating how large language models can process geospatial data and adhere to cartographic principles. The study also paves the way for future innovations in automated geovisualization.

Název v anglickém jazyce

Creating Choropleth Maps by Artificial Intelligence—Case Study on ChatGPT-4

Popis výsledku anglicky

This study explores the potential of ChatGPT-4, an AI-powered large language model, to generate thematic maps and compare its outputs to the traditional method in which maps are produced manually by humans using GIS software. Prompt engineering is a crucial methodology of large language models that can enhance output quality. The main objective of this study is to assess the capability of AI-generated maps and to compare the quality with a traditional method. The study evaluates two prompt patterns: basic (zero-shot prompts) and advanced (Cognitive Verifier and Question Refinement). The performance of AI-generated maps is assessed based on attempts, errors, incorrect results, and map completeness. The final stage involved evaluating AI-generated maps against cartographic rules to assess their suitability. ChatGPT-4 performs well in generating suitable choropleth maps but faced challenges in understanding the prompts and potential errors in the generated code. Advanced prompts reduced errors and improved the quality of outputs, particularly for complex map elements. This paper enhances the understanding of AI’s role in cartography and further research in automated cartography. The study assesses cartographic aspects, offering insights into the strengths and limitations of AI in cartography, illustrating how large language models can process geospatial data and adhere to cartographic principles. The study also paves the way for future innovations in automated geovisualization.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

ISPRS International Journal of Geo-Information

ISSN

2220-9964

e-ISSN

—

Svazek periodika

14

Číslo periodika v rámci svazku

12

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

30

Strana od-do

"486-1"-"486-30"

Kód UT WoS článku

001646748100001

EID výsledku v databázi Scopus

2-s2.0-105025956976