{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T15:46:18Z","timestamp":1778859978557,"version":"3.51.4"},"reference-count":63,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,2,11]],"date-time":"2022-02-11T00:00:00Z","timestamp":1644537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1948997, 1948994, and 1948857"],"award-info":[{"award-number":["1948997, 1948994, and 1948857"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Differencing multi-temporal topographic data (radar, lidar, or photogrammetrically derived point clouds or digital elevation models\u2014DEMs) measures landscape change, with broad applications for scientific research, hazard management, industry, and urban planning. The United States Geological Survey\u2019s 3D Elevation Program (3DEP) is an ambitious effort to collect light detection and ranging (lidar) topography over the United States\u2019 lower 48 and Interferometric Synthetic Aperture Radar (IfSAR) in Alaska by 2023. The datasets collected through this program present an important opportunity to characterize topography and topographic change at regional and national scales. We present Indiana statewide topographic differencing results produced from the 2011\u20132013 and 2016\u20132020 lidar collections. We discuss the insights, challenges, and lessons learned from conducting large-scale differencing. Challenges include: (1) designing and implementing an automated differencing workflow over 94,000 km2 of high-resolution topography data, (2) ensuring sufficient computing resources, and (3) managing the analysis and visualization of the multiple terabytes of data. We highlight observations including infrastructure development, vegetation growth, and landscape change driven by agricultural practices, fluvial processes, and natural resource extraction. With 3DEP and the U.S. Interagency Elevation Inventory data, at least 37% of the Contiguous 48 U.S. states are already covered by repeat, openly available, high-resolution topography datasets, making topographic differencing possible.<\/jats:p>","DOI":"10.3390\/rs14040847","type":"journal-article","created":{"date-parts":[[2022,2,14]],"date-time":"2022-02-14T03:46:00Z","timestamp":1644810360000},"page":"847","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Statewide USGS 3DEP Lidar Topographic Differencing Applied to Indiana, USA"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3884-4693","authenticated-orcid":false,"given":"Chelsea Phipps","family":"Scott","sequence":"first","affiliation":[{"name":"School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Beckley","sequence":"additional","affiliation":[{"name":"UNAVCO, Boulder, CO 80301, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minh","family":"Phan","sequence":"additional","affiliation":[{"name":"San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emily","family":"Zawacki","sequence":"additional","affiliation":[{"name":"School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2522-4193","authenticated-orcid":false,"given":"Christopher","family":"Crosby","sequence":"additional","affiliation":[{"name":"UNAVCO, Boulder, CO 80301, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0928-9851","authenticated-orcid":false,"given":"Viswanath","family":"Nandigam","sequence":"additional","affiliation":[{"name":"San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ramon","family":"Arrowsmith","sequence":"additional","affiliation":[{"name":"School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2017.09.013","article-title":"Big Remotely Sensed Data: Tools, Applications and Experiences","volume":"202","author":"Casu","year":"2017","journal-title":"Remote Sens. 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