Intermap Technologies Inc.

Qiaoping Zhang

Stephen Charles Griffiths

Nathan Zachary Mercer

Michael John Wollersheim

Trevor Roy Miller

Ivan Pierre Maddox

Ladislav Garassy

Jirí Vohlídal

Ralph Mark Hope

Jan Roubalik

Yue Huang

A technique is directed to methods and systems for calculating building heights from mono imagery. In some implementations, a building height calculation system performs orthorectification of an image of buildings against a digital terrain model to remove effects of terrain distortion from the image. The building height calculation system can execute an edge detection algorithm on the image to identify the edges of the building in the image. The edges can provide a rooftop vector of the building. The building height calculation system can execute, using image data at input, a machine learning algorithm to determine the footprint vector of the building in the image. The building height is calculated based on a camera angle, a distance from the camera to the building, and a pixel offset from the footprint vector to the rooftop vector.

Methods and apparatuses for calculating building heights from mono imagery

Systems and methods of enhancing the resolution of digital terrain models (DTM) for location-based applications and analyses. The DTM enhancement process takes the signature of the input image (e.g., via the input image and a noise surface file with similar characteristics as the sensor used to capture the input image) and applies it to the DTM without including large features such as buildings. The disclosed methods include utilize a process similar to that used for enhancing a DSM based on mapping the changing intensity from the image file to changes in elevation in the DSM using a regression over a local neighborhood of pixels. Further, the disclosed methods do not rely on information about the sensors and are extendable to be able to utilize any types of images. Additionally, the disclosed embodiments are sensor agnostic and can be applied on any type of image collected by any type of sensor.

Method and apparatus for enhancing 3D model resolution

Systems and methods of enhancing the resolution or restoring details associated with high resolution images into a filtered digital surface model (DSM) for location-based applications and analyses. The disclosed methods include mapping the changing gray scale values (intensity) from the images to changes in elevation in the DSM using a regression over a local neighborhood of pixels. Further, the disclosed methods do not rely on information about the sensor illumination geometry, and are extendable to be able to utilize any types of images. Additionally, the disclosed embodiments are sensor agnostic. That is, the disclosed methods can be applied on any type of images collected by any type of sensor.

Implementations described and claimed herein provide systems and methods for flood hazard zone modeling. In one implementation, one or more relevant stream segments are identified from an input stream network. One or more cross profiles are defined for one or more selected points on the relevant stream segments, with the selected points located within a flood hazard area. A high resolution flood level elevation map is generated by interpolating flood level elevation from the selected points. A flood depth map is generated having a flood depth value for each of the selected points computed as a difference between the high resolution flood level elevation map and a terrain elevation. One or more flood zones are defined in the flood depth map. The flood zones have a positive flood depth for a return period.

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Englewood, CO, United States of America

Qiaoping Zhang