Processing techniques for generating, tracking, and visualizing environmental insights

A computer-implemented method, the computer-implemented method comprising:

• receiving, by one or more processors, one or more hyperspectral image frames corresponding to at least a portion of a geographic region;
• generating, by the one or more processors and using one or more machine learning models, one or more landcover predictions for the geographic region based at least in part on the one or more hyperspectral image frames, wherein:
• (i) the one or more landcover predictions correspond to one or more geographic portions within the geographic region, and
• (ii) the one or more machine learning models are trained using at least a plurality of historical hyperspectral image frames that correspond to one or more labeled geographic portions within one or more geographic regions;
• and
• initiating, by the one or more processors and through an interactive user interface, a presentation of the one or more landcover predictions to a user.

A computer program product comprising a non-transitory computer readable medium having computer program instructions stored therein, the computer program instructions when executed by one or more processors, cause the one or more processors to:

• receive one or more hyperspectral image frames corresponding to at least a portion of a geographic region;
• generate, using one or more machine learning models, one or more landcover predictions for the geographic region based at least in part on the one or more hyperspectral image frames, wherein:
• (i) the one or more landcover predictions correspond to one or more geographic portions within the geographic region, and
• (ii) the one or more machine learning models are trained using at least a plurality of historical hyperspectral image frames that correspond to one or more labeled geographic portions within one or more geographic regions;
• and
• initiate, through an interactive user interface, a presentation of the one or more landcover predictions to a user.