基于反射光谱和叶绿素荧光数据的作物病害遥感监测研究进展

竞霞, 邹琴, 白宗璠, 黄文江

Research progress of crop diseases monitoring based on reflectance and chlorophyll fluorescence data

JING Xia, ZOU Qin, BAI Zong-Fan, HUANG Wen-Jiang

表2 作物病害遥感监测算法

Table 2 Remote sensing monitoring algorithm for crop diseases

模型 Model 作物病害种类 Type of crop diseases 算法 Algorithm 文献 Reference 统计模型 Statistical model 小麦白粉病 Wheat powdery mildew 相关分析、方差分析 Correlation analysis and variance analysis [41] 小麦条锈病 Wheat stripe rust 线性回归、非线性回归 Linear regression and nonlinear regression [42] 小麦白粉病 Wheat powdery mildew Logistic回归 Logistic regression [43] 番茄叶斑病 Tomato bacterial spot 偏最小二乘回归、多元逐步回归 Partial least squares regression and multiple stepwise regression [44] 小麦条锈病 Wheat stripe rust 偏最小二乘法 Partial least squares [9] 人工智能模型 Artificial intelligence model 水稻颖枯病、曲霉病 Rice glume blight disease and false smut disease 主成分分析 Principal component analysis [31] 黄瓜花叶病毒 Cucumber mosaic virus 人工神经网络 Artificial neural network [45] 小麦白粉病 Wheat powdery mildew Fisher线性判别分析、AdaBoost和支持向量机 Fisher linear discriminant analysis, support vector machine, and AdaBoost model [46] 大豆枯萎病 Soybean sudden death syndrome 偏最小二乘判别分析 Partial least squares discriminant analysis [47] 油棕茎腐病 Oil palm basal stem rot 决策树、随机森林和支持向量机 Decision tree, random forest, and support vector machine [48] 小麦白粉病 Wheat powdery mildew 随机森林 Random forest [49] 蚕豆病虫害 Broad bean disease and pests 聚类算法 K-Means and the FCM clustering [50]