Abstract: Techniques for atmospheric compensation in satellite imagery that include converting an image including an array of radiance values to an array of surface reflectance values. The conversion is performed in an automated fashion by identifying one or more portions of the image for which the surface reflectance can be estimated and determining the Aerosol Optical Depth (AOD) by iteratively comparing the radiance value captured by the image sensor to a calculated radiance value (based on the known surface reflectance, historical values for other atmospheric parameters, and the AOD) and adjusting the AOD until the calculated radiance value is substantially the same as the captured radiance value.

Abstract: Generation of a plurality of orthomosaic image layers for a geographical area, wherein the layers comprise different spatial resolutions and are radiometrically normalized to facilitate improved radiometric consistency when zooming relative to the geographic area. In applications that facilitate zooming with respect to a geographic area imaged by the orthomosaic layers, radiometric normalization of the orthomosaic image layers may reduce radiometric discontinuities when zooming in, zooming out, and/or panning a displayed portion that is output to the user. The orthomosaic layers may be generated based on one or more orthomosaic image layer or may be developed independently using a source images. In any regard, the radiometric normalization may include generating a normalization function based on image metadata that is calculated and may be independent of the spatial resolution of the image.

Abstract: A system for performing global scale object detection using satellite imagery, comprising an object detection server that receives and analyzes image data to identify objects within an image via a curated computational method, and a curation interface that enables a user to curate image information for use in object identification, and a method for a curated computational method for performing global scale object detection.

Abstract: A system for automated conversion of two-dimensional hydrology vector models into valid three-dimensional hydrology vector models, comprising a vector extraction engine that retrieves vectors from, and sends vectors to, a vector storage, a DSM server that retrieves a DSM from a DSM storage and computes a DSM from stereo disparity measurements of a stereo pair retrieved from a raster storage, and a rendering engine that provides visual representations of images for review by a human user, and a method for automated hydrology vector model development utilizing the system of the invention.

Abstract: Techniques for automatically removing slivers from orthomosaics. First, slivers may be identified, which may be based upon user-configurable characteristics such as width and length. Second, slivers may be replaced with portions of another image, such as an older image. Third, boundary slivers may optionally be removed. Fourth, remaining boundary or interior slivers can be inflated by expanding the sliver until it is no longer a sliver, which may include replacing a portion of an adjacent image portion with older imagery.

Abstract: A system for simplified generation of systems for analysis of satellite images to geolocate one or more objects of interest. A plurality of training images labeled for a study object or objects with irrelevant features loaded into a preexisting feature identification subsystem causes automated generation of models for the study object. This model is used to parameterize pre-engineered machine learning elements that are running a preprogrammed machine learning protocol. Training images with the study are used to train object recognition filters. This filter is used to identify the study object in unanalyzed images. The system reports results in a requestor's preferred format.

Abstract: A system for semi-automated feature extraction comprising an image analysis server that receives and initializes a plurality of raster images, a feature extraction server that identifies and extracts image features, a mosaic server that assembles mosaics from multiple images, and a rendering engine that provides visual representations of images for review by a human user, and a method for generating a cost raster utilizing the system of the invention.

Abstract: A system for performing global-scale damage detection using satellite imagery, comprising a damage detection server that receives and analyzes image data to identify objects within an image via a curated computational method, and a curation interface that enables a user to curate image information for use in object identification, and a method for a curated computational method for performing global scale damage detection.

Abstract: A system for broad area geospatial object recognition, identification, classification, location and quantification, comprising an image manipulation module to create synthetically-generated images to imitate and augment an existing quantity of orthorectified geospatial images; together with a deep learning module and a convolutional neural network serving as an image analysis module, to analyze a large corpus of orthorectified geospatial images, identify and demarcate a searched object of interest from within the corpus, locate and quantify the identified or classified objects from the corpus of geospatial imagery available to the system. The system reports results in a requestor's preferred format.

Abstract: Techniques for improving overhead image bathymetry include obtaining depth information from image data based on one or more of the spectral domain, the angular domain (e.g., stereo or photogrammetry), the temporal domain (e.g., monitoring the movement of waves in a body of water), or any other suitable domain, together with a priori information about the area of interest. These different pieces of depth information from the various different domains are combined together using any combination of Optimal Estimation and Continuity Constraints to improve the accuracy of the results.

Abstract: A system for vector extraction comprising a vector extraction engine stored and operating on a network-connected computing device that loads raster images from a database stored and operating on a network-connected computing device, identifies features in the raster images, and computes a vector based on the features, and methods for feature and vector extraction.

Abstract: Utilities (e.g., systems, methods, etc.) for automatically generating high resolution population density estimation data sets through manipulation of low resolution population density estimation data sets with high resolution overhead imagery data (e.g., such as overhead imagery data acquired by satellites, aircrafts, etc. of celestial bodies). Stated differently, the present utilities make use of high resolution overhead imagery data to determine how to distribute the population density of a large, low resolution cell (e.g., 1000m) among a plurality of smaller, high resolution cells (e.g., 100m) within the larger cell.

Abstract: A system for automatically characterizing areas of interest (e.g., urban areas, forests, and/or other compound structures) in high resolution overhead imagery through manipulation of a dictionary of visual words. The pixels of an input overhead image are initially clustered into a plurality of hierarchically-arranged connected components of a first hierarchical data structure. Image descriptors (e.g., shape, spectral, etc.) of the connected components are then clustered into a plurality of hierarchically-arranged nodes of a second hierarchical data structure. The nodes at a particular level in the second hierarchical data structure become a dictionary of visual words. Subsets of the visual words may be used to label the cells of a grid over the geographic area as falling into one of a number of areas of interest. Categorization information from the grid may be mapped into a resultant image whereby pixels depict their respective type of area of interest.

Abstract: A system for automated conversion of two-dimensional hydrology vector models into valid three-dimensional hydrology vector models, comprising a vector extraction engine that retrieves vectors from, and sends vectors to, a vector storage, a DSM server that retrieves a DSM from a DSM storage and computes a DSM from stereo disparity measurements of a stereo pair retrieved from a raster storage, and a rendering engine that provides visual representations of images for review by a human user, and a method for automated hydrology vector model development utilizing the system of the invention.

Abstract: Land classification based on analysis of image data. Feature extraction techniques may be used to generate a feature stack corresponding to the image data to be classified. A user may identify training data from the image data from which a classification model may be generated using one or more machine learning techniques applied to one or more features of the image. In this regard, the classification module may in turn be used to classify pixels from the image data other than the training data. Additionally, quantifiable metrics regarding the accuracy and/or precision of the models may be provided for model evaluation and/or comparison. Additionally, the generation of models may be performed in a distributed system such that model creation and/or application may be distributed in a multi-user environment for collaborative and/or iterative approaches.

Abstract: Automatic characterization or categorization of portions of an input multispectral image based on a selected reference multispectral image. Sets (e.g., vectors) of radiometric descriptors of pixels of each component of a hierarchical representation of the input multispectral image can be collectively manipulated to obtain a set of radiometric descriptors for the component. Each component can be labeled as a (e.g., relatively) positive or negative instance of at least one reference multispectral image (e.g., mining materials, crops, etc.) through a comparison of the set of radiometric descriptors of the component and a set of radiometric descriptors for the reference multispectral image. Pixels may be labeled (e.g., via color, pattern, etc.) as positive or negative instances of the land use or type of the reference multispectral image in a resultant image based on components within which the pixels are found.

Abstract: A system for analysis of remotely sensed image data of parking facilities, storage lots, or road regions, for determining patterns over time and determine time-based information such as facility capacities or vehicle movement.

Abstract: A system for automated mosaic-based vector editing comprising a mosaic imaging server that assembles image tiles to form larger image mosaics while correcting the image tiles for tonality and other visual characteristics, a vector analysis server that analyzes vector information, a routing calculation server that calculates routes from the vector information, and a rendering engine that produces visualizations from the routing information, and a method for image mosaic creation and correction.

Abstract: A system for automated geospatial image analysis comprising a deep learning model module and a convolutional neural network serving as an automated image analysis software module. The deep learning module receives a plurality of orthorectified geospatial images, pre-labeled to demarcate objects of interest, and optimized for the purpose of training the neural network of the image analysis software module. The module presents marked geospatial images and a second set of unmarked, optimized, training geospatial images to the convolutional neural network. This process may be repeated so that an image analysis software module can detect multiple object types or categories. The image analysis software module receives a plurality of orthorectified geospatial images from one or more geospatial image caches. Using multi-scale sliding window submodule, image analysis modules scan geospatial images, detect objects present and locate them on the geographical latitude-longitude system.

Abstract: A system for automated tonal balancing, comprising a rectification server that groups and processes images for use in tone-matching and provides them to a tone-matching server, that then performs tone-matching operations on the images and provides them as output for review or storage, and methods for tonal balancing using the system of the invention.