Abstract: 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.

Abstract: Systems and methods of automating the generation of a correction of an estimate of an elevation of a digital elevation model (DEM) of the bare earth under forest canopy. The disclosed embodiments facilitate generation of a more accurate DEM in areas of canopy coverage (where the input X-band DSM cannot see the ground) to estimate both the canopy height and the associated DEM. In some embodiments, the result of computationally correcting an estimate of an original DEM is a modified DEM. The method of correcting an estimate of an original DEM utilizes a pair of P-band radar images, an original DEM overlapping the same scene as the P-band radar images, at least one common, uniquely-identifiable point in the P-band radar images, and a definition of a geographical area surrounding the common, uniquely identifiable point over which the elevation correction is applicable.

Abstract: Systems and methods of automating the generation of an estimate of the first floor elevation of a building, using a Digital Terrain Model (DTM) and an image of the front of the building. First, machine learning (ML) algorithms are used to estimate the height of the first floor of the building above ground from the image. The estimated height is added to a DTM height of the geographical area corresponding to the location of the building to provide an estimate of the FFE. The disclosed embodiments can be applied in estimating the first floor height of any kind of building. For example, single-family homes, townhomes, high rise buildings, stores, malls, shops, movie theaters, or any other building. Additionally, the disclosed embodiments are camera-agnostic and can be applied on any type of image collected by any type of camera.

Abstract: 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.

Abstract: A system and method for generating a corrected digital elevation model is configured to remove systematic errors from digital elevation models. A residual dataset that is the difference between a first digital elevation model and a second digital elevation model is obtained and at least one error pattern related to a systematic error is identified. An error model representing at least one error pattern is generated and then removed from the first digital elevation model to create the corrected digital elevation model.