{
  "abstract": "Land-use planning in ecologically sensitive landscapes requires balancing biodiversity conservation, ecosystem service provision, agricultural production, settlement expansion, and infrastructure demand within a single spatial system. This challenge is particularly significant in Mediterranean environments, where long-term land transformations and increasing development pressures intensify conflicts among competing land-use priorities. Accordingly, the present study develops an integrated spatial zoning and decision-support framework for Osmaniye Province, southern Türkiye. The framework integrates fuzzy multi-criteria evaluation, CatBoost-based machine learning, SHAP-based interpretability, and NSGA-II multi-objective optimization. The workflow followed a sequential decision process in which an expert-derived zoning surface was first established through fuzzy evaluation, reconstructed from continuous spatial predictors using CatBoost, interpreted through SHAP, and refined through NSGA-II under explicit spatial constraints. By using the expert-derived zoning surface as the learning target, the CatBoost stage aimed to evaluate the internal consistency and spatial learnability of the planning logic within a present-day zoning context. The results indicated that the integrated framework distinguished conservation, controlled-use, and development priorities while identifying the key environmental and anthropogenic drivers shaping class-specific zoning outcomes. The final zoning structure allocated 37.9% of the study area to conservation, 43.6% to controlled use, and 18.5% to development. The study shows that by including a transitional zone with varying proportions of conservation, controlled use, and development, a more balanced distribution among the three goals can be achieved compared to a fixed partition into these three zones. The findings further demonstrate that this approach is more effective than current zoning, which does not accommodate such trade-offs.",
  "abstract_shown": true,
  "affiliations": [
    "Transportation and Traffic Services Program, Department of Transportation Services, Vocational School of Technical Sciences, Bitlis Eren University, Bitlis 13100, Türkiye",
    "Department of Geography, Faculty of Arts and Science, Inonu University, Malatya 44280, Türkiye",
    "Department of Forest Engineering, Faculty of Forestry, Bartin University, Agdaci Campus, Bartin 74100, Türkiye",
    "Department of Geography, Faculty of Humanities and Social Sciences, Manisa Celal Bayar University, Manisa 45140, Türkiye",
    "Department of Forest Engineering, Faculty of Forestry, Bartin University, Bartin 74100, Türkiye"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Fatih Adıgüzel",
      "orcid": "0000-0002-5978-2495"
    },
    {
      "affs": [
        1
      ],
      "name": "Enes Karadeniz",
      "orcid": "0000-0003-0757-8553"
    },
    {
      "affs": [
        2
      ],
      "name": "Tuna Emir",
      "orcid": "0000-0003-3205-7258"
    },
    {
      "affs": [
        3
      ],
      "name": "Ferhat Arslan",
      "orcid": "0000-0001-9495-921X"
    },
    {
      "affs": [
        4
      ],
      "name": "Halil Barış Özel",
      "orcid": "0000-0001-9518-3281"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/emdz4r0772f64.bib",
  "cited_by": 11,
  "doi": "10.3390/land15050881",
  "fulltext_url": null,
  "id": "emdz4r0772f64",
  "issns": [
    "2073-445X"
  ],
  "landing_url": "https://doi.org/10.3390/land15050881",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2306|Land Use and Ecosystem Services"
    ]
  ],
  "openalex": "W7162343506",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-05-19",
  "publisher": "Multidisciplinary Digital Publishing Institute",
  "ris": "https://research.draconitic.com/paper/emdz4r0772f64.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:26:58Z",
      "native_id": "W7162343506",
      "source": "openalex",
      "url": "https://doi.org/10.3390/land15050881"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "openalex:2306|Land Use and Ecosystem Services",
      "subfield": "climate"
    }
  ],
  "title": "Balancing Conservation and Development Through Explainable Machine Learning and NSGA-II: A Case Study of Osmaniye",
  "title_text": "Balancing Conservation and Development Through Explainable Machine Learning and NSGA-II: A Case Study of Osmaniye",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T13:20:42Z",
  "url": "https://research.draconitic.com/paper/emdz4r0772f64",
  "venue": "Land",
  "versions": []
}