Abstract: The present disclosure relates to a method (100) for 3D reconstruction. The method comprises obtaining (S100) a set of images, each image overlapping a region of interest, performing (S400) image registration for the set of images, wherein performing the image registration comprises correlating (S410) each image with a reference 3D data set, the correlating (S410) of each image with the reference 3D data set being arranged to determine the positional accuracy of each image to the same positional accuracy of the reference 3D data set, and generating (S600) a 3D data set relating to the region of interest using (S610) 3D reconstruction based on the registered images. The present disclosure also relates to corresponding computer program products and systems.

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 (100) for providing an assessment media for use in assessing accuracy of a geospatial dataset. The method comprises obtaining (S100) an ordered set of reference media, the ordered set comprising a first and a last reference media, the first reference media comprising one or more identifiable Ground Control Point, GCP, and generating (S200) the assessment media based on establishing (S205) respective links from each GCP of the first reference media to a corresponding point in the last reference media.

Abstract: The present disclosure relates to a method (100) for 3D reconstruction. The method comprises obtaining (S100) a set of images, each image overlapping a region of interest, performing (S400) image registration for the set of images, wherein performing the image registration comprises correlating (S410) each image with a reference 3D data set, the correlating (S410) of each image with the reference 3D data set being arranged to determine the positional accuracy of each image to the same positional accuracy of the reference 3D data set, and generating (S600) a 3D data set relating to the region of interest using (S610) 3D reconstruction based on the registered images. The present disclosure also relates to corresponding computer program products and systems.

Abstract: Forestry timber volume estimations may be provided. In a three-dimensional Digital Surface Model (DSM), a plurality of image data associated with a respective plurality of trees may be identified. Then, from the plurality of image data, species data associated with each of the plurality of trees may be determined. A height above ground may then be determined for each of the plurality of trees by subtracting a height of ground associated with each of the plurality of trees determined from a three-dimensional Digital Terrain Model (DTM) from a height of tree associated with each of the plurality of trees determined from the three-dimensional DSM. A volume associated with each of the plurality of trees may be determined based on the height of tree associated with each of the plurality of trees and the species data associated with each of the plurality of trees.

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 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.