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Identifying Tree Species in a Warm-Temperate Deciduous Forest by Combining Multi-Rotor and Fixed-Wing Unmanned Aerial Vehicles

文献类型：期刊论文

作者Shi, Weibo2; Wang, Shaoqiang3,4; Yue, Huanyin2,5; Wang, Dongliang2,5; Ye, Huping2,5; Sun, Leigang1,6; Sun, Jia; Liu, Jianli7; Deng, Zhuoying; Rao, Yuanyi
刊名DRONES
出版日期2023-06-01
卷号7期号:6页码:353
关键词fixed-wing UAVs multi-rotor UAVs semantic segmentation method tree species classification forest inventory
DOI10.3390/drones7060353
产权排序2
文献子类Article
英文摘要Fixed-wing unmanned aerial vehicles (UAVs) and multi-rotor UAVs are widely utilized in large-area (>1 km(2)) environmental monitoring and small-area (<1 km(2)) fine vegetation surveys, respectively, having different characteristics in terms of flight cost, operational efficiency, and landing and take-off methods. However, large-area fine mapping in complex forest environments is still a challenge in UAV remote sensing. Here, we developed a method that combines a multi-rotor UAV and a fixed-wing UAV to solve this challenge at a low cost. Firstly, we acquired small-scale, multi-season ultra-high-resolution red-green-blue (RGB) images and large-area RGB images by a multi-rotor UAV and a fixed-wing UAV, respectively. Secondly, we combined the reference data of visual interpretation with the multi-rotor UAV images to construct a semantic segmentation model and used the model to expand the reference data. Finally, we classified fixed-wing UAV images using the large-area reference data combined with the semantic segmentation model and discuss the effects of different sizes. Our results show that combining multi-rotor and fixed-wing UAV imagery provides an accurate prediction of tree species. The model for fixed-wing images had an average F1 of 92.93%, with 92.00% for Quercus wutaishanica and 93.86% for Juglans mandshurica. The accuracy of the semantic segmentation model that uses a larger size shows a slight improvement, and the model has a greater impact on the accuracy of Quercus liaotungensis. The new method exploits the complementary characteristics of multi-rotor and fixed-wing UAVs to achieve fine mapping of large areas in complex environments. These results also highlight the potential of exploiting this synergy between multi-rotor UAVs and fixed-wing UAVs.
WOS关键词IMAGERY ; SYSTEMS ; CLASSIFICATION ; POPULATIONS ; CLIMATE ; PATTERN
WOS研究方向Remote Sensing
WOS记录号WOS:001014250500001
出版者MDPI
源URL[http://ir.igsnrr.ac.cn/handle/311030/194397]  
专题生态系统网络观测与模拟院重点实验室_外文论文
作者单位1.Hebei Acad Sci, Inst Geog Sci, Shijiazhuang 050011, Peoples R China
2.Chinese Univ Geosci, Sch Geog & Informat Engn, Hubei Key Lab Reg Ecol & Environm Change, Wuhan 430074, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modelling, Beijing 100101, Peoples R China
5.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
6.Civil Aviat Adm China, Key Lab Low Altitude Geog Informat & Air Route, Beijing 100101, Peoples R China
7.Hebei Technol Innovat Ctr Geog Informat Applicat, Shijiazhuang 050011, Peoples R China
8.China TOPRS Technol Co Ltd, Beijing 100039, Peoples R China
9.China Aero Geophys Survey & Remote Sensing Ctr Nat, Beijing 100083, Peoples R China
推荐引用方式
GB/T 7714		 Shi, Weibo,Wang, Shaoqiang,Yue, Huanyin,et al. Identifying Tree Species in a Warm-Temperate Deciduous Forest by Combining Multi-Rotor and Fixed-Wing Unmanned Aerial Vehicles[J]. DRONES,2023,7(6):353.
APA Shi, Weibo.,Wang, Shaoqiang.,Yue, Huanyin.,Wang, Dongliang.,Ye, Huping.,...&Sun, Xiyong.(2023).Identifying Tree Species in a Warm-Temperate Deciduous Forest by Combining Multi-Rotor and Fixed-Wing Unmanned Aerial Vehicles.DRONES,7(6),353.
MLA Shi, Weibo,et al."Identifying Tree Species in a Warm-Temperate Deciduous Forest by Combining Multi-Rotor and Fixed-Wing Unmanned Aerial Vehicles".DRONES 7.6(2023):353.

入库方式： OAI收割

来源：地理科学与资源研究所

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