orcid:
meta: status_code: 200 timestamp: '2023-10-20T08:42:11.067904' url: https://orcid.org/0000-0002-1201-5459 orcid: activities: works: group: - external-ids: external-id: - external-id-normalized: transient: true value: 10.3390/rs15194894 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.3390/rs15194894 external-id-value: 10.3390/rs15194894 last-modified-date: value: 1697242138600 work-summary: - created-date: value: 1696873829176 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.3390/rs15194894 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.3390/rs15194894 external-id-value: 10.3390/rs15194894 journal-title: value: Remote Sensing last-modified-date: value: 1696873829176 path: /0000-0002-1201-5459/work/144002947 publication-date: day: value: 09 month: value: '10' year: value: '2023' put-code: 144002947 source: assertion-origin-client-id: null assertion-origin-name: null assertion-origin-orcid: null source-client-id: host: orcid.org path: 0000-0001-9884-1913 uri: https://orcid.org/client/0000-0001-9884-1913 source-name: value: Crossref source-orcid: null title: subtitle: null title: value: "Crop Water Productivity from Cloud-Based Landsat Helps Assess\ \ California\u2019s Water Savings" translated-title: null type: journal-article url: value: https://doi.org/10.3390/rs15194894 visibility: public - created-date: value: 1697242138600 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.3390/rs15194894 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.3390/rs15194894 external-id-value: 10.3390/rs15194894 journal-title: value: Remote Sensing last-modified-date: value: 1697242138600 path: /0000-0002-1201-5459/work/144390823 publication-date: day: null month: value: '10' year: value: '2023' put-code: 144390823 source: assertion-origin-client-id: null assertion-origin-name: null assertion-origin-orcid: null source-client-id: host: orcid.org path: APP-WRQOUAK78G5F7GMD uri: https://orcid.org/client/APP-WRQOUAK78G5F7GMD source-name: value: Multidisciplinary Digital Publishing Institute source-orcid: null title: subtitle: null title: value: "Crop Water Productivity from Cloud-Based Landsat Helps Assess\ \ California\u2019s Water Savings" translated-title: null type: journal-article url: value: https://www.mdpi.com/2072-4292/15/19/4894 visibility: public - external-ids: external-id: - external-id-normalized: transient: true value: 10.1109/jstars.2022.3204223 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.1109/JSTARS.2022.3204223 external-id-value: 10.1109/JSTARS.2022.3204223 last-modified-date: value: 1663789139405 work-summary: - created-date: value: 1662416891548 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.1109/jstars.2022.3204223 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.1109/JSTARS.2022.3204223 external-id-value: 10.1109/JSTARS.2022.3204223 journal-title: value: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing last-modified-date: value: 1663789139405 path: /0000-0002-1201-5459/work/118486022 publication-date: day: null month: null year: value: '2022' put-code: 118486022 source: assertion-origin-client-id: null assertion-origin-name: null assertion-origin-orcid: null source-client-id: host: orcid.org path: 0000-0001-9884-1913 uri: https://orcid.org/client/0000-0001-9884-1913 source-name: value: Crossref source-orcid: null title: subtitle: null title: value: New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification translated-title: null type: journal-article url: value: https://doi.org/10.1109/JSTARS.2022.3204223 visibility: public - external-ids: external-id: - external-id-normalized: transient: true value: 10.1080/17538947.2019.1651912 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.1080/17538947.2019.1651912 external-id-value: 10.1080/17538947.2019.1651912 last-modified-date: value: 1653785800639 work-summary: - created-date: value: 1567059364554 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.1080/17538947.2019.1651912 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.1080/17538947.2019.1651912 external-id-value: 10.1080/17538947.2019.1651912 journal-title: value: International Journal of Digital Earth last-modified-date: value: 1653785800639 path: /0000-0002-1201-5459/work/61031898 publication-date: day: value: '02' month: value: 08 year: value: '2020' put-code: 61031898 source: assertion-origin-client-id: null assertion-origin-name: null assertion-origin-orcid: null source-client-id: host: orcid.org path: 0000-0001-9884-1913 uri: https://orcid.org/client/0000-0001-9884-1913 source-name: value: Crossref source-orcid: null title: subtitle: null title: value: A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades translated-title: null type: journal-article url: value: https://doi.org/10.1080/17538947.2019.1651912 visibility: public - external-ids: external-id: - external-id-normalized: transient: true value: 10.3390/rs10122027 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.3390/rs10122027 external-id-value: 10.3390/rs10122027 last-modified-date: value: 1653670258289 work-summary: - created-date: value: 1545098572555 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.3390/rs10122027 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.3390/rs10122027 external-id-value: 10.3390/rs10122027 journal-title: value: Remote Sensing last-modified-date: value: 1653670258289 path: /0000-0002-1201-5459/work/51757003 publication-date: day: null month: value: '12' year: value: '2018' put-code: 51757003 source: assertion-origin-client-id: null assertion-origin-name: null assertion-origin-orcid: null source-client-id: host: orcid.org path: APP-WRQOUAK78G5F7GMD uri: https://orcid.org/client/APP-WRQOUAK78G5F7GMD source-name: value: Multidisciplinary Digital Publishing Institute source-orcid: null title: subtitle: null title: value: Accuracies Achieved in Classifying Five Leading World Crop Types and their Growth Stages Using Optimal Earth Observing-1 Hyperion Hyperspectral Narrowbands on Google Earth Engine translated-title: null type: journal-article url: value: http://www.mdpi.com/2072-4292/10/12/2027 visibility: public - external-ids: external-id: - external-id-normalized: transient: true value: 10.1002/ece3.2876 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.1002/ece3.2876 external-id-value: 10.1002/ece3.2876 last-modified-date: value: 1694969845426 work-summary: - created-date: value: 1493088947662 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.1002/ece3.2876 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: value: https://doi.org/10.1002/ece3.2876 external-id-value: 10.1002/ece3.2876 journal-title: value: Ecology and Evolution last-modified-date: value: 1694969845426 path: /0000-0002-1201-5459/work/32121770 publication-date: day: null month: value: '05' year: value: '2017' put-code: 32121770 source: assertion-origin-client-id: null assertion-origin-name: null assertion-origin-orcid: null source-client-id: host: orcid.org path: 0000-0001-9884-1913 uri: https://orcid.org/client/0000-0001-9884-1913 source-name: value: Crossref source-orcid: null title: subtitle: null title: value: "Correlating species and spectral diversities using hyperspectral\ \ remote sensing in early\u2010successional fields" translated-title: null type: journal-article url: value: https://doi.org/10.1002/ece3.2876 visibility: public - external-ids: external-id: - external-id-normalized: transient: true value: 10.1080/01431161.2016.1259682 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: null external-id-value: 10.1080/01431161.2016.1259682 last-modified-date: value: 1653495522174 work-summary: - created-date: value: 1493137923542 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.1080/01431161.2016.1259682 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: null external-id-value: 10.1080/01431161.2016.1259682 journal-title: value: International Journal of Remote Sensing last-modified-date: value: 1653495522174 path: /0000-0002-1201-5459/work/32141180 publication-date: day: null month: value: '11' year: value: '2016' put-code: 32141180 source: assertion-origin-client-id: null assertion-origin-name: value: Itiya Aneece assertion-origin-orcid: host: orcid.org path: 0000-0002-1201-5459 uri: https://orcid.org/0000-0002-1201-5459 source-client-id: host: orcid.org path: 0000-0002-3054-1567 uri: https://orcid.org/client/0000-0002-3054-1567 source-name: value: Crossref Metadata Search source-orcid: null title: subtitle: null title: value: Identifying invasive plant species using field spectroscopy in the VNIR region in successional systems of north-central Virginia translated-title: null type: journal-article url: null visibility: public - external-ids: external-id: - external-id-normalized: transient: true value: 10.1080/00091383.2016.1198186 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: null external-id-value: 10.1080/00091383.2016.1198186 last-modified-date: value: 1653495521648 work-summary: - created-date: value: 1493137885069 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.1080/00091383.2016.1198186 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: null external-id-value: 10.1080/00091383.2016.1198186 journal-title: value: 'Change: The Magazine of Higher Learning' last-modified-date: value: 1653495521648 path: /0000-0002-1201-5459/work/32141087 publication-date: day: value: '03' month: value: '07' year: value: '2016' put-code: 32141087 source: assertion-origin-client-id: null assertion-origin-name: value: Itiya Aneece assertion-origin-orcid: host: orcid.org path: 0000-0002-1201-5459 uri: https://orcid.org/0000-0002-1201-5459 source-client-id: host: orcid.org path: 0000-0002-3054-1567 uri: https://orcid.org/client/0000-0002-3054-1567 source-name: value: Crossref Metadata Search source-orcid: null title: subtitle: null title: value: Does the Document Matter? The Evolving Role of Syllabi in Higher Education translated-title: null type: journal-article url: null visibility: public - external-ids: external-id: - external-id-normalized: transient: true value: 10.3390/rs71215850 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: null external-id-value: 10.3390/rs71215850 last-modified-date: value: 1653495522052 work-summary: - created-date: value: 1493137919087 display-index: '0' external-ids: external-id: - external-id-normalized: transient: true value: 10.3390/rs71215850 external-id-normalized-error: null external-id-relationship: self external-id-type: doi external-id-url: null external-id-value: 10.3390/rs71215850 journal-title: value: Remote Sensing last-modified-date: value: 1653495522052 path: /0000-0002-1201-5459/work/32141160 publication-date: day: null month: null year: value: '2015' put-code: 32141160 source: assertion-origin-client-id: null assertion-origin-name: value: Itiya Aneece assertion-origin-orcid: host: orcid.org path: 0000-0002-1201-5459 uri: https://orcid.org/0000-0002-1201-5459 source-client-id: host: orcid.org path: 0000-0002-3054-1567 uri: https://orcid.org/client/0000-0002-3054-1567 source-name: value: Crossref Metadata Search source-orcid: null title: subtitle: null title: value: Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data translated-title: null type: journal-article url: null visibility: public last-modified-date: value: 1697242138600 path: /0000-0002-1201-5459/works history: claimed: true completion-date: null creation-method: MEMBER_REFERRED deactivation-date: null last-modified-date: value: 1697242138593 source: null submission-date: value: 1441381610857 verified-email: true verified-primary-email: true person: name: created-date: value: 1460757225450 credit-name: null family-name: value: Aneece given-names: value: Itiya last-modified-date: value: 1460757225450 path: 0000-0002-1201-5459 source: null visibility: public
usgs_staff_profile:
meta: status_code: 200 timestamp: '2023-09-30T16:37:19.494687' url: https://www.usgs.gov/staff-profiles/itiya-p-aneece profile: abstracts: [] affiliations: [] education: [] email: ianeece@usgs.gov expertise_terms: - Remote Sensing - Crops - Invasive Plant Species - Big Data Analysis - Machine Learning - Hyperspectral remote sensing - Machine learning and cloud computing - Crop water productivity honors: [] intro_statements: - Itiya Aneece is currently a Research Geographer at the U.S. Geological Survey (USGS) in Flagstaff, AZ, USA. name: Itiya P Aneece name_qualifier: null orcid: 0000-0002-1201-5459 organization_link: https://www.usgs.gov/centers/western-geographic-science-center organization_name: Western Geographic Science Center personal_statement: At the USGS, she is working with the Western Geographic Science Center using hyperspectral and multispectral remote sensing to study globally dominant agricultural crops. She is also working on a variety of projects with the Astrogeology Science Center. Dr. Aneece earned a PhD in Environmental Sciences from the University of Virginia, where she conducted her dissertation research on studying the impacts of invasive plant species on secondary successional dynamics in abandoned agricultural fields using ground-level hyperspectral remote sensing. She has also recently completed a Mendenhall Postdoctoral Fellowship within the Western Geographic Science Center, in which she studied crops using Hyperion hyperspectral satellite data in Google Earth Engine. professional_experience: [] title: Research Geographer