Article Details

Abstract

In order to strengthen the supervision and management of natural resources exploration and development activities and improve the ability and level of natural resources supervision, this paper deeply analyzes the shortcomings of the traditional natural resources supervision system. On this basis, it is proposed to optimize the Deep Learning target detection algorithm model for the construction machinery used in the illegal mining process by virtue of the advantages of tower high point supervision. The accuracy and efficiency of the algorithm recognition are improved by enlarging the secondary detection of suspicious images. The project has been deeply integrated into the working mechanism of mineral satellite image law enforcement, which greatly improves the ability to identify and stop illegal acts of mineral resources in the supervision area.

Keywords

video surveillance; mineral resource; high point supervision; natural resource

References

1. [1] Huang Yufang, Zhang Qian Research on the Comprehensive Supervision Platform System for Planning and Natural Resource Law Enforcement [J]. Beijing Planning and Construction, 2020 (S1): 149-152
2. [2] Shen Tianci Research on the Construction of Land Law Enforcement Supervision and Management Platform Based on GIS [J]. Jingwei Tiandi, 2021, 56 (5): 65-69
3. [3] Ni Xu, Fu Jing, Zhang Hailiang Research on the Ecological Governance of Strategic Mineral Resources Empowered by Blockchain [J]. Yunnan Social Sciences, 2022 (1): 91-97
4. [4] Zhu Wenfeng, Liu Guofeng China Tower has transformed from a traditional "communication tower" to a "digital tower", helping to modernize the governance system. Communication World, 2021 (11): 18
5. [5] Zhang Yi, Ji Bo, Ruan Jing Practice and Reflection on the Intelligent Perception Mode of Natural Resources Based on Tower based Video Surveillance [J]. Land and Resources Informatization, 2021 (5): 8-14
6. [6] Xu Haiwen, Liu Sha Design and Implementation of Forest Fire Prevention Video Monitoring System in Hunan Province Based on Iron Towers [J]. Modern Information Technology, 2023, 7 (2): 42-44, 48
7. [7] Zuo Tianhui, Yuan Ling, Zhou Yingtong Design and Implementation of Natural Resource Intelligent Supervision System Based on Tower Video [J]. Southern Natural Resources, 2022 (12): 16-22
8. [8] Yang Chengjia, Qian Ming A review of YOLO algorithm research based on small object detection [J]. Journal of Jilin Engineering and Technology Normal University, 2023, 39 (3): 92-96
9. [9] Li Wenbo, Zhao Zhengxu Small Object Detection in Remote Sensing Images Based on YOLOv5 [J]. Technological Innovation and Application, 2023 (6): 63-67
10. [10] Ding Lele, Wang Zhen, Liu Yanfei, etc Research on Monitoring Land Illegal Construction Scenarios Based on Deep Learning [J]. Geospatial Information, 2023 (4): 72-74

About the authors

Lin Hong (1984-), male, Han ethnicity, from Fuzhou, Fujian, is a senior engineer with a master's degree. His research interests include computer networks, computer applications, and information systems.