Department Chair
Alexander Karatayev, Ph.D., Professor of Biology and Director of the Great Lakes Center
Date of Award
12-2015
Access Control
Open Access
Degree Name
Great Lakes Ecosystem Science
Department
Great Lakes Center
Advisor
Tao Tang, Ph.D., Professor of Geography
Department Home page
http://greatlakescenter.buffalostate.edu/
First Reader
Tao Tang, Ph.D., Professor of Geography
Second Reader
Kelly M. Frothingham, Ph.D., Chair and Professor of Geography and Planning
Third Reader
Daniel L. Potts, Ph.D., Associate Professor of Biology
Abstract
Abstract:
Fallopia japonica (Japanese knotweed) is a perennial herbaceous plant that is native to East Asia. It is considered as one of the worst invasive species worldwide because of its serious impact on biological diversity and human activities (Lowe et al., 2001). Once established, Japanese knotweed forms dense stands that shade and crowd out native plant species. The objectives of this research were to verify and confirm the distribution of Japanese knotweed as published online by the New York Department of Environmental Conservation (DEC) – iMap and to identify the geographic areas of spreading and the local habitat conditions. In this research, we apply an unmanned helicopter with multiple sensors including digital camera, thermometer and relative humidity sensor to survey the patches of F.japonica and its three-dimensional (3D) habitat conditions. The areas of each of the patch surveyed were identified and delineated in polygons applying ERDAS Imagine and ArcGIS software. To identify the local habitat conditions, the shade cover and distance to nearest water body were analyzed by using traditional statistical methods. And the distributions of temperature and relative humidity were analyzed in three-dimensional (3D) method in GIS environment.
Recommended Citation
Zhang, Jiazhen, "Spatial Analysis of Distributions and Habitat Conditions of Fallopia japonica (Japanese Knotweed) Invasive Species Applying Unmanned Helicopter Remote Sensing" (2015). Great Lakes Center Masters Theses. 1.
https://digitalcommons.buffalostate.edu/greatlakes_theses/1
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