REMOTE MEASUREMENT SYSTEM AND METHOD FOR PESTICIDE FOG DISTRIBUTION AND DRIFTING TENDENCY IN AERIAL PESTICIDE APPLICATION

摘要

Disclosed are a remote measurement system and method for pesticide fog distribution and drifting tendency in aerial pesticide application, which relate to the technical field of hazardous substance monitoring. The system comprises: a collection module, used for collecting infrared radiation in a detected area, and enabling the infrared radiation to be incident on an optical module; the optical module, used for obtaining, according to the incident infrared radiation, an infrared imaging spectrum in the detected area where a pesticide fog cloud cluster is distributed, and sending the infrared imaging spectrum to a processing module; the processing module, used for analyzing the infrared imaging spectrum, identifying the pesticide fog cloud, obtaining a concentration image of the pesticide fog cloud through inversion, and predicting a drifting tendency of the pesticide fog according to the concentration image. The system and method of the present invention can comprehensively reflect the drifting condition of the pesticide fog in the air in real time, and can obtain the concentration and components of the pesticide fog. The method and system improve the pesticide application efficiency, and prevent damages on the environment and residential areas while saving the cost.

主权项

1. A remote measurement system for pesticide fog distribution and drifting tendency in aerial pesticide application, characterized in that, the system comprises:
a collection module for collecting infrared radiation of a detected area, and guiding the infrared radiation into an optical module; the optical module for obtaining infrared imaging spectrum of the detected area distributed with pesticide fog clouds based on the incident infrared radiation, and sending the infrared imaging spectrum to a processing module; and the processing module for performing characteristic analysis on the infrared imaging spectrum, identifying the pesticide fog clouds, inverting concentration images of the pesticide fog clouds, and predicting drift tendency of the pesticide fog clouds based on the concentration image.