Research on the Application of Computer Big Data Technology in Garden Plant Health Monitoring
Hairong Tang, Xiaoming Liu · 2024
A set of remote sensing monitoring methods suitable for urban terrain and landforms was established. Through multi-period remote sensing image data, spatial location, emission time and emission intensity are decoupled. By integrating the one-dimensional water quality diffusion model with tracer test data, a new method for traceability analysis of explosive water pollution accidents based on fluorescence was constructed. During the solution process, the monitoring data is divided into a training set and an experimental set. The improved firefly algorithm is used to adjust the hydrological parameters of the river through the training set data. Experiments are performed on local images in the Landsat5TM database. It is verified that the accuracy of the proposed algorithm can reach 90.77%, and the operation speed is faster. Compared with traditional post-classification techniques for change detection analysis, our system has higher performance and recognition accuracy with lower computing time. The prevention and control of sudden pollution accidents in rivers in China.