Vector control remains an important strategy worldwide to prevent human infection with pathogens transmitted by arthropods. Vector control strategies rely on accurate identification of vector taxa along with vector-specific biological indicators such as feeding ecology, infection prevalence and insecticide resistance. Multiple 'DNA barcoding' protocols have been published over the past several decades to support these applications, generally relying on informal manual approaches such as BLAST to assign taxonomic identity to the resulting sequences. We present a standardised informatic pipeline for analysis of DNA barcoding data from dipteran vectors, VecTreeID, that uses short-read amplicon sequencing (AmpSeq) coupled with sequence similarity assessment (BLAST) and an evolutionary placement algorithm (EPA-ng) to achieve vector taxonomic identification, capture bionomic features (blood and plant meal sources), determine Plasmodium infection status (for anopheline mosquitoes) and detect target-site insecticide resistance mutations. The VecTreeID pipeline provides uncertainty in assignment through identifications at varying levels of taxonomic rank, a feature missing from many approaches to DNA barcoding, but important given gaps and labelling problems in public sequence databases. We validated an Illumina-based implementation of VecTreeID on laboratory and field samples, and find that the blood meal amplicons can detect vertebrate DNA sequences up to 36 h post-feeding, and that short-read sequencing data are capable of sensitively detecting minor sequences in DNA mixtures representing multi-species blood or nectar meals. This high-throughput VecTreeID approach empowers researchers and public health professionals to survey and control arthropod disease vectors consistently and effectively.