Abstract: Described herein are various technologies relating to constructing a differenced change product (DCP) image. A plurality of synthetic aperture radar (SAR) images of a scene are generated based upon radar signals directed towards and reflected off of the scene, and a plurality of coherence change detection (CCD) images of the scene are generated based upon the SAR images. The CCD images are registered with one another, and their pixel values re-scaled according to a monotonic mapping function. The DCP image is generated based upon a computed pixel-wise difference between a pair of the re-scaled CCD images. The DCP image identifies locations in the scene where human activity-induced change is likely to have occurred between a pair of SAR passes of the scene.

Abstract: Described herein are various technologies relating to constructing a statistically-normalized coherence (SNC) image. A plurality of synthetic aperture radar (SAR) images of a scene are generated based upon radar signals directed towards and reflected off of the scene, and a plurality of coherence change detection (CCD) images of the scene are generated based upon the SAR images. The CCD images are registered with one another, and mean and variance are computed on a pixel-wise basis. A new CCD image is subsequently received, and registered with the plurality of CCD images. The SNC image is generated based upon the computed mean and variance values for each pixel in the registered CCD images, and further based upon values of pixels in the new CCD image. The SNC image identifies locations in the scene where anomalous activity is represented in the new CCD image.

Abstract: The various technologies presented herein relate to detecting small moving entities or targets in radar imagery. Two SAR images can be captured for a common scene, wherein the scene is imaged twice from the same flight path. The first image is captured at a first instance and the second image is captured at a second instance, and differences between the two images are determined using a complex SAR change measure, excess coherency factor or DeltaC, based in part upon quantification of incoherent (or magnitude) change between the two images. A plurality of operations are performed to enable extraction of coherent change measures relating to the small moving entities from measures relating to large objects, stationary reflective structures, radar focusing artifacts, etc.

Abstract: Various embodiments presented herein relate to assigning labels to segments of a synthetic aperture radar (SAR) image, where the segments are based upon a speckle-reduced SAR image product. A plurality of SAR images of a scene are co-registered to form a registered stack of SAR images. A speckle-reduced SAR image product is generated based upon at least one registered SAR image in the registered stack of SAR images. The speckle-reduced SAR image product is segmented into a plurality of superpixels, and boundaries of the superpixels are applied to the at least one registered SAR image to form a segmented SAR image. A segment of the SAR image is then labeled as including or not including a feature, wherein the label is assigned based upon values of pixels in the segment.

Abstract: Various technologies pertaining to identifying objects of interest in remote sensing images by searching over geospatial-temporal graph representations are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Geospatial-temporal graph searches are made computationally efficient by taking advantage of characteristics of geospatial-temporal data in remote sensing images through the application of various graph search techniques.

Abstract: Various technologies for facilitating analysis of large remote sensing and geolocation datasets to identify features of interest are described herein. A search query can be submitted to a computing system that executes searches over a geospatial temporal semantic (GTS) graph to identify features of interest. The GTS graph comprises nodes corresponding to objects described in the remote sensing and geolocation datasets, and edges that indicate geospatial or temporal relationships between pairs of nodes in the nodes. Trajectory information is encoded in the GTS graph by the inclusion of movable nodes to facilitate searches for features of interest in the datasets relative to moving objects such as vehicles.

Abstract: A set of co-registered coherent change detection (CCD) products is produced from a set of temporally separated synthetic aperture radar (SAR) images of a target scene. A plurality of transformations are determined, which transformations are respectively for transforming a plurality of the SAR images to a predetermined image coordinate system. The transformations are used to create, from a set of CCD products produced from the set of SAR images, a corresponding set of co-registered CCD products.