Original Articles Vol. 3 No. 3 (2026): Bioscience Insights Published 2026-10-13

GEOSPATIAL DECISION SUPPORT SYSTEMS FOR SUSTAINABLE LAND USE, NATURAL RESOURCE MANAGEMENT, AND ENVIRONMENTAL PLANNING

Authors

  • Sher Muhammad Ghoto Assistant Professor (PhD in Environmental Engineering) Department of Mechanical Engineering Quaid-e-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan Pakistan Author
  • Habibullah Abbasi Assistant Professor Center for Environmental Science University of Sindh, Jamshoro, Sindh, Pakistan Pakistan Author
  • Nazir Khan M.Phil. Scholar Center for Environmental Science University of Sindh, Jamshoro, Sindh, Pakistan Pakistan Author
  • Rabia Chhachhar M.Phil. Scholar Center for Environmental Science University of Sindh, Jamshoro, Sindh, Pakistan Pakistan Author
  • Asad Ali Ghanghlo Visiting Faculty Member Department of Energy and Environment Sindh Agriculture University, Tandojam, Sindh, Pakistan Pakistan Author
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Abstract

Spatial decision‑making is essential for land use, natural resource management and environmental planning. However the usual Geographic Information Systems (GIS) are mainly descriptive and inventory‑focused which limits their ability to solve complex multi‑stakeholder problems. This review brings together the theory, methods, real‑world uses and new technology of Geospatial Decision Support Systems (SDSS). A careful look at the literature shows that SDSS has changed through four architectural styles: from single‑user desktop programs to client‑server Web‑GIS to cloud‑based service‑oriented systems and now to AI‑powered systems that use machine learning and satellite data. The review also studies Spatial Multi‑Criteria Decision Analysis (S‑MCDA) methods. These include Weighted Linear Combination, Analytic Hierarchy Process, Analytic Network Process, TOPSIS, VIKOR ELECTRE and fuzzy‑hybrid models. For each method the review presents the math for standardising criteria checking consistency and measuring differences. In practice SDSS is useful in areas: choosing sites for renewable energy filling gaps in cities while protecting heritage, precision farming, managing watersheds together and reducing disaster risk. Despite these gains problems remain. These problems are uncertainty in data changes in space over time limits in capacity and the heavy compute load of high‑dimensional data. Looking ahead the trend is toward digital twins that use IoT sensor streams Geo‑AI that can talk with generative language interfaces and cloud‑based platforms that let many people take part in spatial decisions. The review ends by stating that making AI‑enhanced participatory SDSS frameworks a normal part of practice is key, to land care, stronger climate resilience and fair resource control.

Keywords

  • Spatial Decision Support Systems; GIS; Spatial Multi-Criteria Decision Analysis; Sustainable Land Use; Natural Resource Management; Environmental Planning; Cloud-Native Geospatial Architecture; Geo-AI

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