Toward effective high-throughput georeferencing over voluminous observational data in the domain of precision agriculture - Roselius, Maxwell L., author; Pallickara, Sangmi Lee, advisor; Pallickara, Shrideep, committee member; McKay, John, committee member (Colorado State University. Libraries, 2018)
Remote sensing of plant traits and their environment facilitates non-invasive, high-throughput monitoring of the plant's physiological characteristics. Effective ingestion of these sensing data into a storage subsystem while georeferencing phenotyping setups is key to providing timely access to scientists and modelers. In this thesis, we propose a high-throughput distributed data ingestion framework with support for fine-grained georeferencing. The methodology includes a novel spatial indexing scheme, the nested hash grid, for fine-grained georeferencing of data while conserving memory footprints and ensuring acceptable latency. We include empirical evaluations performed on a commodity machine cluster with up to 1TB of data. The benchmarks demonstrate the efficacy of our approach.
Keywords: georeferencing; precision agriculture; high-throughput; distributed systems