Toward effective high-throughput georeferencing over voluminous observational data in the domain of precision agriculture
| dc.contributor.author | Roselius, Maxwell L., author | |
| dc.contributor.author | Pallickara, Sangmi Lee, advisor | |
| dc.contributor.author | Pallickara, Shrideep, committee member | |
| dc.contributor.author | McKay, John, committee member | |
| dc.date.accessioned | 2019-01-07T17:19:47Z | |
| dc.date.available | 2019-01-07T17:19:47Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | 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. | |
| dc.format.medium | born digital | |
| dc.format.medium | masters theses | |
| dc.identifier | Roselius_colostate_0053N_15249.pdf | |
| dc.identifier.uri | https://hdl.handle.net/10217/193210 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | |
| dc.relation.ispartof | 2000-2019 | |
| dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
| dc.subject | georeferencing | |
| dc.subject | precision agriculture | |
| dc.subject | high-throughput | |
| dc.subject | distributed systems | |
| dc.title | Toward effective high-throughput georeferencing over voluminous observational data in the domain of precision agriculture | |
| dc.type | Text | |
| dcterms.rights.dpla | This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.grantor | Colorado State University | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science (M.S.) |
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