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Tytuł pozycji:

THE USE OF OPEN SOURCE SOFTWARE FOR MONITORING BEE DIVERSITY IN NATURAL SYSTEMS: THE BEEMS PROJECT

Tytuł:
THE USE OF OPEN SOURCE SOFTWARE FOR MONITORING BEE DIVERSITY IN NATURAL SYSTEMS: THE BEEMS PROJECT
Autorzy:
P. Dabove
V. Di Pietra
Temat:
Technology
Engineering (General). Civil engineering (General)
TA1-2040
Applied optics. Photonics
TA1501-1820
Źródło:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-4-W1-2022, Pp 111-118 (2022)
Wydawca:
Copernicus Publications, 2022.
Rok publikacji:
2022
Kolekcja:
LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Applied optics. Photonics
Typ dokumentu:
article
Opis pliku:
electronic resource
Język:
English
ISSN:
1682-1750
2194-9034
Relacje:
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVIII-4-W1-2022/111/2022/isprs-archives-XLVIII-4-W1-2022-111-2022.pdf; https://doaj.org/toc/1682-1750; https://doaj.org/toc/2194-9034
DOI:
10.5194/isprs-archives-XLVIII-4-W1-2022-111-2022
Dostęp URL:
https://doaj.org/article/c4ea66614a3842ecb21beef1eb1b8170  Link otwiera się w nowym oknie
Numer akcesji:
edsdoj.4ea66614a3842ecb21beef1eb1b8170
Czasopismo naukowe
This work wants to highlight the results obtained during the BEEMS (Monitoring Bee Diversity in Natural System) project, which the main goal was to answer the following question: Which biotic and abiotic indicators of floral and nesting resources best reflect the diversity of bee species and community composition in the Israeli natural environment? The research was oriented towards the cost-effectiveness analysis of new aerial geomatics techniques and classical ground-based methods for collecting the indicators described above, based only on open-source software for data analysis. Two complementary study systems in central Israel have been considered: the Alexander Stream National Park, an area undergoing an ecological restoration project in a sandy ecosystem, and the Judean foothills area, to the South of Tel Aviv. In each study system, different surveys of bees, flowers, nesting substrates and soil, using classical field measurement methods have been conducted. Simultaneously, an integrated aero photogrammetric survey, acquiring different spectral responses of the land surface by means of Uncrewed Aerial Vehicle (UAV) imaging systems have been performed. The multispectral sensors have provided surface spectral response out of the visible spectrum, while the photogrammetric reconstruction has provided three-dimensional information. Thanks to Artificial Intelligence algorithms and the richness of the data acquired, a methodology for Land Cover Classification has been developed. The results obtained by ground surveys and advanced geomatics tools have been compared and overlapped. The results are promising and show a good fit between the two approaches, and high performance of the geomatics tools in providing valuable ecological data.

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