基于无人机遥感技术分析农作物的特征  

Analysis of Crop Characteristics Based on UAV Remote Sensing Technology

作　　者：赵志全 梁明[2] 孙杰 汪洋 徐鑫[1] 胡维权 ZHAO Zhiquan;LIANG Ming;SUN Jie;WANG Yang;XU Xin;HU Weiquan(Lu'an Vocational and Technical College,Lu'an,Anhui 237000,China;School of Resources and Environmental Engineering,Anhui University,Hefei,Anhui 230601,China)

机构地区：[1]六安职业技术学院,安徽六安237000 [2]安徽大学资源与环境工程学院,安徽合肥230601

出　　处：《自动化应用》2025年第6期67-69,共3页Automation Application

基　　金：安徽省高校自然科学研究项目(2023AH053251)。

摘　　要：应用无人机遥感技术对江淮分水岭地区的玉米、水稻、小麦和大豆4种主要作物进行特征分析,通过高分辨率相机和光谱设备在100~120 m高度采集数据,并通过ENVI软件及机器学习算法处理,实现了94.2%的玉米分类准确率,以及超过91.3%的水稻稻瘟病检测准确率。叶面积指数和土壤水分的估算误差均控制在较小范围内,土壤水分反演模型的R2值高达0.88。研究结果验证了无人机技术在精准农业管理中的高效性,为提升农业生产效率提供了科学支持。The application of unmanned aerial vehicle remote sensing technology was used to analyze the characteristics of four main crops,corn,rice,wheat,and soybean,in the Jianghuai watershed area.High resolution cameras and spectral equipment were used to collect data at heights of 100~120 meters,and ENVI software and machine learning algorithms were used for processing,achieving a corn classification accuracy of 94.2%and a rice blast disease detection accuracy of over 91.3%.The estimation errors of leaf area index and soil moisture are both controlled within a small range,and the R²value of the soil moisture inversion model is as high as 0.88.The research results have verified the efficiency of drone technology in precision agriculture management,providing scientific support for improving agricultural production efficiency.

关 键 词：无人机遥感 农作物特征分析 精准农业 多光谱影像 病害检测 

分 类 号：S157[农业科学—土壤学]