Background. The city is not a propitious environment for the growth of trees. The authors attempted to solve the problem which anthropogenic areas of uniform function may have negative influence on the development of trees. Due to the diversity of tree species and their different environmental requirements the study was a preliminary overview of their health, allowing for the direct neighbourhood of wooded areas.
Material and methods. The research was conducted in Jakubowo Park in Olsztyn, which is the oldest park in the city. At the first stage of the study the authors described the health of the trees according to their age and species. The research involved preparatory work, during which the site was catalogued by means of a calliper, measuring tape and altimeter. The results were used to make a map and inventory table of the area. The visualisation resulted in a map showing health classes of the tree stand. At the second stage of the study the correlation between the location of tree stands in different health states and the neighbouring areas with separate functions was investigated. GIS tools were used to locate trees in different health states. GIS software also enabled identification of anthropogenic areas in direct neighbourhood of the stand. QGis and Statistica software was used for all spatial analyses.
Results. The diagrams of internal relationships between variables show that the most healthy specimens could be found among hawthorns (Crataegus ×media Bechst.) and rowans (Sorbus aucuparia L.). Silver birches (Betula pendula Roth), red oaks (Quercus rubra L.), common oaks (Quercus robur L.), ashes (Fraxinus excelsior L.), ash-leaved maples (Acer negundo L.), common maples (Acer platanoides L.) and small-leaved limes (Tilia cordata Mill.) were in the poorest health, because their medians showed the first, poorest health class.
Conclusions. The correlation analysis showed that the overall health of the trees was better when they stood closer to public recreational areas. There was a separate correlation in the case of areas under standing water, e.g. ponds. Trees growing at longer distances from ponds were in worse health.
|MLA||Adamska, Daria, and Cezary Kowalczyk. "Analiza GIS oraz metody statystyczne rozmieszczenia drzew – przykład parku Jakubowo." Nauka Przyr. Technol. 11.2 (2017): 185-195. http://dx.doi.org/10.17306/J.NPT.00180|
|APA||Daria Adamska, Cezary Kowalczyk (2017). Analiza GIS oraz metody statystyczne rozmieszczenia drzew – przykład parku Jakubowo. Nauka Przyr. Technol. 11 (2), 185-195 http://dx.doi.org/10.17306/J.NPT.00180|
|ISO 690||ADAMSKA, Daria, KOWALCZYK, Cezary. Analiza GIS oraz metody statystyczne rozmieszczenia drzew – przykład parku Jakubowo. Nauka Przyr. Technol., 2017, 11.2: 185-195. http://dx.doi.org/10.17306/J.NPT.00180|
Katedra Planowania i Inżynierii Przestrzennej
Uniwersytet Warmińsko-Mazur?ski w Olsztynie
ul. Prawocheńskiego 15
e-mail: daria.adamska@uwm. edu.pl