PIGLT: A Pollen Identification and Geolocation system for forensic applications

The Department of Homeland Security, Science and Technology Directorate (DHS/S&T) is exploring the feasibility to geolocate pollen grains found on goods or people for compliance with U.S. import laws and criminal forensics. A multidisciplinary team built the Pollen Identification and Geolocation Technology (PIGLT) system to help users identify pollen samples and perform geolocation. Identification is performed using either traditional family, genus and species information, or a morphological ID system based on an existing database of herbaria samples. As the user makes morphological decisions, visual aids help exclude pollen taxa that lack given attributes. The user systematically lowers the number of matches until the number is small enough for visual identification. PIGLT has ~5 images per sample, but experiments with Z-stack imagery may positively affect human identification. Given grain identities, geolocation proceeds using distributions developed using Maxent. The database is implemented in PostgreSQL and the userinterface uses Django, a high-level Python Web framework.