Modeling plant canopy biophysical parameters at the individual plant level remains a major challenge.This study presents a workflow for automatic strawberry canopy delineation and biomass prediction from high-resoluti...Modeling plant canopy biophysical parameters at the individual plant level remains a major challenge.This study presents a workflow for automatic strawberry canopy delineation and biomass prediction from high-resolution images using deep neural networks.High-resolution(5 mm)RGB orthoimages,near-infrared(NIR)orthoimages,and Digital Surface Models(DSM),which were generated by Structure from Motion(SfM),were utilized in this study.Mask R-CNN was applied to the orthoimages of two band combinations(RGB and RGB-NIR)to identify and delineate strawberry plant canopies.展开更多
文摘Modeling plant canopy biophysical parameters at the individual plant level remains a major challenge.This study presents a workflow for automatic strawberry canopy delineation and biomass prediction from high-resolution images using deep neural networks.High-resolution(5 mm)RGB orthoimages,near-infrared(NIR)orthoimages,and Digital Surface Models(DSM),which were generated by Structure from Motion(SfM),were utilized in this study.Mask R-CNN was applied to the orthoimages of two band combinations(RGB and RGB-NIR)to identify and delineate strawberry plant canopies.
