The present paper introduces a satellite-based approach to the detection of phenology events in beech forests across Slovakia (the Western Carpathians) using the MOD/MYD09 products. Normalized vegetation index (NDVI) was used for determining the onset of the phenophases in spring and autumn. Double logistic sigmoid function was applied in order to fit the NDVI profile during the year. The satellite-derived phenological metrics was based on calculating the extreme values of the sigmoid function and its derivatives. Between 2000 and 2015, a time-series analysis using the linear regressions models revealed that the onset of leaf unfolding shifted at a rate of 0.8 day per decade, the onset of leaf fall was delayed at a rate of 1.9 day per decade, and the growing season (GS) extended at a rate of 1.1 day per decade. However, at a regional level, the trends were not found to be statistically significant in either case. Leaf unfolding/fall was significantly non-linearly delayed/advanced with the increase of altitude (p<0.01). GS duration varied extensively within the region. Theil-Sen estimation of GS trend revealed the median shift of 1.8 days, the range of shift being from -7.0 to +12.1 days at the 5-95 % quantile for 2000-2015. A significant inverse correlation between GS shift and GS length (p<0.01) was observed. The GS shift was positive in the sites with shorter GS and negative in the sites with longer GS.
Keywords
, , , ,
Citation
Bucha T, Koren M (2017). Phenology of the beech forests in the Western Carpathians from MODIS for 2000-2015. iForest 10: 537-546. - doi: 10.3832/ifor2062-010
Academic Editor
Matteo Garbarino
Paper history
Received: Mar 15, 2016
Accepted: Feb 22, 2017
First online: May 05, 2017
Publication Date: Jun 30, 2017
Publication Time: 2.40 months
© SISEF - The Italian Society of Silviculture and Forest Ecology 2017
Open Access
This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Breakdown by View Type
(Waiting for server response...)
Article Usage
Total Article Views: 20236
(from publication date up to now)
Breakdown by View Type
HTML Page Views: 14439
Abstract Page Views: 842
PDF Downloads: 3509
Citation/Reference Downloads: 79
XML Downloads: 1367
Web Metrics
Days since publication: 2744
Overall contacts: 20236
Avg. contacts per week: 51.62
Article Citations
Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Nov 2020)
Total number of cites (since 2017): 7
Average cites per year: 1.75
Publication Metrics
by Dimensions ©
Articles citing this article
List of the papers citing this article based on CrossRef Cited-by.
(1)
Beck PSA, Atzberger TC, Hogda KA, Johansen B, Skidmore AK (2006)Improved monitoring of vegetation dynamics at very high latitudes: a new method using MODIS NDVI. Remote Sensing of Environment 100: 321-334.
CrossRef |
Gscholar
(2)
Beck PSA, Jönsoon P, Hogda KA, Karlsen SR, Eklund L, Skidmore AK (2007)A ground-validated NDVI dataset for monitoring vegetation dynamics and mapping phenology in Fennoscandia and the Kola Peninsula. International Journal of Remote Sensing 28 (19): 4311-4330.
CrossRef |
Gscholar
(3)
Brandysová V, Bucha T (2012)Effect of understory vegetation and undergrowth on course of phenological curve of beech forests derived from MODIS. Lesnícky časopis - Forestry Journal 58 (4): 231-242.
Gscholar
(4)
Bucha T (1999)Classification of tree species composition in Slovakia from satellite images as a part of monitoring forest ecosystems biodiversity. LVU Zvolen, Acta Instituti Forestalis Zvolen, Tomus 9, pp. 65-84.
Gscholar
(5)
Cufar K, De Luis M, Saz MA, Crepinsek Z, Kajfez-Bogataj L (2012)Temporal shifts in leaf phenology of beech (
Fagus sylvatica) depend on elevation. Trees 26 (4): 1091-1100.
CrossRef |
Gscholar
(6)
Delpierre N, Dufre E, Soudani K, Ulrich E, Cecchini S, Boé J, Francois C (2009)Modelling interannual and spatial variability of leaf senescence for three deciduous tree species in France. Agricultural and Forest Meteorology 149: 938-948.
CrossRef |
Gscholar
(7)
Fisher JI, Mustard JF (2007)Cross-scalar satellite phenology from ground, Landsat and MODIS data. Remote Sensing of Environment 109: 261-273.
CrossRef |
Gscholar
(8)
Eklundh L, Jönsson P (2015)TIMESAT: a software package for time-series processing and assessment of vegetation dynamics. In: “Remote Sensing Time Series 22” (Kuenzer C, Dech S, Wagner W eds). Springer International Publishing, Switzerland, pp. 141-158.
CrossRef |
Gscholar
(9)
Franch B, Vermote EF, Sobrino JA, Fédèle E (2013)Analysis of directional effect on atmospheric correction. Remote Sensing of Environment 128: 276-288.
CrossRef |
Gscholar
(10)
Fu YH, Piao S, Op de Beeck MO, Cong N, Zhao H, Zhang Y, Menzel A, Janssens IA (2014)Recent spring phenology shifts in western Central Europe based on multiscale observations. Global Ecology and Biogeography 23 (11): 1255-1263.
CrossRef |
Gscholar
(11)
Ganguly S, Friedl MA, Tan B, Zhang X, Verma M (2010)Land surface phenology from MODIS: characterization of the collection 5 global land cover dynamics product. Remote Sensing of Environment 114: 1805-1816.
CrossRef |
Gscholar
(12)
Garonna I, De Jong R, De Wit AJW, Mücher CA, Schmid B, Schaepman ME (2014)Strong contribution of autumn phenology to changes in satellite-derived growing season length estimates across Europe (1982-2011). Global Change Biology 20 (11): 3457-3470.
CrossRef |
Gscholar
(13)
Hamunyela E, Verbesselt J, Roerink G, Herold M (2013)Trends in spring phenology of western European deciduous forests. Remote Sensing 5: 6159-6179.
CrossRef |
Gscholar
(14)
Heumann BW, Seaquist JW, Eklundh L, Jönsson P (2007)AVHRR derived phenological change in the Sahel and Soudan, Africa, 1982-2005. Remote Sensing of Environment 108: 385-392.
CrossRef |
Gscholar
(15)
Hmimina G, Dufrêne E, Pontailler JY, Delpierre N, Aubinet M, Caquet B, De Grandcourt A, Burban B, Flechard C, Granier A, Gross P, Heinesch B, Longdoz B, Moureaux C, Ourcival JM, Rambal S, Saint André L, Soudani K (2013)Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: an investigation using ground-based NDVI measurements. Remote Sensing of Environment 132: 145-158.
CrossRef |
Gscholar
(16)
Ju J, Roy DP, Shuai Y, Schaaf C (2011)Development of an approach for generation of temporally complete daily nadir MODIS reflectance time series. Remote Sensing of Environment 114: 1-20.
CrossRef |
Gscholar
(17)
Justice CO, Townshend JRG, Vermote EF, Masuoka E, Wolfe RE, Saleous N, Roy DP, Morisette JT (2002)An overview of MODIS land data processing and product status. Remote Sensing of Environment 83: 3-15.
CrossRef |
Gscholar
(18)
Kang S, Running SW, Lim J-H, Zhao M, Park Ch-R, Loehman R (2003)A regional phenology model for detecting the onset of greenness in temperate mixed forests, Korea: an application of MODIS leaf area index. Remote Sensing of Environment 86 (2): 232-242.
CrossRef |
Gscholar
(19)
Karmeshu N (2012)Trend detection in annual temperature and precipitation using the Mann Kendall test - a case study to assess climate change in selected states in the Northeastern United States. Master’s thesis, University of Pennsylvania, ScholarlyCommons, Philadelphia, PA, USA, pp. 27.
Gscholar
(20)
Kristof D, Pataki R (2009)Novel vector-based pre-processing of MODIS data. In: “Ebook Remote Sensing for a Changing Europe” (Maktav D ed). IOS Press, Amsterdam, Netherlands, pp. 483-490.
Gscholar
(21)
Liu L, Liang L, Schwartz MD, Donnelly A, Wang Z, Schaaf CB, Liu L (2015)Evaluating the potential of MODIS satellite data to track temporal dynamics of autumn phenology in a temperate mixed forest. Remote Sensing of Environment 160 (5): 156-165.
CrossRef |
Gscholar
(22)
Menzel A (2000)Trends in phenological phases in Europe between 1951 and 1996. International Journal of Biometeorology 44: 76-81.
CrossRef |
Gscholar
(23)
Menzel A, Estrella N, Fabian P (2001)Spatial and temporal variability of the phenological seasons in Germany from 1951 to 1996. Global Change Biology 7 (6): 657-666.
CrossRef |
Gscholar
(24)
Pavlendová H, Snopková Z, Priwitzer T, Bucha T (2014)Using of long-term phenological observations of SHMI and NFC for validation of regional phenology model for European beech. In: Proceedings of the International Conference “Mendel and Bioclimatology” (Roznovsky J, Litschmann T eds). Masaryk University (Brno, Czech Republic) 3-5 Sept 2014, pp. 294-311.
Online |
Gscholar
(25)
Piao S, Fang J, Zhou L, Ciais P, Zhu B (2006)Variations in satellite-derived phenology in China’s temperate vegetations. Global Change Biology 12: 672-685.
CrossRef |
Gscholar
(26)
Schaber J, Badeck FW (2005)Plant phenology in Germany over the 20th century. Regional Enviromental Change 5 (1): 37-46.
CrossRef |
Gscholar
(27)
Schieber B, Janík R, Snopková Z (2013)Phenology of common beech (
Fagus sylvatica L.) along the altitudinal gradient in the Slovak Republic (Inner Western Carpathians). Journal of Forest Science 59 (4): 176-184.
Online |
Gscholar
(28)
Soudami K, Maire GM, Dufrene E, Francois Ch Delpierre N, Ulrich E, Cecchini S (2008)An evaluation of the onset of green-up in temperate deciduous broadleaf forests derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Remote Sensing of Environment 122 (5): 2643-2655.
CrossRef |
Gscholar
(29)
Stöckli R, Vidale PL (2004)European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset. International Journal of Remote Sensing 25 (17): 3303-3330.
CrossRef |
Gscholar
(30)
Studer S, Appenzeller C, Defila C (2005)Inter-annual variability and decadal trends in alpine spring phenology: a multivariate analysis approach. Climate Change 7 (3): 395-414.
CrossRef |
Gscholar
(31)
Townshend JRG, Huang SN, Kalluri V, Defries RS, Liang S (2000)Beware of the per-pixel characterization of land cover. International Journal of Remote Sensing 21 (4): 839-843.
CrossRef |
Gscholar
(32)
Vitasse Y, Delzon S, Dufrene E, Pontailler JY, Louvet JM, Kremer A, Michalet R (2009)Leaf phenology sensitivity to temperature in European trees: do within-species populations exhibit similar responses? Agricultural and Forest Meteorology 149 (5): 735-744.
CrossRef |
Gscholar
(33)
Vitasse Y, Basler D (2013)What role for photoperiod in the bud burst phenology of European beech. European Journal of Forest Research 132 (1): 1-8.
CrossRef |
Gscholar
(34)
Wolfe ER, Nishihama M, Fleig AJ, Kuyper JA, Roy DA, Storey JC, Pat FS (2002)Achieving sub-pixel geolocation accuracy in support of MODIS land science. Remote Sensing of Environment 83: 31-49.
CrossRef |
Gscholar
(35)
Wu C, Gonsamo A, Gough C, Chen JM, Xu S (2014)Modelling growing season phenology in North American forests using seasonal mean vegetation indices from MODIS. Remote Sensing of Environment 147: 79-88.
CrossRef |
Gscholar
(36)
Zhang X, Friedl HA, Schaaf BS, Strahler AH, Hodges JCF, Gao F, Reed BC, Huete A (2003)Monitoring vegetation phenology using the MODIS. Remote Sensing of Environment 84: 471-475.
CrossRef |
Gscholar
(37)
Zhou L, Tucker CJ, Kaufmann R, Slayback D, Shabanov NV, Myneni RB (2001)Variations in northern vegetation activity inferred from the satellite data of the vegetation index from 1981 to 1999. Journal of Geophysical Research 106 (D17): 20069-20083.
CrossRef |
Gscholar