Abstract: An agricultural modeling system may include a scanning platform configured to generate 3D point cloud data of an agricultural geographic area, a geospatial database configured to store a data layer for the agricultural geographic area, and a computing resource in communication with the scanning platform, client devices, and the geospatial database. The computing resource may be configured to geographically reference the data layer fused with the 3D point cloud data of the agricultural geographic area, and generate a multi-layered data model for the geographically referenced data layer fused with the 3D point cloud data of the agricultural geographic area. A client device may be configured to selectively render the multi-layered data model.

Abstract: An agricultural modeling system may include a mobile ranging platform configured to generate 3D point cloud data of an agricultural geographic area, client devices, a geospatial database configured to store a data layer for the agricultural geographic area, and a server computing resource in communication with the mobile ranging platform, the client devices, and the geospatial database. The server computing resource may be configured to geographically reference the data layer fused with the 3D point cloud data of the agricultural geographic area, and generate a multi-layered data model for the geographically referenced data layer fused with the 3D point cloud data of the agricultural geographic area. A client device may be configured to selectively render the multi-layered data model.

Abstract: An agricultural modeling system may include a mobile LiDAR platform configured to generate 3D point cloud data of an agricultural geographic area, client devices, a geospatial database configured to store a data layer for the agricultural geographic area, and a server computing resource in communication with the mobile LiDAR platform, the client devices, and the geospatial database. The server computing resource may be configured to geographically reference the data layer fused with the 3D point cloud data of the agricultural geographic area, and generate a multi-layered data model for the geographically referenced data layer fused with the 3D point cloud data of the agricultural geographic area for providing interactive analysis and visualization of agricultural information alongside collaborators with LiDAR-based high resolution 3D plant model. A client device may be configured to selectively render the multi-layered data model.

Abstract: Systems, apparatuses and methods for determining a risk of catastrophic failure for a tree based on a mechanistic model of physical characteristics of the tree are described. The systems, apparatuses and methods include a mobile sensing platform comprising one or more sensors for obtaining data, a transport vehicle configured to transport the mobile sensing platform, a positioning sensor configured to precisely calculate geographic coordinates of the positioning sensor and the location of the positioning sensor relative to a reference object as positioning data, and a processor configured to fuse the imaging data and the positioning data in order to determine conditions for catastrophic tree failure.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality. According to embodiments of the invention, a plant analysis system is configured determine a spectral signature of a plant based on spectral data, and plant color based on photographic data. The spectral signatures and plant color are associated with assembled point cloud data. Morphological data of the plant can be generated based on the assembled point cloud data. A record of the plant can be created that associates the plant with the spectral signature, plant color, spectral data, assembled point cloud data, and morphological data, and stored in a library.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality. According to embodiments of the invention, a plant analysis system is configured determine a spectral signature of a plant based on spectral data, and plant color based on photographic data. The spectral signatures and plant color are associated with assembled point cloud data. Morphological data of the plant can be generated based on the assembled point cloud data. A record of the plant can be created that associates the plant with the spectral signature, plant color, spectral data, assembled point cloud data, and morphological data, and stored in a library.

Abstract: Systems, apparatuses and methods for determining a risk of catastrophic failure for a tree based on a mechanistic model of physical characteristics of the tree are described. The systems, apparatuses and methods include a mobile sensing platform comprising one or more sensors for obtaining data, a transport vehicle configured to transport the mobile sensing platform, a positioning sensor configured to precisely calculate geographic coordinates of the positioning sensor and the location of the positioning sensor relative to a reference object as positioning data, and a processor configured to fuse the imaging data and the positioning data in order to determine conditions for catastrophic tree failure.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality.

Abstract: Systems, and methods for controlling a modular system for improved real-time yield monitoring and sensor fusion of crops in an orchard are disclosed. According to some embodiments of the invention, a modular system for improved real-time yield monitoring and sensor fusion may include a collection vehicle, a modular processing unit, a volume measurement module, a three-dimensional point-cloud scanning module, an inertial navigation system, and a post-processing server. As the collection vehicle travels through an orchard, the volume measurement module calculates volume measurements of the windrow, the three-dimensional point-cloud scanning module assembles point-clouds of each plant in the orchard, and the inertial navigation system calculates geodetic positions of the collection vehicle. The modular processing unit may fuse the collected data together and transmit the fused data set to a post-processing server.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality. According to embodiments of the invention, a plant analysis system is configured determine a spectral signature of a plant based on spectral data, and plant color based on photographic data. The spectral signatures and plant color are associated with assembled point cloud data. Morphological data of the plant can be generated based on the assembled point cloud data. A record of the plant can be created that associates the plant with the spectral signature, plant color, spectral data, assembled point cloud data, and morphological data, and stored in a library.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality.

Abstract: Systems, and methods for controlling a modular system for improved real-time yield monitoring and sensor fusion of crops in an orchard are disclosed. According to some embodiments of the invention, a modular system for improved real-time yield monitoring and sensor fusion may include a collection vehicle, a modular processing unit, a volume measurement module, a three-dimensional point-cloud scanning module, an inertial navigation system, and a post-processing server. As the collection vehicle travels through an orchard, the volume measurement module calculates volume measurements of the windrow, the three-dimensional point-cloud scanning module assembles point-clouds of each plant in the orchard, and the inertial navigation system calculates geodetic positions of the collection vehicle. The modular processing unit may fuse the collected data together and transmit the fused data set to a post-processing server.

Abstract: Systems, and methods for controlling a modular system for improved real-time yield monitoring and sensor fusion of crops in an orchard are disclosed. According to some embodiments of the invention, a modular system for improved real-time yield monitoring and sensor fusion may include a collection vehicle, a modular processing unit, a volume measurement module, a three-dimensional point-cloud scanning module, an inertial navigation system, and a post-processing server. As the collection vehicle travels through an orchard, the volume measurement module calculates volume measurements of the windrow, the three-dimensional point-cloud scanning module assembles point-clouds of each plant in the orchard, and the inertial navigation system calculates geodetic positions of the collection vehicle. The modular processing unit may fuse the collected data together and transmit the fused data set to a post-processing server.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality. According to embodiments of the invention, a plant analysis system is configured determine a spectral signature of a plant based on spectral data, and plant color based on photographic data. The spectral signatures and plant color are associated with assembled point cloud data. Morphological data of the plant can be generated based on the assembled point cloud data. A record of the plant can be created that associates the plant with the spectral signature, plant color, spectral data, assembled point cloud data, and morphological data, and stored in a library.

Abstract: Systems, and methods for controlling a modular system for improved real-time yield monitoring and sensor fusion of crops in an orchard are disclosed. According to some embodiments of the invention, a modular system for improved real-time yield monitoring and sensor fusion may include a collection vehicle, a modular processing unit, a volume measurement module, a three-dimensional point-cloud scanning module, an inertial navigation system, and a post-processing server. As the collection vehicle travels through an orchard, the volume measurement module calculates volume measurements of the windrow, the three-dimensional point-cloud scanning module assembles point-clouds of each plant in the orchard, and the inertial navigation system calculates geodetic positions of the collection vehicle. The modular processing unit may fuse the collected data together and transmit the fused data set to a post-processing server.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality.

Abstract: The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality.

Abstract: Systems, and methods for controlling a modular system for improved real-time yield monitoring and sensor fusion of crops in an orchard are disclosed. According to some embodiments of the invention, a modular system for improved real-time yield monitoring and sensor fusion may include a collection vehicle, a modular processing unit, a volume measurement module, a three-dimensional point-cloud scanning module, an inertial navigation system, and a post-processing server. As the collection vehicle travels through an orchard, the volume measurement module calculates volume measurements of the windrow, the three-dimensional point-cloud scanning module assembles point-clouds of each plant in the orchard, and the inertial navigation system calculates geodetic positions of the collection vehicle. The modular processing unit may fuse the collected data together and transmit the fused data set to a post-processing server.

Abstract: Systems, and methods for controlling a modular system for improved real-time yield monitoring and sensor fusion of crops in an orchard are disclosed. According to some embodiments of the invention, a modular system for improved real-time yield monitoring and sensor fusion may include a collection vehicle, a modular processing unit, a volume measurement module, a three-dimensional point-cloud scanning module, an inertial navigation system, and a post-processing server. As the collection vehicle travels through an orchard, the volume measurement module calculates volume measurements of the windrow, the three-dimensional point-cloud scanning module assembles point-clouds of each plant in the orchard, and the inertial navigation system calculates geodetic positions of the collection vehicle. The modular processing unit may fuse the collected data together and transmit the fused data set to a post-processing server.