Item talk:Q54489
From geokb
{
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Jeff is also the ECCOE Lidar Co-Lead. In addition to working with ECCOE, Jeff also leads fieldwork for the Terrain Modeling and Monitoring Focus Area of the EROS Integrated Science and Applications Branch (ISAB). Jeff is responsible for ensuring high quality field data is collected, processed, and published for a variety of activities, including developing methodologies to access the accuracy of airborne lidar and accessing the accuracy of airborne topographic and topobathymetric lidar systems for the USGS 3D Elevation Program (3DEP), validating Landsat products, mapping river bluffs for sediment transport and erosion modeling, and validating regional topobathymetric digital elevation models (TBDEMs). Jeff relies heavily on his years of experience working for a private land surveying firm to conduct this work.Jeff started with the USGS at EROS on a Pathways Internship with the Fire Science Focus Area within ISAB in 2016. Jeff's work as an intern focused on developing methodology to map understory fuels in northeastern Minnesota using airborne lidar data. Jeff also worked on mapping historic fires for the Fish and Wildlife Service using Landsat imagery. In addition to those activities, Jeff has supported Fire Science by leading efforts to collect ground based lidar data to be used for improving burn severity modeling by looking at 3D forest structure changes." } ], "email": "jrirwin@usgs.gov", "url": "https://www.usgs.gov/staff-profiles/jeffrey-r-irwin", "affiliation": [], "hasCredential": [ { "@type": "EducationalOccupationalCredential", "name": "M.S., 2018, Geography, South Dakota State University, Thesis: Quantification of Understory Fuels in the Superior Nation Forest using Lidar Data" }, { "@type": "EducationalOccupationalCredential", "name": "B.S., 2014, Geography, South Dakota State University" }, { "@type": "EducationalOccupationalCredential", "name": "A.A.S., 2009, Civil Engineering Technology, Southeast Technical Institute" } ], "knowsAbout": [ { "@type": "Thing", "additionalType": "self-claimed expertise", "name": "Surveying" }, { "@type": "Thing", "additionalType": "self-claimed expertise", "name": "Ground Based Lidar" }, { "@type": "Thing", "additionalType": "self-claimed expertise", "name": "Lidar" } ], "memberOf": { "@type": "OrganizationalRole", "name": "staff member", "member": { "@type": "Organization", "name": "U.S. Geological Survey" }, "startDate": "2024-09-21T07:58:58.214340" } }, "ORCID": { "@context": "http://schema.org", "@id": "https://orcid.org/0000-0001-5828-0787", "@reverse": { "creator": [ { "@id": "https://doi.org/10.3390/rs16091492", "@type": "CreativeWork", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.3390/rs16091492" }, "name": "Landsat 8 and 9 Underfly International Surface Reflectance Validation Collaboration" }, { "@id": "https://doi.org/10.5066/p9ahfc7f", "@type": "CreativeWork", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5066/p9ahfc7f" }, "name": "ECCOE 2022 Surface Reflectance Validation Dataset" }, { "@id": "https://doi.org/10.3390/rs15235451", "@type": "CreativeWork", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.3390/rs15235451" }, "name": "Implementing a Dual-Spectrometer Approach for Improved Surface Reflectance Estimation" }, { "@id": "https://doi.org/10.5066/p9z25kvq", "@type": "CreativeWork", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5066/p9z25kvq" }, "name": "2021 McKenzie River Topobathymetric Lidar Validation - 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