Unmanned aerial vehicles(UAV)for assessment of qualitative classification of Norway spruce in temperate forest stands

作     者：Olga Brovkina Emil Cienciala Peter Surový Přemysl Janata 

作者机构：Global Change Research Institute(CzechGlobe)CASBrnoCzech Republic Department of Ecosystem AnalysesInstitute of Forest Ecosystem Research(IFER)Jilove u PrahyCzech Republic Department of Forest ManagementCzech University of Life SciencesPragueCzech Republic Department of Forest Management and Applied GeoinformaticsMendel University in BrnoBrnoCzech Republic 

出 版 物：《Geo-Spatial Information Science》 (地球空间信息科学学报（英文）)

年 卷 期：2018年第21卷第1期

页      面：12-20页

核心收录：

学科分类：08[工学] 082503[工学-航空宇航制造工程] 0825[工学-航空宇航科学与技术] 

基　　金：This work was supported by the Ministry of Education,Youth and Sports of the Czech Republic within the National Programme for Sustainability I[grant number LO1415] partly by EEA Grants if Iceland,Liechtenstein and Norway[grant number EHP-CZ02-OV-1-019-2014] 

主　　题：Remote sensing species classification spruce health indicator Unmanned Aerial System(UAS) 

摘      要：The study investigates the potential of UAV-based remote sensing technique for monitoring of Norway spruce health condition in the affected forest *** objectives are:(1)to test the applicability of UAV visible an near-infrared(VNIR)and geometrical data based on Z values of point dense cloud(PDC)raster to separate forest species and dead trees in the study area;(2)to explore the relationship between UAV VNIR data and individual spruce health indicators from field sampling;and(3)to explore the possibility of the qualitative classification of spruce health *** based on NDVI and PDC raster was successfully applied for separation of spruce and silver fir,and for identification of dead tree *** between common beech and fir was distinguished by the object-oriented image *** was able to identify the presence of key indicators of spruce health,such as mechanical damage on stems and stem resin exudation linked to honey fungus infestation,while stem damage by peeling was identified at the significance *** results contributed to improving separation of coniferous(spruce and fir)tree species based on VNIR and PDC raster UAV data,and newly demonstrated the potential of NDVI for qualitative classification of spruce *** proposed methodology can be applicable for monitoring of spruce health condition in the local forest sites.