Method of generating at-scale geospatial features of designated attribution and geometry

A method of improving the accuracy of a model using mimicking training data, the method comprising:

• receiving, at a trained model, mimicking training data generated by a process comprising:
• selecting, by a user, a schema having desired or required characteristics, related to geospatial features, for the mimicking training data to comply with the schema;
• selecting, by the user, one or more evaluation protocols associated with the selected schema;
• creating generator modules for the evaluation protocols;
• creating an internal data structure to compile and record mimicking generated training data, the mimicking generated training data being generated from the generator modules after the schema is selected, the internal data structure comprising a plurality of bounding boxes wherein at least a first bounding box is arranged to only contain generated data that comply with the schema and at least a second bounding box is arranged to only contain generated data that do not comply with the schema;
• executing the generator modules to create the mimicking generated data according to the internal data structure, wherein the mimicking generated training data comprises geospatial features including map features;
• and
• improving the accuracy of the model by further iteratively training the model using, at least in part, mimicking generated training data newly generated based on real-world data.

A method of creating mimicking training data, the method comprising:

• selecting, a schema having desired or required characteristics, related to geospatial features, for the mimicking training data to comply with the schema;
• selecting, one or more evaluation protocols associated with the selected schema;
• creating generator modules for the evaluation protocols;
• creating an internal data structure to compile and record mimicking generated training data, the mimicking generated training data being generated from the generator modules after the schema is selected, the internal data structure comprising a plurality of bounding boxes wherein at least a first bounding box is arranged to only contain mimicking generated training data that comply with the schema and at least a second bounding box is arranged to only contain mimicking generated training data that do not comply with the schema;
• executing the generator modules to create the mimicking generated training data according to the internal data structure, wherein the mimicking generated training data comprises geospatial features including map features;
• and
• training the model using one or more simulations, provided by the mimicking generated training data, as training data.