VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain

EscaYard: Precision viticulture multimodal dataset of vineyards affected by Esca disease consisting of geotagged smartphone images, phytosanitary status, UAV 3D point clouds and Orthomosaics

“…It enables new methods for plant health, phenotyping, and precision agriculture, advancing research techniques. The possibility of combining this dataset with other datasets gathered from the same vineyard (such as [ [1] , [2] , [3] ], which contain multispectral images, RGB videos and LiDAR data), enhances its value, enabling comprehensive studies on vineyard ecosystems, disease dynamics, and the impact of agricultural practices on crop health and the environment. Increased flexibility and convenience for students conducting preliminary research, as they can efficiently utilize smartphones for survey purposes, streamlining their data collection efforts.…”

“…The possibility of combining this dataset with other datasets gathered from the same vineyard (such as [ [1] , [2] , [3] ], which contain multispectral images, RGB videos and LiDAR data), enhances its value, enabling comprehensive studies on vineyard ecosystems, disease dynamics, and the impact of agricultural practices on crop health and the environment.…”

“…In addition, this dataset can be combined with other datasets on the same disease [ 16 , 17 ], or with existing datasets from the same vineyard [ [1] , [2] , [3] ] to enhance the understanding of vineyard ecosystems. By integrating these datasets, researchers can conduct a more detailed analysis of grape bunch visibility, phenotypic traits, disease assessment, and yield estimation under different conditions.…”

GrapeMOTS: UAV vineyard dataset with MOTS grape bunch annotations recorded from multiple perspectives for enhanced object detection and tracking

“… Datasets, together with annotations, address the lack of public agricultural datasets. This dataset can be integrated with other datasets from the same vineyard that contain key information such as the position of the plant trunks or lidar point clouds [ 4 , 6 , 7 ], enabling researchers to go further and achieve a more precise understanding of the vineyard. …”

“…Moreover, the significance of this dataset extends beyond its immediate utility. It serves as another piece that can be synergistically combined with other existing datasets from the same vineyard [ 4 , 6 , 7 ], which encompass a diverse range of data types, including videos, UAV orthoimages, and even LiDAR information. This diversity enhances the potential for data fusion and enables a multifaceted analysis of the vineyard ecosystem on the same dates but also across different years.…”