{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T14:30:57Z","timestamp":1761489057865,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2012,12,24]],"date-time":"2012-12-24T00:00:00Z","timestamp":1356307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The interferometric coherence parameter \u03b3 estimates the degree of correlation between two Synthetic Aperture Radar (SAR) images and can be influenced by vegetation structure. Here, we investigate the use of repeat-pass interferometric coherence \u03b3 to map stand age, an important parameter for the study of carbon stocks and forest regeneration. In August 2009 NASA\u2019s L-band airborne sensor UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) acquired zero-baseline data over Quebec with temporal separation ranging between 45 min and 9 days. Our analysis focuses on a 66 km2 managed boreal forest and addresses three questions: (i) Can coherence from L-band systems be used to model forest age? (ii) Are models sensitive to weather events and temporal baseline? and (iii) How is model accuracy impacted by the spatial scale of analysis? Linear regression models with 2-day baseline showed the best results and indicated an inverse relationship between \u03b3 and stand age. Model accuracy improved at 5 ha scale (R2 = 0.75, RMSE = 5.3) as compared to 1 ha (R2 = 0.67, RMSE = 5.8). Our results indicate that coherence measurements from L-band repeat-pass systems can estimate forest age accurately and with no saturation. However, empirical model relationships and their accuracy are sensitive to weather events, temporal baseline, and spatial scale of analysis.<\/jats:p>","DOI":"10.3390\/rs5010042","type":"journal-article","created":{"date-parts":[[2012,12,24]],"date-time":"2012-12-24T07:41:06Z","timestamp":1356334866000},"page":"42-56","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Using InSAR Coherence to Map Stand Age in a Boreal Forest"],"prefix":"10.3390","volume":"5","author":[{"given":"Naiara","family":"Pinto","sequence":"first","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, 2181 LeFrak Hall, College Park, MD 20742, USA"}]},{"given":"Marc","family":"Simard","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory\/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA"}]},{"given":"Ralph","family":"Dubayah","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, 2181 LeFrak Hall, College Park, MD 20742, USA"}]}],"member":"1968","published-online":{"date-parts":[[2012,12,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"18866","DOI":"10.1073\/pnas.0702737104","article-title":"Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks","volume":"104","author":"Canadell","year":"2007","journal-title":"Proc. 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