首页|Central South University of Forestry and Technology Researcher Reports Research in Artificial Intelligence (Rapid Forest Change Detection Using Unmanned Aerial Vehicles and Artificial Intelligence)
Central South University of Forestry and Technology Researcher Reports Research in Artificial Intelligence (Rapid Forest Change Detection Using Unmanned Aerial Vehicles and Artificial Intelligence)
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Investigators publish new report on ar tificial intelligence. According to news reporting from Changsha, People's Repub lic of China, by NewsRx journalists, research stated, "Forest inspection is a cr ucial component of forest monitoring in China. The current methods for detecting changes in forest patches primarily rely on remote sensing imagery and manual v isual interpretation, which are timeconsuming and labor-intensive approaches." Financial supporters for this research include Hainan Provincial Natural Science Foundation of China. Our news correspondents obtained a quote from the research from Central South Un iversity of Forestry and Technology: "This study aims to automate the extraction of changed forest patches using UAVs and artificial intelligence technologies, thereby saving time while ensuring detection accuracy. The research first utiliz es position and orientation system (POS) data to perform geometric correction on the acquired UAV imagery. Then, a convolutional neural network (CNN) is used to extract forest boundaries and compare them with the previous vector data of for est boundaries to initially detect patches of forest reduction. The average boun dary distance algorithm (ABDA) is applied to eliminate misclassified patches, ul timately generating precise maps of reduced forest patches. The results indicate that using POS data with RTK positioning for correcting UAV imagery results in a central area correction error of approximately 4 m and an edge area error of a pproximately 12 m. The TernausNet model achieved a maximum accuracy of 0.98 in i dentifying forest areas, effectively eliminating the influence of shrubs and gra sslands."
Central South University of Forestry and TechnologyChangshaPeople's Republic of ChinaAsiaArtificial IntelligenceEmerging TechnologiesMachine Learning
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