Integrating spectral and textural information for identifying the tasseling date of summer maize using UAV based RGB images

The extraction of phenological events in forest and agriculture commonly relies on Vegetation Indices (VI) composed by visible near infrared bands from satellite images. However, the textural information playing an important role image fusion, classification change detection is ignored. In this study, high-throughput images collected Unmanned Aerial Vehicle (UAV) platform during growth stages summer maize were used to identify Tasseling Date (TD) based both spectral information. extracted using various VI Gray Level Co-occurrence Matrix (GLCM), respectively. results showed that Normalized Green Blue Difference Index (NGBDI), (GBDI) Contrast Information (Contrast) GLCM performed better than other variables. A new index was generated integrating Improved Adaptive Feature Weighting Method (IAFWM), then TDs identified for each plot. Root Mean Square Error (RMSE) 5.77 days it lowest among all potential ability more advanced machine learning deep should be investigated.