{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T20:48:40Z","timestamp":1770842920247,"version":"3.50.1"},"reference-count":23,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T00:00:00Z","timestamp":1729814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Norwegian Space Centre"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Norwegian Environment Agency is responsible for updating a map of undisturbed nature, which is performed every five years based on aerial photos. Some of the aerial photos are already up to five years old when a new version of the map of undisturbed nature is published. Thus, several new nature interventions may have been missed. To address this issue, the timeliness and mapping accuracy were improved by integrating Sentinel-2 satellite imagery for the detection of new roads across Norway. The focus on new roads was due to the fact that most new nature interventions include the construction of new roads. The proposed methodology is based on applying U-Net on all the available summer images with less than 10% cloud cover over a five-year period, with an aggregation step to summarize the predictions. The observed detection rate was 98%. Post-processing steps reduced the false positive rate to 46%. However, as the false positive rate was still substantial, the manual verification of the predicted new roads was needed. The false negative rate was low, except in areas without vegetation.<\/jats:p>","DOI":"10.3390\/rs16213972","type":"journal-article","created":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T08:42:13Z","timestamp":1729845733000},"page":"3972","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["National-Scale Detection of New Forest Roads in Sentinel-2 Time Series"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3817-9777","authenticated-orcid":false,"given":"\u00d8ivind Due","family":"Trier","sequence":"first","affiliation":[{"name":"Norwegian Computing Center, Postboks 114 Blindern, NO-0314 Oslo, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8113-8460","authenticated-orcid":false,"given":"Arnt-B\u00f8rre","family":"Salberg","sequence":"additional","affiliation":[{"name":"Norwegian Computing Center, Postboks 114 Blindern, NO-0314 Oslo, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1023\/A:1008129329289","article-title":"Landscape division, splitting index, and effective mesh size: New measures of landscape fragmentation","volume":"15","author":"Jaeger","year":"2000","journal-title":"Landsc. 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