Abstract: The present disclosure relates to a computer implemented method (100) for attribution of Land Use/Land Cover, LULC, said method comprising the steps of: providing (S1) a plurality of images covering a transport network part, identifying (S2) objects in at least a subset of said plurality of images, identifying (S4) transport routes at least in said at least one satellite image of the plurality of images, and determining (S5) characteristics of said transport network part based on the identified objects at said identified (S4) transport routes.

Abstract: The present disclosure relates to a method and system for navigation of an aerial vehicle. The method (100) comprises providing (110) a sensor image from an aerial vehicle sensor and repeatedly, until at least one predetermined criterion is reached, performing the steps: setting (120) input data comprising information related to pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle; providing (130) at least one two-dimensional perspective view image based on the input data, where the at least one two-dimensional perspective view image is obtained from a database comprising three-dimensional geo-referenced information of the environment, said three-dimensional geo-referenced information comprising texture data; and comparing (140) the sensor image and the at least one two-dimensional perspective view image.

Abstract: The present disclosure relates to a method and system for navigation of an aerial vehicle. The method (100) comprises providing (110) a sensor image from an aerial vehicle sensor and repeatedly, until at least one predetermined criterion is reached, performing the steps: setting (120) input data comprising information related to pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle; providing (130) at least one two-dimensional perspective view image based on the input data, where the at least one two-dimensional perspective view image is obtained from a database comprising three-dimensional geo-referenced information of the environment, said three-dimensional geo-referenced information comprising texture data; and comparing (140) the sensor image and the at least one two-dimensional perspective view image.

Abstract: A material transfer vehicle includes a loading conveyor and a loading component (such as a truck-receiving hopper component or a windrow pick-up component) that is adapted to be removably attached to the lower end of the loading conveyor. The loading conveyor has a right guide plate on the right side of the lower end and a left guide plate on the left side of the lower end. The loading component has a right guide bracket that is adapted to align with and engage the right guide plate of the loading conveyor, and a left guide bracket that is adapted to align with and engage the left guide plate of the loading conveyor.

Abstract: A material transfer vehicle includes a loading conveyor and a loading component (such as a truck-receiving hopper component or a windrow pick-up component) that is adapted to be removably attached to the lower end of the loading conveyor. The loading conveyor has a right guide plate on the right side of the lower end and a left guide plate on the left side of the lower end. The loading component has a right guide bracket that is adapted to align with and engage the right guide plate of the loading conveyor, and a left guide bracket that is adapted to align with and engage the left guide plate of the loading conveyor.

Abstract: A method of estimating absolute orientation of a vehicle utilizing a camera and GPS. At least three images are selected from concurrent images taken above an essentially horizontal ground at a distance from each other. Key points are identified in each selected image. Absolute positions of the images are obtained from the GPS defining the image positions when a respective image was taken. Key points between selected images are matched to obtain an estimate of the absolute orientation.

Abstract: A method of estimating absolute orientation of a vehicle utilizing a camera and GPS. At least three images are selected from concurrent images taken above an essentially horizontal ground at a distance from each other. Key points are identified in each selected image. Absolute positions of the images are obtained from the GPS defining the image positions when a respective image was taken. Key points between selected images are matched to obtain an estimate of the absolute orientation.