Systems and methods for pest pressure heat maps

A method for generating heat maps, the method implemented using a heat map generation computing device including a memory communicatively coupled to a processor, the method comprising:

• receiving trap data for a plurality of pest traps in a geographic location, the trap data including current and historical pest pressure values at each of the plurality of pest traps;
• receiving weather data for the geographic location;
• receiving image data for the geographic location;
• applying a machine learning algorithm to the trap data, the weather data, and the image data to generate predicted future pest pressure values at each of the plurality of pest traps;
• generating a first heat map for a first point in time and a second heat map for a second point in time, the second heat map generated using the predicted future pest pressure values, the first and second heat maps each generated by:
• plotting a plurality of nodes on a map of the geographic location, each node corresponding to one of the plurality of pest traps, each node having a color that represents the pest pressure value for the corresponding pest trap at the associated point in time;
• and
• coloring at least some remaining portions of the map of the geographic location to generate a continuous map of pest pressure values for the geographic location by interpolating between pest pressure values associated with the plurality of nodes at the associated point in time;
• and
• transmitting the first and second heat maps to a mobile computing device to cause a user interface on the mobile computing device to display a time lapse heat map that dynamically transitions between the first heat map and the second heat map over time, the user interface implemented via an application installed on the mobile computing device.

A computer-readable storage medium having computer-executable instructions embodied thereon, wherein when executed by a heat map generation computing device including at least one processor in communication with a memory, the computer-readable instructions cause the heat map generation computing device to:

• receive trap data for a plurality of pest traps in a geographic location, the trap data including current and historical pest pressure values at each of the plurality of pest traps;
• receive weather data for the geographic location;
• receive image data for the geographic location;
• apply a machine learning algorithm to the trap data, the weather data, and the image data to generate predicted future pest pressure values at each of the plurality of pest traps;
• generate a first heat map for a first point in time and a second heat map for a second point in time, the second heat map generated using the predicted future pest pressure values, the first and second heat maps each generated by:
• plotting a plurality of nodes on a map of the geographic location, each node corresponding to one of the plurality of pest traps, each node having a color that represents the pest pressure value for the corresponding pest trap at the associated point in time;
• and
• coloring at least some remaining portions of the map of the geographic location to generate a continuous map of pest pressure values for the geographic location by interpolating between pest pressure values associated with the plurality of nodes at the associated point in time;
• and
• transmit the first and second heat maps to a mobile computing device to cause a user interface on the mobile computing device to display a time lapse heat map that dynamically transitions between the first heat map and the second heat map over time, the user interface implemented via an application installed on the mobile computing device.