Inclusion of time-series geospatial markers in analyses employing a cyber-decision platform
A system for programmatic and user interactive inclusion of time-series geospatial markers in analyses employing a cyber-decision platform has been developed comprising a module to retrieve an indexed geospatial image tiles and map overlay data corresponding to tiles. The system may attach a unique geo-hash label to each point of an indexed geospatial image tile based upon the point's geographical coordinates such that points in close proximity will have similar geo-hash values. A web application interface allows users to interactively retrieve and visualize indexed geospatial image tiles, add map overlays and create geo-hashes as desired.
1. A system for highly scalable parallel world simulations, comprising:
a plurality of computing devices each comprising at least a processor, a memory, and a network interface;
wherein a plurality of programming instructions stored in one or more of the memories and operating on one or more of the processors of the plurality of computing devices causes the plurality of computing devices to:
retrieve a plurality of geospatial image tiles corresponding to a geographic region from a plurality of sources;
retrieve a plurality of geotagged data corresponding to the geographic region;
calculate a geohash for each piece of retrieved geotagged data, wherein a geohash is an encoded geographic location comprising a short string of letters and digits;
overlay the geohash on the corresponding geospatial image tile containing the geographic coordinates of the geohash;
assign each geographic region and the corresponding geotagged data to a unique process execution swimlane;
execute simulations within each unique process execution swimlane using its respective geotagged data;
generate updated geospatial image tile data based on results of the simulations;
transmit the updated geospatial image tile data to a user via a network; and
send map overlay data for at least one of the transmitted updated geospatial image tiles to the user via the network;
wherein the geohashes for each pair of geographic regions have a degree of string similarity that is inversely proportional to the geographic distance between the respective geographic regions, such that geohashes for proximate geographic regions share longer common prefixes than geohashes for distant geographic regions.
2. The system of claim 1 , wherein the geographic region is a geographical location made up of at least one geographical point.
3. The system of claim 1 , wherein the geographic region is a geographical region made up of a plurality of geographical locations.
4. The system of claim 1 , wherein post-simulation data is stored and retrieved for further analysis.
5. The system of claim 1 , wherein the plurality of geotagged data comprises streaming data from sensors.
6. The system of claim 1 , wherein executing simulations comprises running parallel world simulations on aggregated geospatial image tiles and corresponding geotagged data for a geographic region to predict real-world outcomes.
7. The system of claim 1 , wherein:
the plurality of geotagged data comprises sensor data from multiple real-world locations within the geographic region; and
the simulations generate predicted future sensor data values for those locations.
8. A method for highly scalable parallel world simulations, comprising the steps of:
retrieving a plurality of geospatial image tiles corresponding to a geographic region from a plurality of sources;
retrieving a plurality of geotagged data corresponding to the geographic region;
calculating a geohash for each piece of retrieved geotagged data, wherein a geohash is an encoded geographic location comprising a short string of letters and digits; and
overlaying the geohash on the corresponding geospatial image tile containing the geographic coordinates of the geohash;
assigning each geographic region and the corresponding geotagged data to a unique process execution swimlane;
executing simulations for within each unique process execution swimlane using its respective geotagged data;
generating updated geospatial image tile data based on results of the simulations;
transmitting the updated geospatial image tile data to a user via a network; and
sending map overlay data for at least one of the transmitted updated geospatial image tiles to the user via the network;
wherein the geohashes for each pair of geographic regions have a degree of string similarity that is inversely proportional to the geographic distance between the respective geographic regions, such that geohashes for proximate geographic regions share longer common prefixes than geohashes for distant geographic regions.
9. The method of claim 8 , wherein the geographic region is a geographical location made up of at least one geographical point.
10. The method of claim 8 , wherein the geographic region is a geographical region made up of a plurality of geographical locations.
11. The system of claim 8 , wherein post-simulation data is stored and retrieved for further analysis.
12. The system of claim 8 , wherein the plurality of geotagged data comprises streaming data from sensors.
13. One or more non-transitory computer-storage media having computer-executable instructions embodied thereon that, when executed by one or more processors of a computing system employing a similarity subsystem, cause the computing system to perform the method of claim 8 .
14. The method of claim 8 , wherein executing simulations comprises running parallel world simulations on aggregated geospatial image tiles and corresponding geotagged data for a geographic region to predict real-world outcomes.
15. The method of claim 8 , wherein:
the plurality of geotagged data comprises sensor data from multiple real-world locations within the geographic region; and
the simulations generate predicted future sensor data values for those locations.