International Journal For Multidisciplinary Research

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GeoAI-Driven Integration of Remote Sensing and Geostatistics for Spatiotemporal Intelligence Modeling in Türkiye

Author(s) Mr. AYBARS OZTUNA
Country United Kingdom
Abstract Integrating Multi-resolution Remote Sensing, Geostatistical Modeling, and Deep Learning to Generate Spatiotemporal Intelligence Products for Türkiye Türkiye. Regional-scale geospatial pipelines largely exist in silos between modalities and platforms, preventing truly integrated and discovery-geoscience workflows which capitalize on the strengths of each data source and analysis method. Geointelligence (geoint) workflows stand to benefit immensely from such integration to improve intelligence product generation throughput and quality. Here, we present the inaugural GeoAI Integration Triad (satellite remote sensing, geostatistics, and deep learning) capable of generating actionable spatiotemporal intelligence (STINT) products in Türkiye. We benchmark our proposed GeoAI IT across diverse land cover regimes of interest spanning hyper-urbanization (Istanbul), mixed urban and agricultural development (Ankara), drought mitigation/afforestation (Konya), cold-case georeconstruction (Kahramanmaraş), and rapid housing development (Osmaniye). Satellite datasets comprise Sentinel, Landsat, and MODIS bands while geostatistical techniques comprise Bayesian and deterministic interpolation via DeepKriging to model nonlinear, non-stationary signals. We achieve DL-based land use/land cover (LULC) classification accuracies of up to 93.3% and reduce interpolation error by up to 25% through task-specific data fusion. These land cover change projections through 2040 are intended to support national policy decisions, encompassing environmental oversight, plans for mitigating natural disaster risks, and the creation of climate-resilient housing, all while safeguarding vital LULC areas as Turkey builds out its GEOINT framework.
Keywords GeoAI, Spatiotemporal Intelligence, Remote Sensing, DeepKriging, Türkiye, Urban Expansion, Land Use Change
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-06-13
DOI https://doi.org/10.36948/ijfmr.2026.v08i03.81285
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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