KARTOGRAFIYA VA KADASTR SOHASIDA GEOFAZOVIY FOUNDATION MODELLAR: QO‘LLASH IMKONIYATLARI VA RIVOJLANISH ISTIQBOLLARI
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kartografiya, kadastr, sun'iy intellekt (SI), geofazoviy sun'iy intellekt (GeoAI), geofazoviy foundation model (GeoFM), foundation model, masofadan zondlash, sun'iy yo'ldosh tasvirlari, aerokosmik tasvirlar, GIS, geofazoviy ma'lumotlar, avtomatik segmentatsiya, obyektlarni aniqlash, geofazoviy tahlil, raqamli xaritalash, chuqur o'rganish (Deep Learning), mashinali o'rganish (Machine Learning), katta til modellari (LLM), multimodal modellar, geofazoviy ma'lumotlar bazasi.Abstrak
Ushbu tezisda kartografiya va geodeziya sohasida sun'iy intellekt texnologiyalarining yangi bosqichi hisoblangan geofazoviy foundation modellar (Geo Foundation Models, GeoFM) ning mazmun-mohiyati, rivojlanish bosqichlari, zamonaviy holati, amaliy qo'llanilish imkoniyatlari hamda istiqbollari tahlil qilingan. Shuningdek, dunyo miqyosida ushbu yo'nalishda olib borilayotgan ilg'or ilmiy tadqiqotlar va ularning natijalari umumlashtirilib, ularni O‘zbekiston Respublikasi kartografiya va kadastr tizimiga joriy etishning ilmiy, texnologik hamda huquqiy jihatlari yoritilgan. Tadqiqot davomida GeoFM texnologiyalarini milliy geofazoviy axborot tizimlariga integratsiya qilishning mavjud muammolari, istiqbollari va kutilayotgan samaradorligi ilmiy asosda baholangan.
Iqtiboslar
O‘zbekiston Respublikasi Prezidentining “Sun’iy intellekt texnalogiyalarini 2030-yilga qadar rivojlantirish strategiyasini taqsdiqlash to‘g‘risida”gi 2024-yil 14-oktyabrdagi PQ-358-son qarori.
Mai G., Huang W., Sun J. et al. On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper). ACM Transactions on Spatial Algorithms and Systems, 2024, Vol. 10, No. 2, Article 11. DOI: 10.1145/3653070.
Mai G. Geo-Foundation Models. Wiley Encyclopedia of GIS, 2024. DOI: 10.1002/9781118786352.wbieg2206.
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Mai G., Huang W., Sun J., et al. On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper). ACM Transactions on Spatial Algorithms and Systems, 2024.
Mai G. Geo-Foundation Models. Wiley Encyclopedia of GIS, 2024.
Hsu C.-Y., Li W., Wang S. Geospatial Foundation Models for Image Analysis: Evaluating and Enhancing NASA–IBM Prithvi's Domain Adaptability. International Journal of Geographical Information Science, 2024.
Szwarcman D., et al. Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications. arXiv, 2024.
Klemmer K., et al. SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery. NeurIPS, 2024.
Clay Foundation Team. Clay Foundation Model for Earth Observation. Radiant Earth Foundation, 2024.
Esri Research. GeoVLM: Vision-Language Foundation Model for Geospatial Artificial Intelligence. 2025.
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