Methods and systems for geospatial identification of media streams

A system comprising:

• one or more processors;
• and
• a non-transitory machine-readable medium storing instructions that when executed by the one or more processors, cause the one or more processors to perform operations including:
• displaying a first representation of a first geographical area;
• including icons representing locations of a first set of broadcast sources within the first geographical area;
• extracting user characteristics from a first user device, wherein the user characteristics include geospatial data indicative of a location of the first user device within the first geographical area;
• receiving an identification of a second geographical area to simulate, wherein the second geographical area is different from the first geographical area;
• executing a machine-learning model using the user characteristics and the identification of the second geographical area, the machine-learning model being configured to generate a prediction of contemporaneous broadcast characteristics associated with the second geographical area, wherein the contemporaneous broadcast characteristics include an identification of a simulated location of the first user device within the second geographical area;
• displaying a second representation of the second geographical area based on the contemporaneous broadcast characteristics, wherein the second representation includes icons representing locations of a second set of broadcast sources within the second geographical area, and wherein the locations of the second set of broadcast sources are selected based on the simulated location of the first user device;
• and
• facilitating a presentation of media from a particular broadcast source of the second set of broadcast sources.

A non-transitory machine-readable medium storing instructions that when executed by one or more processors, cause the one or more processors to perform operations including:

• displaying a first representation of a first geographical area including icons representing locations of a first set of broadcast sources within the first geographical area;
• extracting user characteristics from a first user device, wherein the user characteristics include geospatial data indicative of a location of the first user device within the first geographical area;
• receiving an identification of a second geographical area to simulate, wherein the second geographical area is different from the first geographical area;
• executing a machine-learning model using the user characteristics and the identification of the second geographical area, the machine-learning model being configured to generate a prediction of contemporaneous broadcast characteristics associated with the second geographical area, wherein the contemporaneous broadcast characteristics include an identification of a simulated location of the first user device within the second geographical area;
• displaying a second representation of the second geographical area based on the contemporaneous broadcast characteristics, wherein the second representation includes icons representing locations of a second set of broadcast sources within the second geographical area, and wherein the locations of the second set of broadcast sources are selected based on the simulated location of the first user device;
• and
• facilitating a presentation of media from a particular broadcast source of the second set of broadcast sources.