{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:18:43Z","timestamp":1760145523273,"version":"build-2065373602"},"reference-count":60,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,8,2]],"date-time":"2024-08-02T00:00:00Z","timestamp":1722556800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004281","name":"National Science Centre in Poland","doi-asserted-by":"publisher","award":["2021\/41\/B\/ST10\/04113"],"award-info":[{"award-number":["2021\/41\/B\/ST10\/04113"]}],"id":[{"id":"10.13039\/501100004281","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In light of recently accelerating global warming, the changes in vegetation trends are vital for the monitoring of the dynamics of both whole ecosystems and individual species. Detecting changes within the time series of specific forest ecosystems or species is very important in the context of assessing their vulnerability to climate change and other negative phenomena. Hence, the aim of this paper was to identify the trend change points and periods of greening and browning in multi-annual time series of the normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI) of four main forest-forming tree species in the temperate zone: pine, spruce, oak and beech. The research was conducted over the last two decades (2002\u20132022), and was based on vegetation indices data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). To this end, several research approaches, including calculating the linear trends in the moving periods and BEAST algorithm, were adapted. A pattern of browning then greening then constant was detected for coniferous species, mostly pine. In turn, for broadleaved species, namely oak and beech, a pattern of greening then constant was identified, without the initial phase of browning. The main trend change points seem to be ca. 2006 and ca. 2015 for coniferous species and solely around 2015 for deciduous ones.<\/jats:p>","DOI":"10.3390\/rs16152844","type":"journal-article","created":{"date-parts":[[2024,8,2]],"date-time":"2024-08-02T13:14:42Z","timestamp":1722604482000},"page":"2844","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Temporal Patterns of Vegetation Greenness for the Main Forest-Forming Tree Species in the European Temperate Zone"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0605-534X","authenticated-orcid":false,"given":"Kinga","family":"Kulesza","sequence":"first","affiliation":[{"name":"Centre of Applied Geomatics, Institute of Geodesy and Cartography, 27 Modzelewskiego Street, 02-679 Warsaw, Poland"}]},{"given":"Agata","family":"Ho\u015bci\u0142o","sequence":"additional","affiliation":[{"name":"Institute of Environmental Protection\u2014National Research Institute, 32 S\u0142owicza Street, 02-170 Warsaw, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,2]]},"reference":[{"key":"ref_1","unstructured":"FAO, and UNEP (2020). The State of the World\u2019s Forests 2020. Forests, Biodiversity and People, FAO and UNEP."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1146\/annurev-ecolsys-110512-135914","article-title":"The Structure, Distribution, and Biomass of the World\u2019s Forests","volume":"44","author":"Pan","year":"2013","journal-title":"Annu. Rev. Ecol. Evol. Syst."},{"key":"ref_3","unstructured":"Forest Europe (2020). State of Europe\u2019s Forests 2020, Ministerial Conference on the Protection of Forests in Europe\u2014FOREST EUROPE, Liaison Unit Bratislava."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1038\/386698a0","article-title":"Increased plant growth in the northern high latitudes from 1981 to 1991","volume":"386","author":"Myneni","year":"1997","journal-title":"Nature"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1655","DOI":"10.5194\/bg-17-1655-2020","article-title":"Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003","volume":"17","author":"Buras","year":"2020","journal-title":"Biogeosciences"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11676-020-01155-1","article-title":"A commentary review on the use of Normalized Difference Vegetation Index (NDVI) in the era of popular remote sensing","volume":"32","author":"Huang","year":"2021","journal-title":"J. For. Res."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Soubry, I., Doan, T., Chu, T., and Guo, X. (2021). A Systematic Review on the Integration of Remote Sensing and GIS to Forest and Grassland Ecosystem Health Attributes, Indicators, and Measures. Remote Sens., 13.","DOI":"10.3390\/rs13163262"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Gomez, D.F., Ritger, H.M.W., Pearce, C., Eickwort, J., and Hulcr, J. (2020). Ability of Remote Sensing Systems to Detect Bark Beetle Spots in the Southeastern US. Forests, 11.","DOI":"10.3390\/f11111167"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"7021","DOI":"10.1111\/gcb.15360","article-title":"Large-scale early-wilting response of Central European forests to the 2018 extreme drought","volume":"26","author":"Brun","year":"2020","journal-title":"Glob. Chang. Biol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2350","DOI":"10.1016\/j.rse.2011.04.035","article-title":"On intra-annual EVI variability in the dry season of tropical forest: A case study with MODIS and hyperspectral data","volume":"115","author":"Galvao","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.isprsjprs.2018.11.024","article-title":"Wavelet approach applied to EVI\/MODIS time series and meteorological data","volume":"147","author":"Moreira","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"63","DOI":"10.3390\/cli3010063","article-title":"Land Use\/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso","volume":"3","author":"Zoungrana","year":"2015","journal-title":"Climate"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_14","unstructured":"Didan, K., and Munoz, A.B. (2019). MODIS Vegetation Index User\u2019s Guide (MOD13 Series), Vegetation Index and Phenology Lab, The University of Arizona."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"13233","DOI":"10.3390\/rs71013233","article-title":"Spatial and Temporal Patterns of Global NDVI Trends: Correlations with Climate and Human Factors","volume":"7","author":"Liu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1007\/s11769-018-1002-2","article-title":"Detecting Global Vegetation Changes Using Mann-Kendal (MK) Trend Test for 1982\u20132015 Time Period","volume":"28","author":"Guo","year":"2018","journal-title":"Chin. Geogr. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Yang, Y., Wang, S., Bai, X., Tan, Q., Li, Q., Wu, L., Tian, S., Hu, Z., Li, C., and Deng, Y. (2019). Factors Affecting Long-Term Trends in Global NDVI. Forests, 10.","DOI":"10.3390\/f10050372"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"e2020EF001618","DOI":"10.1029\/2020EF001618","article-title":"Nearly Half of Global Vegetated Area Experienced Inconsistent Vegetation Growth in Terms of Greenness, Cover, and Productivity","volume":"8","author":"Ding","year":"2020","journal-title":"Earth\u2019s Future"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1111\/j.1365-2486.2011.02578.x","article-title":"Trend changes in global greening and browning: Contribution of short-term trends to longer-term change","volume":"18","author":"Verbesselt","year":"2012","journal-title":"Glob. Chang. Biol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"108629","DOI":"10.1016\/j.ecolind.2022.108629","article-title":"NDVI-based ecological dynamics of forest vegetation and its relationship to climate change in Romania during 1987\u20132018","volume":"136","author":"Nita","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1007\/s10661-022-10853-8","article-title":"Enhanced trends in spectral greening and climate anomalies across Europe","volume":"195","author":"Kempf","year":"2023","journal-title":"Environ. Monit. Assess."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e2156","DOI":"10.1002\/met.2156","article-title":"Influence of climatic conditions on Normalized Difference Vegetation Index variability in forest in Poland (2002\u20132021)","volume":"30","author":"Kulesza","year":"2023","journal-title":"Meteorol. Appl."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3275","DOI":"10.1111\/gcb.16121","article-title":"Satellite observations document trends consistent with a boreal forest biome shift","volume":"28","author":"Berner","year":"2022","journal-title":"Glob. Chang. Biol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e2020GL091496","DOI":"10.1029\/2020GL091496","article-title":"Where Are Global Vegetation Greening and Browning Trends Significant?","volume":"48","author":"Mahecha","year":"2021","journal-title":"Geophys. Res. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"104002","DOI":"10.1088\/1748-9326\/acf58e","article-title":"Changes in vegetation greenness and its response to precipitation seasonality in Central Asia from 1982 to 2022","volume":"18","author":"Su","year":"2023","journal-title":"Environ. Res. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1560","DOI":"10.1126\/science.1082750","article-title":"Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999","volume":"300","author":"Nemani","year":"2003","journal-title":"Science"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"L23402","DOI":"10.1029\/2006GL028205","article-title":"Effect of climate and CO2 changes on the greening of the Northern Hemisphere over the past two decades","volume":"33","author":"Piao","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3228","DOI":"10.1111\/j.1365-2486.2011.02419.x","article-title":"Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006","volume":"17","author":"Piao","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1126\/science.1192666","article-title":"Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009","volume":"329","author":"Zhao","year":"2010","journal-title":"Science"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Matas-Granados, L., Pizarro, M., Cayuela, L., Domingo, D., G\u00f3mez, D., and Garc\u00eda, M.B. (2022). Long-term monitoring of NDVI changes by remote sensing to assess the vulnerability of threatened plants. Biol. Conserv., 265.","DOI":"10.1016\/j.biocon.2021.109428"},{"key":"ref_31","unstructured":"Tomczyk, A.M., and Bednorz, E. (2022). Atlas klimatu Polski (1991\u20132020), Bogucki Wydawnictwo Naukowe."},{"key":"ref_32","unstructured":"Zaj\u0105czkowski, G., Jab\u0142o\u0144ski, M., Jab\u0142o\u0144ski, T., Sikora, K., Kowalska, A., Ma\u0142achowska, J., and Piwnicki, J. (2022). Raport o Stanie Las\u00f3w w Polsce 2021, Centrum Informacyjne Las\u00f3w Pa\u0144stwowych."},{"key":"ref_33","unstructured":"RDLP Lublin (2023, December 14). Lasy Regionu, Available online: https:\/\/www.lublin.lasy.gov.pl\/lasy-regionu."},{"key":"ref_34","unstructured":"Zi\u0119ba, M. (2023, December 14). Lasy Regionu, Available online: https:\/\/www.wroclaw.lasy.gov.pl\/lasy-regionu."},{"key":"ref_35","unstructured":"Ho\u015bci\u0142o, A., Rynkiewicz, A., Wasik, A., and Stosio, D. (2023). Klasyfikacja G\u0142\u00f3wnych Gatunk\u00f3w Drzew na Podstawie Danych Sentinel-2, Instytut Geodezji i Kartografii."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Ho\u015bci\u0142o, A., and Lewandowska, A. (2019). Mapping Forest Type and Tree Species on a Regional Scale Using Multi-Temporal Sentinel-2 Data. Remote Sens., 11.","DOI":"10.3390\/rs11080929"},{"key":"ref_37","unstructured":"Didan, K. (2022, December 04). MODIS\/Aqua Vegetation Indices 16-Day L3 Global 250m SIN Grid V061 [Data Set], Available online: https:\/\/lpdaac.usgs.gov\/products\/myd13q1v061\/."},{"key":"ref_38","unstructured":"Didan, K. (2022, December 04). MODIS\/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V061 [Data Set], Available online: https:\/\/lpdaac.usgs.gov\/products\/mod13q1v061\/."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1080\/01431168608948945","article-title":"Characteristics of maximum-value composite images from temporal AVHRR data","volume":"7","author":"Holben","year":"1986","journal-title":"Int. J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3582","DOI":"10.1002\/joc.4231","article-title":"A conceptual model for assessing rainfall and vegetation trends in sub-Saharan Africa from satellite data","volume":"35","author":"Balzter","year":"2015","journal-title":"Int. J. Climatol."},{"key":"ref_41","unstructured":"Mu\u00f1oz-Sabater, J. (2022, November 04). ERA5-Land Hourly Data from 1981 to Present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). 2019. 4.11.2022. Available online: https:\/\/cds.climate.copernicus.eu\/cdsapp#!\/dataset\/10.24381\/cds.e2161bac?tab=overview."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"4349","DOI":"10.5194\/essd-13-4349-2021","article-title":"ERA5-Land: A state-of-the-art global reanalysis dataset for land applications","volume":"13","author":"Dutra","year":"2021","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"111181","DOI":"10.1016\/j.rse.2019.04.034","article-title":"Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm","volume":"232","author":"Zhao","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"112247","DOI":"10.1016\/j.rse.2020.112247","article-title":"Evolution of NDVI secular trends and responses to climate change: A perspective from nonlinearity and nonstationarity characteristics","volume":"254","author":"Yang","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"151465","DOI":"10.1016\/j.scitotenv.2021.151465","article-title":"Amplified signals of soil moisture and evaporative stresses across Poland in the twenty-first century","volume":"812","author":"Somorowska","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.5194\/hess-21-1397-2017","article-title":"The European 2015 drought from a climatological perspective","volume":"21","author":"Ionita","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.baae.2020.04.003","article-title":"A first assessment of the impact of the extreme 2018 summer drought on Central European forests","volume":"45","author":"Schuldt","year":"2020","journal-title":"Basic Appl. Ecol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"e2020GL087285","DOI":"10.1029\/2020GL087285","article-title":"Quantifying the Central European Droughts in 2018 and 2019 With GRACE Follow-On","volume":"47","author":"Boergens","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Hari, V., Rakovec, O., Markonis, Y., Hanel, M., and Kumar, R. (2020). Increased future occurrences of the exceptional 2018\u20132019 Central European drought under global warming. Sci. Rep., 10.","DOI":"10.1038\/s41598-020-68872-9"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Buras, A., Meyer, B., and Rammig, A. (2023, January 24\u201328). Record reduction in European forest canopy greenness during the 2022 drought. Proceedings of the EGU General Assembly 2023, Vienna, Austria.","DOI":"10.5194\/egusphere-egu23-8927"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, Y., Zhu, X., Rammig, A., and Buras, A. (2023, January 24\u201328). Quantifying Tree-species Specific Responses to the Extreme 2022 Drought in Germany. Proceedings of the EGU General Assembly 2023, Vienna, Austria.","DOI":"10.5194\/egusphere-egu23-6144"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1014","DOI":"10.1016\/j.tplants.2023.03.024","article-title":"Vegetation browning: Global drivers, impacts, and feedbacks","volume":"28","author":"Liu","year":"2023","journal-title":"Trends Plant Sci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3072","DOI":"10.1111\/gcb.16657","article-title":"Compound droughts slow down the greening of the Earth","volume":"29","author":"Liu","year":"2023","journal-title":"Glob. Chang. Biol."},{"key":"ref_54","first-page":"e02791","article-title":"The global greening continues despite increased drought stress since 2000","volume":"49","author":"Chen","year":"2024","journal-title":"Glob. Ecol. Conserv."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2143","DOI":"10.1111\/gcb.14082","article-title":"Forest resilience to drought varies across biomes","volume":"24","author":"Gazol","year":"2018","journal-title":"Glob. Chang. Biol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"117848","DOI":"10.1016\/j.foreco.2019.117848","article-title":"Inter-specific tolerance to recurrent droughts of pine species revealed in saplings rather than adult trees","volume":"459","author":"Andivia","year":"2020","journal-title":"For. Ecol. Manag."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1111\/gcb.12038","article-title":"Driving factors of a vegetation shift from Scots pine to pubescent oak in dry Alpine forests","volume":"19","author":"Rigling","year":"2013","journal-title":"Glob. Chang. Biol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1093\/treephys\/tpt044","article-title":"Not all droughts are created equal: Translating meteorological drought into woody plant mortality","volume":"33","author":"Anderegg","year":"2013","journal-title":"Tree Physiol."},{"key":"ref_59","unstructured":"San-Miguel-Ayanz, J., de Rigo, D., Caudullo, G., Houston Durrant, T., and Mauri, A. (2016). Pinus sylvestris in Europe: Distribution, habitat, usage and threats. European Atlas of Forest Tree Species, Publication Office of the European Union."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"3381","DOI":"10.1080\/01431160152609227","article-title":"Spatial scale variations in vegetation indices and above-ground biomass estimates: Implications for MERIS","volume":"22","author":"Bakker","year":"2001","journal-title":"Int. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/15\/2844\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:29:08Z","timestamp":1760110148000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/15\/2844"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,2]]},"references-count":60,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["rs16152844"],"URL":"https:\/\/doi.org\/10.3390\/rs16152844","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,8,2]]}}}