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基于无人机和卷积神经网络的林火监测技术研究
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Abstract:
森林火灾是一种严重的自然灾害，且我国地域辽阔、森林面积广阔，对于森林火灾的预警监测需求量巨大。针对我国森林火灾问题，从扩大森林火灾监测范围、提升森林火灾识别响应速度的角度出发，设计了一种基于无人机图像拍摄、利用卷积神经网络对火灾信号进行识别的方案。该方案与传统的人工监控、飞机巡视、卫星火情监控等方案对比后认为具有更低的成本以及更高的效率和安全性。
Forest fire is a serious natural disaster and our country is vast, so the forest area is vast, for the prevention and monitoring of forest fire huge demand. Aiming at the problem of forest fire in China, in order to expand the scope of forest fire monitoring and improve the response speed of forest fire identification, a scheme based on UAV image shooting and using convolutional neural network to identify fire signals is designed. Compared with traditional manual monitoring, aircraft patrol, sat-ellite fire monitoring and other programs, the scheme has higher efficiency and safety and lower cost.
| [1] | Richards, K.R. and Stokes, C. (2004) A Review of Forest Carbon Sequestration Cost Studies: A Dozen Years of Re-search. Climatic Change, 63, 1-48. https://doi.org/10.1023/B:CLIM.0000018503.10080.89 |
| [2] | 国家林业和草原局. 中国森林资源清查报告(2014-2018) [M]. 北京: 中国林业出版社, 2019. |
| [3] | 孙龙, 王千雪, 魏书精, 等. 气候变化背景下我国森林火灾灾害的响应特征及展望[J]. 灾害学, 2014, 29(1): 12-17. |
| [4] | 于诗文, 王秋华. 近年雷击火研究进展综述[J]. 林业调查规划, 2020, 45(2): 71-76, 112. |
| [5] | 李英科, 李全民. 基于卫星数据的森林火灾监测系统探讨[J]. 森林防火, 2019(2): 25-29+43. |
| [6] | 王冬雨. 无线传感器网络在森林火灾监测中的应用研究[D]: [硕士学位论文]. 上海: 上海应用技术大学, 2020. |
| [7] | 陈培昕, 刘嘉新, 蒲先良, 潘治杭. 基于卷积神经网络的林火烟雾识别[J]. 仪表技术, 2019(5): 21-24. |
| [8] | 许明伟, 王东涛, 叶剑华. 基于卷积神经网络图像识别的港口防火系统设计[J]. 天津职业技术师范大学学报, 2019, 29(4): 21-24+31. |
| [9] | Yuan, C., Zhang, Y. and Liu, Z. (2015) A Survey on Technologies for Automatic Forest Fire Monitoring, Detection, and Fighting Using Unmanned Aer-ial Vehicles and Remote Sensing Techniques. Canadian Journal of Forest Research, 45, 783-792. https://doi.org/10.1139/cjfr-2014-0347 |
| [10] | Beard, R.W., McLain, T.W., Nelson, D.B., et al. (2006) Decentralized Cooperative Aerial Surveillance Using Fixed-Wing Miniature UAVs. Proceedings of the IEEE, 94, 1306-1324. https://doi.org/10.1109/JPROC.2006.876930 |
| [11] | Berni, J.A.J., Zarco-Tejada, P.J., Suárez, L., et al. (2009) Ther-mal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring from an Unmanned Aerial Vehicle. IEEE Transactions on Geoscience and Remote Sensing, 47, 722-738. https://doi.org/10.1109/TGRS.2008.2010457 |
| [12] | Li, M.X., Xu, W.J., Xu, K, et al. (2013) Review of Fire Detec-tion Technologies Based on Video Image. Journal of Theoretical & Applied Information Technology, 49, 700-707. |
| [13] | 杜建华, 高仲亮, 舒立福. 森林火灾探测扑救中的无人机技术及其应用[J]. 森林防火, 2013(4): 52-54. |
| [14] | 谢尧庆, 邓继忠, 叶家杭, 霍静朗, 严智威. 基于5G的无人机图传及在植保无人机中的应用展望[J]. 中国农机化学报, 2022, 43(1): 135-141. |
| [15] | 朱永乾. 基于COFDM的无人机图像传输系统设计[D]: [硕士学位论文]. 青岛: 山东科技大学, 2018. |
| [16] | 王鹏, 徐莹, 徐岩, 等. 基于WIFI的嵌入式无线图像监控系统设计[J]. 单片机与嵌入式系统应用, 2013, 13(10): 57-59. |
| [17] | Yuan, D. and Walsh, R.W. (2016) Abnormal Oscillation Modes in a Warning Light Bridge. Astronomy & Astrophysics, 594, A101. https://doi.org/10.1051/0004-6361/201629258 |
| [18] | 李杰, 邱选兵, 张恩华, 李宁, 魏永卜, 李传亮. 基于卷积神经网络的火灾识别算法[J]. 计算机应用, 2020, 40(S2): 173-177. |
| [19] | 冯路佳, 王慧琴, 王可, 等. 基于目标区域的卷积神经网络火灾烟雾识别[J]. 激光与光电子学进展, 2020, 57(16): 83-91. |
| [20] | 周志华. 机器学习[M]. 北京: 清华大学出版社, 2016. |
