Drone remote sensing in urban forest management: A case study |
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| Institution: | 1. University of Tennessee, 1621 Cumberland Avenue, 602 Strong Hall, Knoxville, TN 37996, USA;2. National Institute for Mathematical and Biological Synthesis, 1122 Volunteer Blvd., Suite 106, Knoxville, TN 37996-3410, USA;3. University of Tennessee Institute of Agriculture, 2505 E J Chapman Dr., 427 Plant Biotechnology Building, Knoxville, TN 37996, USA;4. Earth & Planetary Sciences, University of Tennessee, 1621 Cumberland Avenue, 633 Strong Hall, Knoxville, TN 37996, USA;1. Department of Landscape, Southwest Jiaotong University, Chengdu 610031, Sichuan, China;2. School of Life Science and Engineering, Southwest Jiaotong University, Chengdu 610031, Sichuan, China;1. Centre for Environmental Research and Impact Studies, University of Bucharest, 1 Nicolae Balcescu Blvd., 010041 Bucharest, Romania;2. Department of Environmental Science, Faculty of Environmental Science and Engineering, Babes-Bolyai University, 30 Fantanele St., 400535 Cluj-Napoca, Romania;3. Chair for Strategic Landscape Planning and Management, School of Life Sciences Weihenstephan, Technical University of Munich, 6 Emil-Ramann St., 85354 Freising, Germany;1. The Centre for Modern Chinese City Studies, East China Normal University, Shanghai, China;2. Research Center for China Administrative Division, East China Normal University, Shanghai, China;3. Future City Lab, East China Normal University, Shanghai, China;4. Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China;5. Faculty of Land Resources Engineering, Kunming University of Science and Technology, China;1. School of Geography and Ocean Science, Nanjing University, Xianlin Ave.163, 210023 Nanjing, China;2. School of Architecture and Urban Planning, Nanjing University, No. 22, Hankou Road, 210093 Nanjing, China;3. School of Arts, Media and Engineering, Arizona State University, 950 S. Forest Mall, Stauffer B258, 85281 Tempe, Arizona, USA;1. School of Urban Design, Wuhan University, Wuhan, China;2. College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou, China;3. College of Architecture, Changsha University of Science & Technology, Changsha, China |
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| Abstract: | We applied drone remote sensing to identify relationships between key forest health indicators collected in the field and four Vegetative Indices (VI) to improve conservation management of urban forests. Key indicators of urban forest health revealed several areas of conservation concern including a majority of overstory trees in moderate to severe decline, canopy gaps, anthropogenic dumping, vines overtaking the forest canopy, and invasion by non-native plant species. We found plot-level vegetation index (VI) values of NDVI, NDRE, GNDVI, and GRVI calculated from drone imagery are significantly related to the impact of several of these ecological concerns as well as metrics of forest composition and equitability. Despite the small number of plots, too few to provide a general predictive framework, these findings indicate a substantial potential for drone remote sensing as a low-cost, efficient tool for urban forest management. We discuss how our findings can advance urban forest management and discuss challenges and opportunities for future drone VI research in urban natural areas. |
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| Keywords: | Urban Forest Drone Remote sensing NDVI Vegetation index |
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