Abstract: Systems and methods are provided for selecting, pricing, and prioritizing images obtained by a constellation of imaging satellites. The systems and methods presented can determine whether an imagery collection request should be accepted or rejected. If the imagery collection request is accepted, the systems and methods presented can determine an appropriate pricing option for the imagery collection request and how the imagery collection request should be prioritized in relation to other outstanding imagery collection requests.

Abstract: Systems and methods for providing a user interface for searching, browsing, and ordering overhead (e.g. aircraft or satellite) imagery are provided. The user interface provides a map and search bar for searching and browsing images. Images may be presented to a user based on a selected and/or displayed geographic region of interest. Browsing to a different geographic region of interest may dynamically and automatically update the images presented. The user interface allows the user to select an image for viewing and/or purchase. Selection of an image overlays the image on the map, aligned with the geographic region which the image captures. Closing the selected image re-centers and re-zooms to the original display. Presented images can be filtered based on several criteria. Images can include still images and/or videos.

Abstract: Systems and methods are provided for scheduling objects having pair-wise and cumulative constraints. The systems and methods presented can utilize a directed acyclic graph to increase or maximize a utilization function. Violation of cumulative constraints can be identified at the moment of constraint violation such that events resulting in constraint violations can be removed from the schedule while the schedule is being determined. By removing the events triggering constraint violations at the point of constraint violation, the systems and methods provided can determine optimal or near-optimal schedules in a relatively quick and efficient manner compared to systems and methods that check for violations of cumulative constraints after determining a schedule. The objects can comprise satellites in a constellation of satellites.

Abstract: Examples of an imaging sensor include a two-dimensional staring sensor with spectral filter strips for multispectral overhead imaging. The sensor may also include a panchromatic sensor with block or strip filters. The sensor may be used to collect multispectral color image data at a sampling resolution from overhead imaging platforms such as airplanes or satellites. The sensor can be used to provide video images. If a panchromatic sensor is included, the sensor may be used to collect panchromatic image data. Examples of methods for processing the image date include using the panchromatic image data to perform multi-frame enhancement or panchromatic sharpening on spectral images to improve their quality and resolution.

Abstract: Systems and methods are provided for scheduling objects having pair-wise and cumulative constraints. The systems and methods presented can utilize a directed acyclic graph to increase or maximize a utilization function. Violation of cumulative constraints can be identified at the moment of constraint violation such that events resulting in constraint violations can be removed from the schedule while the schedule is being determined. By removing the events triggering constraint violations at the point of constraint violation, the systems and methods provided can determine optimal or near-optimal schedules in a relatively quick and efficient manner compared to systems and methods that check for violations of cumulative constraints after determining a schedule. The objects can comprise satellites in a constellation of satellites.

Abstract: Systems and methods are provided for scheduling objects having pair-wise and cumulative constraints. The systems and methods presented can utilize a directed acyclic graph to increase or maximize a utilization function. Violation of cumulative constraints can be identified at the moment of constraint violation such that events resulting in constraint violations can be removed from the schedule while the schedule is being determined. By removing the events triggering constraint violations at the point of constraint violation, the systems and methods provided can determine optimal or near-optimal schedules in a relatively quick and efficient manner compared to systems and methods that check for violations of cumulative constraints after determining a schedule. The objects can comprise satellites in a constellation of satellites.

Abstract: Described are systems, methods, computer programs, and user interfaces for image location, acquisition, analysis, and data correlation that uses human-in-the-loop processing, Human Intelligence Tasks (HIT), and/or or automated image processing. Results obtained using image analysis are correlated to non-spatial information useful for commerce and trade. For example, images of regions of interest of the earth are used to count items (e.g., cars in a store parking lot to predict store revenues), detect events (e.g., unloading of a container ship, or evaluating the completion of a construction project), or quantify items (e.g., the water level in a reservoir, the area of a farming plot).

Abstract: Examples of satellite scheduling systems are provided that use crowd-sourced data to generate image acquisition events for a network of imaging satellites. A crowd-sourcing system may utilize crowd-sourced data (e.g., messages generated by users of social network services) to determine events of interest and geographic locations of such events. Event data may then be used to create or update image acquisition tasks and/or task priorities which are automatically provided to a scheduling system to facilitate timely and responsive acquisition of overhead images of the geographic location of the event. The scheduling system can utilize a directed acyclic graph to increase or maximize a utilization function, which can lead to determination of optimal or near-optimal schedules in a relatively quick and efficient manner.

Abstract: Described are systems, methods, computer programs, and user interfaces for image location, acquisition, analysis, and data correlation that uses human-in-the-loop processing, Human Intelligence Tasks (HIT), and/or or automated image processing. Results obtained using image analysis are correlated to non-spatial information useful for commerce and trade. For example, images of regions of interest of the earth are used to count items (e.g., cars in a store parking lot to predict store revenues), detect events (e.g., unloading of a container ship, or evaluating the completion of a construction project), or quantify items (e.g., the water level in a reservoir, the area of a farming plot).

Abstract: Systems and methods are provided for scheduling objects having pair-wise and cumulative constraints. The systems and methods presented can utilize a directed acyclic graph to increase or maximize a utilization function. Violation of cumulative constraints can be identified at the moment of constraint violation such that events resulting in constraint violations can be removed from the schedule while the schedule is being determined. By removing the events triggering constraint violations at the point of constraint violation, the systems and methods provided can determine optimal or near-optimal schedules in a relatively quick and efficient manner compared to systems and methods that check for violations of cumulative constraints after determining a schedule. The objects can comprise satellites in a constellation of satellites.

Abstract: Examples of satellite scheduling systems are provided that use crowd-sourced data to generate image acquisition events for a network of imaging satellites. A crowd-sourcing system may utilize crowd-sourced data (e.g., messages generated by users of social network services) to determine events of interest and geographic locations of such events. Event data may then be used to create or update image acquisition tasks and/or task priorities which are automatically provided to a scheduling system to facilitate timely and responsive acquisition of overhead images of the geographic location of the event. The scheduling system can utilize a directed acyclic graph to increase or maximize a utilization function, which can lead to determination of optimal or near-optimal schedules in a relatively quick and efficient manner.

Abstract: Systems and methods for providing a user interface for searching, browsing, and ordering overhead (e.g. aircraft or satellite) imagery are provided. The user interface provides a map and search bar for searching and browsing images. Images may be presented to a user based on a selected and/or displayed geographic region of interest. Browsing to a different geographic region of interest may dynamically and automatically update the images presented. The user interface allows the user to select an image for viewing and/or purchase. Selection of an image overlays the image on the map, aligned with the geographic region which the image captures. Closing the selected image re-centers and re-zooms to the original display. Presented images can be filtered based on several criteria. Images can include still images and/or videos.

Abstract: Examples of an imaging sensor include a two-dimensional staring sensor with spectral filter strips for multispectral overhead imaging. The sensor may also include a panchromatic sensor with block or strip filters. The sensor may be used to collect multispectral color image data at a sampling resolution from overhead imaging platforms such as airplanes or satellites. The sensor can be used to provide video images. If a panchromatic sensor is included, the sensor may be used to collect panchromatic image data. Examples of methods for processing the image date include using the panchromatic image data to perform multi-frame enhancement or panchromatic sharpening on spectral images to improve their quality and resolution.

Abstract: Described are systems, methods, computer programs, and user interfaces for image location, acquisition, analysis, and data correlation that uses human-in-the-loop processing, Human Intelligence Tasks (HIT), and/or or automated image processing. Results obtained using image analysis are correlated to non-spatial information useful for commerce and trade. For example, images of regions of interest of the earth are used to count items (e.g., cars in a store parking lot to predict store revenues), detect events (e.g., unloading of a container ship, or evaluating the completion of a construction project), or quantify items (e.g., the water level in a reservoir, the area of a farming plot).

Abstract: Described are systems, methods, computer programs, and user interfaces for image location, acquisition, analysis, and data correlation that uses human-in-the-loop processing, Human Intelligence Tasks (HIT), and/or or automated image processing. Results obtained using image analysis are correlated to non-spatial information useful for commerce and trade. For example, images of regions of interest of the earth are used to count items (e.g., cars in a store parking lot to predict store revenues), detect events (e.g., unloading of a container ship, or evaluating the completion of a construction project), or quantify items (e.g., the water level in a reservoir, the area of a farming plot).

Abstract: Described are systems, methods, computer programs, and user interfaces for image location, acquisition, analysis, and data correlation that uses human-in-the-loop processing, Human Intelligence Tasks (HIT), and/or or automated image processing. Results obtained using image analysis are correlated to non-spatial information useful for commerce and trade. For example, images of regions of interest of the earth are used to count items (e.g., cars in a store parking lot to predict store revenues), detect events (e.g., unloading of a container ship, or evaluating the completion of a construction project), or quantify items (e.g., the water level in a reservoir, the area of a farming plot).

Abstract: Described are systems, methods, computer programs, and user interfaces for image location, acquisition, analysis, and data correlation that uses human-in-the-loop processing, Human Intelligence Tasks (HIT), and/or or automated image processing. Results obtained using image analysis are correlated to non-spatial information useful for commerce and trade. For example, images of regions of interest of the earth are used to count items (e.g., cars in a store parking lot to predict store revenues), detect events (e.g., unloading of a container ship, or evaluating the completion of a construction project), or quantify items (e.g., the water level in a reservoir, the area of a farming plot).

Abstract: Examples of an imaging sensor include a two-dimensional staring sensor with spectral filter strips for multispectral overhead imaging. The sensor may also include a panchromatic sensor with block or strip filters. The sensor may be used to collect multispectral color image data at a sampling resolution from overhead imaging platforms such as airplanes or satellites. The sensor can be used to provide video images. If a panchromatic sensor is included, the sensor may be used to collect panchromatic image data. Examples of methods for processing the image date include using the panchromatic image data to perform multi-frame enhancement or panchromatic sharpening on spectral images to improve their quality and resolution.

Abstract: Examples of an imaging sensor include a two-dimensional staring sensor with spectral filter strips for multispectral overhead imaging. The sensor may also include a panchromatic sensor with block or strip filters. The sensor may be used to collect multispectral color image data at a sampling resolution from overhead imaging platforms such as airplanes or satellites. The sensor can be used to provide video images. If a panchromatic sensor is included, the sensor may be used to collect panchromatic image data. Examples of methods for processing the image date include using the panchromatic image data to perform multi-frame enhancement or panchromatic sharpening on spectral images to improve their quality and resolution.