Registration Number
0226U002506,
(0122U002269)
, R & D reports
Title
Monitoring of biotic and habitat diversity using GIS and remote sensing data
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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
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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
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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
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Onishchuk Iryna Petrivna
Vasylenko Olga Mykolaivna
Garbar Diana A
Ivan Khomiak
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2026-02-26
