{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T10:32:47Z","timestamp":1724063567449},"reference-count":25,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T00:00:00Z","timestamp":1671062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005416","name":"The Research Council of Norway","doi-asserted-by":"publisher","award":["269927"],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Horizion 2020 project ArcticHubs","award":["869580"]},{"name":"Generalitat Valenciana","award":["SEJIGENT\/2021\/001"]},{"name":"European Union\u2013Next Generation EU","award":["ZAMBRANO 21-04"]},{"name":"European Research Council (ERC) under the ERC-2017-STG SENTIFLEX project","award":["755617"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"The global temperature is increasing, and this is affecting the vegetation phenology in many parts of the world. The most prominent changes occur at northern latitudes such as our study area, which is Svalbard, located between 76\u00b030\u2032N and 80\u00b050\u2032N. A cloud-free time series of MODIS-NDVI data was processed. The dataset was interpolated to daily data during the 2000\u20132020 period with a 231.65 m pixel resolution. The onset of vegetation growth was mapped with a NDVI threshold method which corresponds well with a recent Sentinel-2 NDVI-based mapping of the onset of vegetation growth, which was in turn validated by a network of in-situ phenological data from time lapse cameras. The results show that the years 2000 and 2008 were extreme in terms of the late onset of vegetation growth. The year 2020 had the earliest onset of vegetation growth on Svalbard during the 21-year study. Each year since 2013 had an earlier or equally early timing in terms of the onset of the growth season compared with the 2000\u20132020 average. A linear trend of 0.57 days per year resulted in an earlier onset of growth of 12 days on average for the entire archipelago of Svalbard in 2020 compared to 2000.<\/jats:p>","DOI":"10.3390\/rs14246346","type":"journal-article","created":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T09:25:26Z","timestamp":1671096326000},"page":"6346","source":"Crossref","is-referenced-by-count":4,"title":["Changes in Onset of Vegetation Growth on Svalbard, 2000\u20132020"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-9456-6990","authenticated-orcid":false,"given":"Stein Rune","family":"Karlsen","sequence":"first","affiliation":[{"name":"NORCE Norwegian Research Centre AS, P.O. Box 6434, 9294 Troms\u00f8, Norway"}]},{"given":"Arve","family":"Elvebakk","sequence":"additional","affiliation":[{"name":"Noregs Arktiske Universitetsmuseum, UiT\u2014The Arctic University of Norway, 9037 Troms\u00f8, Norway"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-7273-1695","authenticated-orcid":false,"given":"Hans","family":"T\u00f8mmervik","sequence":"additional","affiliation":[{"name":"Norwegian Institute for Nature Research (NINA), FRAM\u2014High North Research Centre for Climate and the Environment, Langnes, P.O. Box 6606, 9296 Troms\u00f8, Norway"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-3739-6056","authenticated-orcid":false,"given":"Santiago","family":"Belda","sequence":"additional","affiliation":[{"name":"Applied Mathematics Department, University of Alicante, 03080 Alicante, Spain"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9802-8962","authenticated-orcid":false,"given":"Laura","family":"Stendardi","sequence":"additional","affiliation":[{"name":"Department of Agriculture, Food, Environment, and Forestry (DAGRI), University of Florence, Piazzale Delle Cascine 18, 50144 Florence, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1038\/s41586-018-0555-7","article-title":"Widespread Seasonal Compensation Effects of Spring Warming on Northern Plant Productivity","volume":"562","author":"Buermann","year":"2018","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"11931","DOI":"10.1002\/2016JD025606","article-title":"Recent Warming on Spitsbergen-Influence of Atmospheric Circulation and Sea Ice Cover","volume":"121","author":"Isaksen","year":"2016","journal-title":"J. Geophys. Res."},{"unstructured":"Hanssen-Bauer, I., F\u00f8rland, E., Hisdal, H., Mayer, S., and Sand\u00f8, A. (2022, October 29). Climate in Svalbard 2100\u2014A Knowledge Base for Climate Adaptation; 2019. Available online: https:\/\/repository.oceanbestpractices.org\/handle\/11329\/1382.","key":"ref_3"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"9371","DOI":"10.1038\/s41598-022-13568-5","article-title":"Exceptional Warming over the Barents Area","volume":"12","author":"Isaksen","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1038\/nclimate1836","article-title":"Temperature and Vegetation Seasonality Diminishment over Northern Lands","volume":"3","author":"Xu","year":"2013","journal-title":"Nat. Clim. Chang."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2013.11.020","article-title":"Remotely Sensed Trends in the Phenology of Northern High Latitude Terrestrial Vegetation, Controlling for Land Cover Change and Vegetation Type","volume":"143","author":"Jeganathan","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"084001","DOI":"10.1088\/1748-9326\/11\/8\/084001","article-title":"Changes in Growing Season Duration and Productivity of Northern Vegetation Inferred from Long-Term Remote Sensing Data","volume":"11","author":"Park","year":"2016","journal-title":"Environ. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4304","DOI":"10.3390\/rs5094304","article-title":"Trends in the Start of the Growing Season in Fennoscandia 1982\u20132011","volume":"5","author":"Karlsen","year":"2013","journal-title":"Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4621","DOI":"10.1038\/s41467-020-18479-5","article-title":"Summer Warming Explains Widespread but Not Uniform Greening in the Arctic Tundra Biome","volume":"11","author":"Berner","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.rse.2011.12.015","article-title":"Evaluation of Earth Observation Based Global Long Term Vegetation Trends\u2014Comparing GIMMS and MODIS Global NDVI Time Series","volume":"119","author":"Fensholt","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.rse.2015.03.031","article-title":"Evaluating Temporal Consistency of Long-Term Global NDVI Datasets for Trend Analysis","volume":"163","author":"Tian","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3147","DOI":"10.1111\/gcb.12647","article-title":"Vegetation Productivity Patterns at High Northern Latitudes: A Multi-Sensor Satellite Data Assessment","volume":"20","author":"Guay","year":"2014","journal-title":"Glob. Change Biol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1038\/s41558-019-0688-1","article-title":"Complexity Revealed in the Greening of the Arctic","volume":"10","author":"Kerby","year":"2020","journal-title":"Nat. Clim. Chang."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"8088","DOI":"10.3390\/rs6098088","article-title":"Spatial and Temporal Variability in the Onset of the Growing Season on Svalbard, Arctic Norway\u2014Measured by MODIS-NDVI Satellite Data","volume":"6","author":"Karlsen","year":"2014","journal-title":"Remote Sens."},{"unstructured":"Norwegian Centre for Climate Services (2022, October 23). Meterological Data. Available online: https:\/\/seklima.met.no\/observations\/.","key":"ref_15"},{"doi-asserted-by":"crossref","unstructured":"Karlsen, S.R., Stendardi, L., T\u00f8mmervik, H., Nilsen, L., Arntzen, I., and Cooper, E.J. (2021). Time-Series of Cloud-Free Sentinel-2 NDVI Data Used in Mapping the Onset of Growth of Central Spitsbergen, Svalbard. Remote Sens., 13.","key":"ref_16","DOI":"10.3390\/rs13153031"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1017\/S0032247411000647","article-title":"Vegetation Mapping of Svalbard Utilising Landsat TM\/ETM+ Data","volume":"48","author":"Johansen","year":"2012","journal-title":"Polar Rec."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1109\/TGRS.2011.2168963","article-title":"Nonlinear Statistical Retrieval of Atmospheric Profiles From MetOp-IASI and MTG-IRS Infrared Sounding Data","volume":"50","author":"Guanter","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"104666","DOI":"10.1016\/j.envsoft.2020.104666","article-title":"DATimeS: A Machine Learning Time Series GUI Toolbox for Gap-Filling and Vegetation Phenology Trends Detection","volume":"127","author":"Belda","year":"2020","journal-title":"Environ. Model. Softw."},{"unstructured":"Karlsen, S.R., and H\u00f8gda, K.-A. (2014). Endringer i Start P\u00e5 Vekstsesongen P\u00e5 Svalbard i Relasjon Til Klima, NORUT.","key":"ref_20"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"114021","DOI":"10.1088\/1748-9326\/9\/11\/114021","article-title":"Warmer and Wetter Winters: Characteristics and Implications of an Extreme Weather Event in the High Arctic","volume":"9","author":"Hansen","year":"2014","journal-title":"Environ. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.1016\/j.scitotenv.2017.05.050","article-title":"Understanding the Drivers of Extensive Plant Damage in Boreal and Arctic Ecosystems: Insights from Field Surveys in the Aftermath of Damage","volume":"599\u2013600","author":"Bjerke","year":"2017","journal-title":"Sci. Total Environ."},{"doi-asserted-by":"crossref","unstructured":"Anderson, H.B., Nilsen, L., T\u00f8mmervik, H., Karlsen, S.R., Nagai, S., and Cooper, E.J. (2016). Using Ordinary Digital Cameras in Place of Near-Infrared Sensors to Derive Vegetation Indices for Phenology Studies of High Arctic Vegetation. Remote Sens., 8.","key":"ref_23","DOI":"10.3390\/rs8100847"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/BF00139438","article-title":"Scales of Climate Impacts","volume":"7","author":"Clark","year":"1985","journal-title":"Clim. Change"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.rse.2018.04.041","article-title":"Short Term Changes in Moisture Content Drive Strong Changes in Normalized Difference Vegetation Index and Gross Primary Productivity in Four Arctic Moss Communities","volume":"212","author":"May","year":"2018","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/24\/6346\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,11]],"date-time":"2024-08-11T05:55:00Z","timestamp":1723355700000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/24\/6346"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,15]]},"references-count":25,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["rs14246346"],"URL":"https:\/\/doi.org\/10.3390\/rs14246346","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,12,15]]}}}