Abstract: A system for automated geospatial image analysis comprising a deep learning model that receives orthorectified geospatial images, pre-labeled to demarcate objects of interest. The module presents marked geospatial images and a second set of unmarked, optimized, training geospatial images to a 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 orthorectified geospatial images from one or more geospatial image caches. Using a multi-scale sliding window submodule, image analysis software scans geospatial images, detects objects present and geospatially locates them.

Abstract: A system and various methods for processing an image to produce a hierarchical image representation model, segment the image model using shape criteria to produce positive and negative training data sets as well as a search-space data set comprising shapes matched to a search query provided as input, and using the training data sets to train a machine learning model to improve recognition of shapes that are similar to an input query without being exact matches, to improve object recognition.

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 large-scale crowd sourcing of map data cleanup and correction, comprising an application server that generates image data, sends image data to a user device, receives tagging data provided by the device user, and provides tags to a crowdsourced search and locate server based on tagging data from a user device, a crowdsourced search and locate server that receives tags from an application server, computes agreement and disagreement values and performs expectation-maximization analysis, and a map data server that stores and provides map data, and a method for estimating location and quality of a set of geolocation data.

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 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: 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.

Abstract: A system for automated vector updating, comprising a database that stores raster and vector information, and a vector processing server that algorithmically processes vectors for updates, and methods for algorithm-based vector updating.

Abstract: A crowdsourced search and locate platform has been developed and put into practice. A plurality of geospatial images of a geographical region of interest are presented to a plurality of participants in an internet mediated crowdsourcing campaign for the purpose of identifying and tagging specific features of interest to the campaign administrator. An algorithm of the invention, CrowdRank, monitors the identification accuracy of the participants both absolute and compared to other participants calculating a score used to weight each identification made by that user. CrowdRank also chooses images to maximize campaign efficiency and calculates the confidence level of each feature identification.

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: A system for advanced vector editing, comprising 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 several methods for advanced vector editing in two- and three-dimensional visualizations.

Abstract: A database for creating orthomosaics, where the database is tailored to retrieve the most recent imagery for each pixel, in an efficient manner that partitions the orthomosaic into sufficiently small chunks that can each be quickly processed.

Abstract: A system for enhanced geospatial modeling using a spectral data analytic cube classifier and normalized multispectral raster data, comprising a geospatial modeling server that receives and analyzes input imagery, a data import/export server that provides data for review or interaction and receives data to provide to the analysis server, and a database that stores data, and a method for enhanced geospatial modeling using raster data according to the system of the invention.

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 incorporating geographical data into a map-related system, adding objects being tracked while moving within a specific geographic area and automatically analyzing their movement characteristics; wherein the tracking is done by visual means from a sky-borne platform.

Abstract: Techniques for automatically determining, on a pixel by pixel basis, whether imagery includes ground images or is obscured by cloud cover. The techniques include training a cloud dictionary and a ground dictionary, determining whether a given pixel is best represented by “words” from the cloud dictionary or “words” from the ground dictionary to make an initial determination of cloud or ground, and performing a max-flow, min-cut operation on the image to determine whether each pixel is a cloud or ground imagery.

Abstract: A system for large-scale crowd sourcing of map data cleanup and correction, comprising an application server that generates image data, sends image data to a user device, receives tagging data provided by the device user, and provides tags to a crowdsourced search and locate server based on tagging data from a user device, a crowdsourced search and locate server that receives tags from an application server, computes agreement and disagreement values and performs expectation-maximization analysis, and a map data server that stores and provides map data, and a method for estimating location and quality of a set of geolocation data.

Abstract: A crowdsourced search and locate platform, comprising an application server that receives input from a plurality of user devices and navigates to a particular location, sends images of the location to a user device, and receives tagging data provided by the device user, and a client interface application that displays a plurality of interactive elements to a user, receive input from the user, and provide the results of the input to the application server, and methods for operating and administering a crowdsourced search and locate platform.

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 operating an integrated architecture for near real-time satellite communications, comprising a plurality of collector satellites augment by aerial and terrestrial sensing systems that capture a plurality of EO, SAR and/or Signals sensor data of a portion of a region of the surface of the Earth, and a plurality of connector satellites that communicate with at least a collector satellite using a communication interface, and a method for using advanced environmental monitoring to adaptively task a collector satellite.