Exploring the Aurrent Status of the Application of Drone Remote Sensing Technology in Agroforestry Pest Control

Chuhan Ao; Chenyang He

doi:10.54097/ha0hn003

Authors

Chuhan Ao
Chenyang He

DOI:

https://doi.org/10.54097/ha0hn003

Keywords:

Unmanned aerial remote sensing, multispectral remote sensing monitoring, deep learning.

Abstract

As an essential pillar industry of the national economy, agriculture and forestry industries are often seriously threatened by diseases and pests such as stem-boring pests and stem borers, which lead to crop yield reduction and even crop failure. For this reason, the establishment of a scientific and practical monitoring and early warning mechanism and the implementation of precise prevention and control measures are important measures to ensure the safety of agricultural production and ecological security. The purpose of this paper is to explore the advantages of UAV remote sensing in the application of pest control in agriculture and forestry. Meanwhile, this paper focuses on analyzing the current status of the application of a comprehensive vegetation index combined with deep learning methods. This paper proposes two possible directions for future research: one is to explore the synergistic application mode of satellite remote sensing and UAV remote sensing; the other is to study the changing law of spectral features of different crops in each growth stage to optimize the selection of monitoring parameters. The analyses in this paper can provide a valuable scientific basis for advancing the practical application of UAV remote sensing technology in the monitoring of pests and diseases in agriculture and forestry, and thus promote the sustainable development of pest control in agriculture and forestry.

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