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Information × Registration Number 0226U002506, (0122U002269) , R & D reports Title Monitoring of biotic and habitat diversity using GIS and remote sensing data popup.stage_title Моніторинг біотичного та оселищного різноманіття з використанням ГІС та даних дистанційного зондування Землі Head Harbar Oleksandr V., Доктор біологічних наук Registration Date 26-02-2026 Organization Zhytomyr Ivan Franko State University popup.description1 Сollection and analysis of spatial data on common, adventive and rare components of biota and their habitats, assessment and forecasting of their state using geographic information systems and remote sensing data popup.description2 The ob. of research is the transformation processes of biotic and habitat diversity of ecosystems. The subject of research is the regularities of spatio-temporal dynamics habitats, the structure of soil fauna complexes and predictive distribution models species. The purpose of the study: Collection and analysis of spatial data, assessment and forecasting their condition using geoinformation systems and data remote sensing of the Earth. Comparative-geographical, DZZ methods, GIS modeling, were used synphytoindication modeling, statistical methods. For the first time, an integrated monitoring model of pedofauna was developed, which combines ground accounts with satellite spectral predictors; new data were obtained on the 30-year dynamics of settlements in the Kozachelager Arena; models of anthropotolerance of plant communities are mathematically substantiated. The results are covered in 9 scientific publications. A critical reduction in the area of water habitats (by 2.5 times) and doubling of open sand areas in southern Ukraine; 10 species identified Lumbricidae in urban ecosystems and the gradient of their changes along highways; forecast maps of the distribution of the invasive species were built Opuntia humifusa in Europe. The results allow the process to be automated environmental monitoring of large areas; developed models can be used to assess damage to ecosystems and plan activities with reclamation of landscapes. The obtained results are recommended to be used in environmental management, state administration in the field of protection environment, activities of nature reserve fund facilities, educational process in higher education institutions. The effectiveness of the combination of remote sensing and machine learning for biota monitoring. It is advisable to continue research in the direction of creation automated system for monitoring PZF territories using neural network algorithms for real-time recognition of habitat types. Product Description popup.authors Onishchuk Iryna Petrivna Vasylenko Olga Mykolaivna Garbar Diana A Ivan Khomiak popup.nrat_date 2026-02-26 Close