{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T23:52:44Z","timestamp":1782345164530,"version":"3.54.5"},"reference-count":49,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,10,3]],"date-time":"2021-10-03T00:00:00Z","timestamp":1633219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Freely available satellite data at Google Earth Engine (GEE) cloud platform enables vegetation phenology analysis across different scales very efficiently. We evaluated seasonal and annual phenology of the old-growth Hyrcanian forests (HF) of northern Iran covering an area of ca. 1.9 million ha, and also focused on 15 UNESCO World Heritage Sites. We extracted bi-weekly MODIS-NDVI between 2017 and 2020 in GEE, which was used to identify the range of NDVI between two temporal stages. Then, changes in phenology and growth were analyzed by Sentinel 2-derived Temporal Normalized Phenology Index. We modelled between seasonal phenology and growth by additionally considering elevation, surface temperature, and monthly precipitation. Results indicated considerable difference in onset of forests along the longitudinal gradient of the HF. Faster growth was observed in low- and uplands of the western zone, whereas it was lower in both the mid-elevations and the western outskirts. Longitudinal range was a major driver of vegetation growth, to which environmental factors also differently but significantly contributed (p &lt; 0.0001) along the west-east gradient. Our study developed at GEE provides a benchmark to examine the effects of environmental parameters on the vegetation growth of HF, which cover mountainous areas with partly no or limited accessibility.<\/jats:p>","DOI":"10.3390\/rs13193965","type":"journal-article","created":{"date-parts":[[2021,10,8]],"date-time":"2021-10-08T21:26:20Z","timestamp":1633728380000},"page":"3965","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Vegetation Growth Analysis of UNESCO World Heritage Hyrcanian Forests Using Multi-Sensor Optical Remote Sensing Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Suyash","family":"Khare","sequence":"first","affiliation":[{"name":"Department of Computer Science, GIS Division, NIIT University, Neemrana 301705, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1054-889X","authenticated-orcid":false,"given":"Hooman","family":"Latifi","sequence":"additional","affiliation":[{"name":"Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran"},{"name":"Department of Remote Sensing, University of W\u00fcrzburg, D-97070 W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6996-4583","authenticated-orcid":false,"given":"Siddhartha","family":"Khare","sequence":"additional","affiliation":[{"name":"Department of Biology, McGill University, Montreal, QC H3A 1B1, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/j.tree.2005.05.011","article-title":"Using the satellite-derived NDVI to assess ecological responses to environmental change","volume":"20","author":"Pettorelli","year":"2005","journal-title":"Trends Ecol. 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