A method for colourising a three-dimensional point cloud including surveying a point cloud with a surveying instrument. Each point of the point cloud may be characterised by coordinates within an instrument coordinate system having an instrument center. The method may include capturing a first image of the setting with a first camera. Each pixel value of the first image is assigned coordinates within a first camera coordinate system having a first projection center as origin and a first parallax shift relative to the instrument center. The method may include transforming the point cloud from the instrument coordinate system into the first camera coordinate system, resulting in a first transformed point cloud, detecting one or more uncovered points within the first transformed point cloud which are openly visible from the first projection center, and for each uncovered point, assigning a pixel value having corresponding coordinates in the first camera coordinate system.

A high-precision waterway reconstruction method based on a multi-satellite source information coupling is provided. The method includes a determination method for a waterway section, a reconstruction method for a basic waterway section high-precision coupling, a reconstruction method for a fixed waterway section coupling, and a reconstruction method for a river reach waterway terrain. The method fills the gap of surveying and mapping of the waterways based on satellite remote sensing information, extremely improves the perpendicular precision and planar precision of the existing digital surface model of satellites for river waterways, and provides decision support for a water-related emergency rescue in areas lacking data.

A method is provided. The method includes: determining, by one or more computers, a name of a target region, wherein the name of the target region is determined based on geometry attribute information of the target region; and determining, by one or more computers, region attribute information of the target region based on the name of the target region

A method for constructing a three-dimensional road network map is disclosed. The method includes: extracting a two-dimensional road based on a satellite remote sensing image; skeletonizing the two-dimensional road to obtain a two-dimensional road network map; and determining a height of each point in the two-dimensional road network map based on an elevation of three-dimensional point cloud data, to obtain the three-dimensional road network map.

A method of determining a roadway map includes receiving an image from above a roadway. The method further includes generating a skeletonized map based on the received image, wherein the skeletonized map comprises a plurality of roads. The method includes identifying intersections based on joining of multiple roads of the plurality of roads in the skeletonized map. The method includes partitioning the skeletonized map based on the identified intersections, wherein partitioning the skeletonized map defines a roadway data set and an intersection data set. The method includes analyzing the roadway data set to determine a number of lanes in each roadway of the plurality of roads. The method further includes analyzing the intersection data set to lane connections in the identified intersections. The method further includes merging results of the analyzed road data set and the analyzed intersection data set to generate the roadway map.

Methods, systems and apparatus, including computer programs encoded on computer storage media for determining a center location of a ground control point used in aerial surveys. Machine learning models are used to identify in digital images pixel coordinates of the ground control point identified in the digital images. These image pixel coordinates are used in photogrammetric processing and software.

A method for analyzing a geologic sample includes illuminating the geologic sample with a halogen light beam, and capturing an image of the geologic sample on a camera thereby collecting spectra reflected from a surface of the geologic sample. The method further includes processing the image to identify rock properties of the geologic sample and determine a qualitative descriptor of the rock properties. The method further includes analyzing the qualitative descriptor of the rock properties of the geologic sample to determine subsurface lithography.

A reflector arrangement for position determination and/or marking of target points, comprising a retroreflector and a first sensor arrangement, by means of which the orientation measurement radiation passing through the retroreflector is acquirable. The first sensor arrangement comprises a first optical assembly providing a fisheye lens, and a first sensor, wherein the retroreflector and the first sensor arrangement are arranged in such a way that orientation measurement radiation passing through the retroreflector is projectable onto the detection surface of the first sensor by means of the first optical assembly.

A method and device for calculating a river surface flow velocity are provided based on a variational principle, which are used to capture and process the images of an objective area, and to obtain the flow velocity field data of the objective area with high precision in a non-contact manner. The method and device include 3 steps: (1) preparation before initial flow measurement; (2) capturing a video of the river by an image acquisition device, converting a motion of a pixel flow field of the fluid in a captured image sequence into solving an energy functional optimization problem, and solving partial differential equations to obtain data of pixel flow field distribution; and (3) obtaining space coordinates of the pixel point in a world coordinate system and calculating the flow velocity according to the data obtained in the step 2 and the transformation relationship determined in the step 1.

A method and instruction memory for processing acoustic images of a downhole casing to determine perforations of the tubular. The images may be acquired by an acoustic logging tool deployed into cased well. A Machine Learning model is trained to recognize regions of the acoustic images that are perforations or not, in order to calculate geometric properties of the perforation and overall casing. Renderings of the imaged casing may be overlaid with contours and properties of perforations to improve perforation, fracturing and producing operations.