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DOI: 10.15862/07NZOR425 (https://doi.org/10.15862/07NZOR425)

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Fleenko A.S. Identification of objects with implicit spatial localization in spatial modelling and visualization using geographic information systems (GIS). Russian journal of resources, conservation and recycling. 2025; 12(4). Available at: https://resources.today/PDF/07NZOR425.pdf (in Russian). DOI: 10.15862/07NZOR425

Identification of objects with implicit spatial localization in spatial modelling and visualization using geographic information systems (GIS)

Fleenko Anton Sergeevich
«Roszheldorproject» JSC, Moscow, Russia
Designing-And-Survey Institute of Railway Electrification and Power Installations «Transelektroproject»
E-mail: fleenkospb@mail.ru
ORCID: https://orcid.org/0000-0002-2829-9361

Abstract. The article, prepared as part of a dissertation research on developing a methodology for 3D spatial modelling and visualization of a specific type of natural and anthropogenic environmental objects using geographic information systems (GIS), examines and characterizes the identification features of these modelling objects. The advancement of computer technologies naturally leads to the improvement of modelling tools and methods. A special role is played by the creation of cartographic models through GIS. It has been established that certain natural and anthropogenic objects cannot be adequately modelled or visualized using standard methods due to the unavailability of their shape and dimensions for direct measurement. Their preliminary identification and separation from the surrounding environment is a crucial task for enhancing spatial modelling and mapping technologies that utilize GIS. To identify these objects, the author proposes a system of three criteria, including the criterion of spatial localization, the criterion of implicit localization and the criterion of spatial configuration. A key feature is parametric (essential) demarcation — a method for determining object boundaries based on measurements of key parameters in accordance with research classifications. Examples of objects classified as this specific type include: airborne impurity clouds, placer deposits of valuable minerals (or useful components), soil and ground contamination bodies. The conducted research aims to develop GIS tools and improve the accuracy of modelling spatially distributed objects that are difficult to identify.

Keywords: system analysis; modeling method; geoinformation systems; spatial modelling; criteria‑based selection; cartographic models; geodata

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