Extraction and Analysis of Discolored Standing Trees for Forest Diseases and Pests Using Drone Remote Sensing Data
With the large-scale artificial afforestation,forest diseases and pests have been increasing year by year,and monitoring of diseases and pests has become a key focus of prevention and control.By utilizing mature unmanned aerial vehicle remote sensing monitoring technology,high-precision or-thophoto images are obtained.Through data analysis of remote sensing images,a color changing standing tree intelligent extraction technology based on deep learning methods is adopted.With forest land verifi-cation as a review,the occurrence of forestry diseases and pests is effectively controlled.Deep learning algorithms compared to traditional machine learning can provide more accurate and timely monitoring of forest health status,thereby helping forestry workers detect and address potential forest health issues in a timely manner.Improve the comprehensiveness and accuracy of monitoring forestry pests and diseases,and effectively monitor forest ecological health.
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