Artificial Intelligence and Landscape Sustainability: Comparative Insights from Urban Sports and Recreation Areas in Turkey and Lithuania

Dalia Perkumienė (), Ahmet Atalay (), Daiva Šiliekienė and Laima Česonienė
Additional contact information
Dalia Perkumienė: Department of Business Creation and Management, SMK College of Applied Sciences, Nemuno g. 2, 91199 Klaipeda, Lithuania
Ahmet Atalay: Department of Sport Management, Sport Science Faculty, Ardahan University, 75000 Ardahan, Turkey
Daiva Šiliekienė: Forestry Faculty, Department of Environment and Ecology, Vytautas Magnus University, 44221 Kaunas, Lithuania
Laima Česonienė: Forestry Faculty, Department of Environment and Ecology, Vytautas Magnus University, 44221 Kaunas, Lithuania

Land, 2025, vol. 14, issue 12, 1-39

Abstract: This study examines the integration of artificial intelligence (AI)-based strategies within the framework of landscape sustainability science and urban ecology, focusing on urban sports and recreation areas in Turkey and Lithuania. In the era of sustainable urban transformation, AI technologies offer new opportunities for maintaining ecological integrity, enhancing green infrastructure connectivity, and supporting adaptive management of urban ecosystems. The research aims to comparatively analyze the role and effectiveness of AI applications—such as intelligent waste management, predictive maintenance, and spatial planning tools—in promoting clean, safe, and ecologically resilient environments. A qualitative design was employed, and data were collected through semi-structured interviews with 30 experts, including local administrators, facility managers, environmental professionals, AI specialists, and academics from both countries. Thematic analysis using NVivo revealed key themes linking AI functions to ecological outcomes, including improved resource efficiency, habitat connectivity, and data-informed governance. Results show that Lithuania’s institutionalized green infrastructure facilitates multi-scale AI adoption, while Turkey’s evolving policy framework presents significant potential for system integration. The study emphasizes the necessity of embedding AI-driven ecological indicators into landscape-scale planning and developing an interdisciplinary governance model to achieve sustainable, resilient, and inclusive urban ecosystems.

Keywords: artificial intelligence (AI); landscape sustainability; urban ecology; green infrastructure; waste management; sports and recreation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/14/12/2330/pdf (application/pdf)
https://www.mdpi.com/2073-445X/14/12/2330/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:14:y:2025:i:12:p:2330-:d:1804461

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().