Abstract: Systems, methods, and other embodiments associated with indexing spatial data in a distributed file system are described. A query window defining a portion of a spatial data space is received, and candidate partitions containing the spatial data within the query window are identified. An intermediate partition dataset comprising each of the identified candidate partitions is created. Execution of a distributed function is limited to the identified candidate partitions, and a data structure including at least one record included in the result of the query is generated, and returned as the result of the query over a communication network.

Abstract: Systems, methods, and other embodiments associated with computerized geo-referencing of images are described. In one embodiment, a method includes extracting features from an image of a location. The method includes determining similarities between the extracted features and known features within vector data for the location. The method includes generating a data structure based upon the similarities. The method includes processing the similarities to identify a match between an extracted feature and a known feature. The method includes assigning geo-location data from the vector data for the known feature to the extracted feature. The method includes identifying a position of an object within the location using the geo-location data.

Abstract: Systems, methods, and other embodiments associated with indexing spatial data in a distributed file system are described. A query window defining a portion of a spatial data space is received, and candidate partitions containing the spatial data within the query window are identified. An intermediate partition dataset comprising each of the identified candidate partitions is created. Execution of a distributed function is limited to the identified candidate partitions, and a data structure including at least one record included in the result of the query is generated, and returned as the result of the query over a communication network.

Abstract: Systems, methods, and other embodiments are disclosed for identifying features within point cloud data. In one embodiment, point cloud data is read which represents multiple points of at least one point cloud in a multi-dimensional space. Each point in the point cloud data is defined by an attribute value quantifying an attribute of the point and a set of coordinates specifying a location of the point in the multi-dimensional space. The set of coordinates for each point is transformed into a space-filling distance value representing a distance along a space-filling curve. The points are sorted according to the space-filling distance values to generate a sorted order of the points. The points are traversed in the sorted order and output data points are derived, while traversing the points, based on a specified feature criterion. The output data points identify a feature within the at least one point cloud.

Abstract: Systems, methods, and other embodiments associated with computerized geo-referencing of images are described. In one embodiment, a method includes extracting features from an image of a location. The example method may also include determining similarities between the extracted features and known features within vector data for the location. The example method may also include generating a data structure based upon the similarities. The example method may also include processing the similarities to identify a match between an extracted feature and a known feature. The example method may also include assigning geo-location data from the vector data for the known feature to the extracted feature. The example method may also include identifying a position of an object within the location using the geo-location data.

Abstract: Systems, methods, and other embodiments are disclosed for identifying features within point cloud data. In one embodiment, point cloud data is read which represents multiple points of at least one point cloud in a multi-dimensional space. Each point in the point cloud data is defined by an attribute value quantifying an attribute of the point and a set of coordinates specifying a location of the point in the multi-dimensional space. The set of coordinates for each point is transformed into a space-filling distance value representing a distance along a space-filling curve. The points are sorted according to the space-filling distance values to generate a sorted order of the points. The points are traversed in the sorted order and output data points are derived, while traversing the points, based on a specified feature criterion. The output data points identify a feature within the at least one point cloud.