Proceedings of International Conference on Applied Innovation in IT  ·  2026/06/12  ·  Vol. 14  ·  Issue 3  ·  pp. 803–824
Artificial Intelligence and Big Data as a Key Driver of Digitalization in Natural Resource Management in Central Asian Countries
Saodat Sharipova, Sharifjon Pulatov, Nodira Yuldashova, Marina Kozlova, Aizat Uryustyumova, Тuymurod Sadullaev, Feruza Murtazaeva and Gulbahor Zaynobiddinova
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Abstract
The digitalization of natural resource management is becoming a key factor in enhancing the sustainability of socio-economic development under conditions of global environmental threats and increasing anthropogenic pressure. For the countries of Central Asia, characterized by a high dependence on water and land resources, the transboundary nature of water systems, and institutional fragmentation in governance structures, the implementation of digital transformation is of particular relevance. The aim of this study is to provide a comprehensive scientific assessment of the potential of Artificial Intelligence (AI) and Big Data technologies in advancing the digitalization of natural resource management in the region. The methodological framework integrates satellite-based Earth observation data, climate reanalysis datasets, hydrological monitoring records, and administrative data within a Data Lake-Lakehouse architecture. Machine learning and deep learning methods, including ensemble models and recurrent neural networks, were employed for analysis and forecasting, complemented by explainable AI tools (SHAP). Spatio-temporal validation and uncertainty assessment ensured the robustness and reliability of the obtained results. The findings demonstrate that intelligent models significantly improve the accuracy of hydrological and climatic forecasting compared to traditional statistical approaches, while also identifying high-risk zones of water scarcity, land degradation, and desertification. Spatial analysis of land-use change and NDVI dynamics confirmed substantial land cover transformations driven by the combined effects of climatic and anthropogenic factors. The application of SHAP analysis enhanced model transparency and enabled the linkage between key contributing factors and policy-relevant management decisions. Within the discussion framework, a roadmap for implementing digital platforms for natural resource governance is proposed, along with practical recommendations at both national and regional levels. The results confirm that digitalization of natural resource management based on Big Data and Artificial Intelligence can serve as an effective instrument for strengthening resilience, adaptability, and policy coherence in Central Asian countries.
Keywords
Digital Governance Big Data Artificial Intelligence Natural Resources Water Scarcity Land Use Central Asia Data-Driven Management Sustainable Development.
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