Characterising the Land Surface Phenology of Europe Using Decadal MERIS Data
Abstract
:1. Introduction
Study | Year of Publication | Study Area | Type | Resolution | Period | Composite Period | Vegetation Index |
---|---|---|---|---|---|---|---|
Myneni, et al. [29] | 1997 | Global | GIMMS AVHRR | 8 km | 1981–1991 | 10 days | NDVI |
Tucker, et al. [30] | 2001 | Northern Hemisphere | AVHRR | 8 km | 1982–1999 | 7 days | NDVI |
Zhou, et al. [31] | 2001 | Eurasia | GIMMS AVHRR | 9 km | 1981–1999 | 15 days | NDVI |
Stockli and Vidale [32] | 2004 | Europe | PAL AVHRR | 8 Km | 1982–2001 | 10 days | NDVI |
Tateishi and Ebata [33] | 2004 | Global | PAL AVHRR | 8 Km | 1982–2000 | 10 days | NDVI |
Beck, Atzberger, Høgda, Johansen and Skidmore [22] | 2006 | Finland Norway and Sweden | MODIS | 250 m | 2000–2004 | 16 days | NDVI |
Karlsen, et al. [34] | 2007 | Fennoscandia | GIMMS AVHRR | 8 Km | 1982–2002 | 15 days | NDVI |
Delbart, Picard, Le Toans, Kergoat, Quegan, Woodward, Dye and Fedotova [24] | 2008 | Boreal Eurasia | SPOT VGT | 1 Km | 1998–2005 | 10 days | NDVI |
Maignan, et al. [35] | 2008 | Europe | PAL AVHRR | 8 Km | 1982–1999 | 1 day | DVI |
Julien and Sobrino [36] | 2009 | Global | GIMMS AVHRR | 8 Km | 1981–2003 | 10 days | NDVI |
De Beurs and Henebry [37] | 2010 | Eurasia | PAL AVHRR | 8 km | 1981–1999 | 10 days | NDVI |
Hogda, et al. [38] | 2011 | Fennoscandia | GIMMS AVHRR | 8 Km | 1982–2011 | 15 days | NDVI |
Jeong, et al. [39] | 2011 | Northern Hemisphere | GIMMS AVHRR | 8 km | 1982–2008 | 15 days | NDVI |
Ivits, et al. [40] | 2012 | Europe | GIMMS AVHRR | 8 Km | 1982–2006 | 15 days | NDVI |
O’Connor, Dwyer, Cawkwell and Eklundh [23] | 2012 | Ireland | MERIS | 1.2 Km | 2003–2009 | 10 days | MGVI |
Atzberger, et al. [41] | 2013 | Europe | GIMMS AVHRR MODIS | 8 Km | 2003–2011 | 15 days | NDVI |
Hamunyela, Verbesselt, Roerink and Herold [25] | 2013 | Western Europe | MODIS | 250 m | 2001–2011 | 16 days | NDVI |
Han, Luo and Li [26] | 2013 | Europe | SPOT VGT | 1 Km | 1999–2005 | 10 days | NDVI |
Klisch, Atzberger and Luminari [27] | 2014 | Europe | MODIS | 250 m | 2003–2011 | 16 days | NDVI |
Zhang, et al. [42] | 2014 | Global | AVHRR and MODIS | 5 Km | 1982–2010 | 3 days | EVI |
2. Data and Methods
2.1. Dataset
2.2. Phenology Estimates
3. Results
3.1. Spatial Variation in Phenological Metrics
3.2. Characterisation of the Phenology of the Main Biogeographical Regions in Europe
4. Discussion
Broadleaved Deciduous Forest | ||||||
Alpine | Anatolian | Black Sea | Continental | Mediterranean | Panonian | |
Anatolian | 0.067 | -- | ||||
Black Sea | 0 * | 0.1 | -- | |||
Continental | 0.808 | 0.066 | 0 * | -- | ||
Mediterranean | 0 * | 0.027 * | 0 * | 0 * | -- | |
Panonian | 0 * | 0.105 | 0.699 | 0 * | 0 * | -- |
Steppic | 0.467 | 0.062 | 0 * | 0.507 | 0 * | 0 * |
Needleleaved Evergreen Forest | ||||||
Alpine | Anatolian | Black Sea | Continental | Mediterranean | ||
Anatolian | 0 * | -- | ||||
Black Sea | 0 * | 0.03 * | -- | |||
Continental | 0 * | 0 * | 0* | -- | ||
Mediterranean | 0 * | 0.691 | 0.001 * | 0 * | -- | |
Steppic | 0 * | 0.03 * | 0.816 | 0.021 * | 0.002 * | |
Shrublands | ||||||
Alpine | Anatolian | Black Sea | Continental | |||
Anatolian | 0 * | -- | ||||
Black Sea | 0 * | 0 * | -- | |||
Continental | 0 * | 0 * | 0 * | -- | ||
Mediterranean | 0 * | 0 * | 0 * | 0 * | ||
Grasslands | ||||||
Continental | ||||||
Atlantic | 0.826 * |
Broadleaved Deciduous Forest | ||||||
Alpine | Anatolian | Black Sea | Continental | Mediterranean | Panonian | |
Anatolian | 0.271 | -- | ||||
Black Sea | 0 * | 0.137 | -- | |||
Continental | 0.324 | 0.25 | 0 * | -- | ||
Mediterranean | 0 * | 0.999 | 0 * | 0 * | -- | |
Panonian | 0.168 | 0.364 | 0 * | 0.086 | 0 * | -- |
Steppic | 0.021 * | 0.366 | 0 * | 0.001 * | 0 * | 0.949 |
Needleleaved Evergreen Forest | ||||||
Alpine | Anatolian | Black Sea | Continental | Mediterranean | ||
Anatolian | 0.836 | -- | ||||
Black Sea | 0.154 | 0.202 | -- | |||
Continental | 0.048 * | 0.328 | 0 * | -- | ||
Mediterranean | 0 * | 0 * | 0 * | 0 * | -- | |
Steppic | 0 * | 0.018 * | 0 * | 0.006 * | 0 * | |
Shrublands | ||||||
Alpine | Anatolian | Black Sea | Continental | |||
Alpine | -- | |||||
Anatolian | 0 * | -- | ||||
Black Sea | 0 * | 0 * | -- | |||
Continental | 0 * | 0 * | 0.001 * | -- | ||
Mediterranean | 0 * | 0 * | 0.38 | 0 * | ||
Grasslands | ||||||
Continental | ||||||
Atlantic | 0 * |
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Parmesan, C.; Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 2003, 421, 37–42. [Google Scholar] [CrossRef] [PubMed]
- Menzel, A.; Sparks, T.H.; Estrella, N.; Koch, E.; Aaasa, A.; Ahas, R.; Alm-Kübler, K.; Bissolli, P.; Braslavská, O.; Briede, A.; et al. European phenological response to climate change matches the warming pattern. Glob. Change Biol. 2006, 12, 1969–1976. [Google Scholar] [CrossRef]
- Wolkovich, E.M.; Cook, B.I.; Allen, J.M.; Crimmins, T.M.; Betancourt, J.L.; Travers, S.E.; Pau, S.; Regetz, J.; Davies, T.J.; Kraft, N.J.B.; et al. Warming experiments underpredict plant phenological responses to climate change. Nature 2012, 485, 494–497. [Google Scholar] [CrossRef] [PubMed]
- Sobrino, J.A.; Julien, Y.; Morales, L. Changes in vegetation spring dates in the second half of the twentieth century. Int. J. Remote Sens. 2011, 32, 5247–5265. [Google Scholar] [CrossRef]
- Richardson, A.D.; Keenan, T.F.; Migliavacca, M.; Ryu, Y.; Sonnentag, O.; Toomey, M. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agric. For. Meteorol. 2013, 169, 156–173. [Google Scholar] [CrossRef]
- Menzel, A. Phenology: Its importance to the global change community. Clim. Change 2002, 54, 379–385. [Google Scholar] [CrossRef]
- Betts, R.A. Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature 2000, 408, 187–190. [Google Scholar] [CrossRef] [PubMed]
- Klosterman, S.T.; Hufkens, K.; Gray, J.M.; Melaas, E.; Sonnentag, O.; Lavine, I.; Mitchell, L.; Norman, R.; Friedl, M.A.; Richardson, A.D. Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using Phenocam imagery. Biogeosciences Discuss. 2014, 11, 2305–2342. [Google Scholar] [CrossRef]
- Kirbyshire, A.L.; Bigg, G.R. Is the onset of the English summer advancing? Clim. Change 2010, 100, 419–431. [Google Scholar] [CrossRef]
- Fitter, A.H.; Fitter, R.S.R. Rapid changes in flowering time in British plants. Science 2002, 296, 1689–1691. [Google Scholar] [CrossRef] [PubMed]
- Menzel, A. Trends in phenological phases in Europe between 1951 and 1996. Int. J. Biometeorol. 2000, 44, 76–81. [Google Scholar] [CrossRef] [PubMed]
- Roetzer, T.; Wittenzeller, M.; Haeckel, H.; Nekovar, J. Phenology in Central Europe differences and trends of spring phenophases in urban and rural areas. Int. J. Biometeorol. 2000, 44, 60–66. [Google Scholar] [CrossRef] [PubMed]
- Defila, C.; Clot, B. Phytophenological trends in Switzerland. Int. J. Biometeorol. 2001, 45, 203–207. [Google Scholar] [CrossRef] [PubMed]
- Ahas, R.; Aasa, R.; Menzel, A.; Fedotova, V.G.; Scheifinger, H. Changes in European spring phenology. Int. J. Climatol. 2002, 22, 1727–1738. [Google Scholar] [CrossRef]
- Studer, S.; Stöckli, R.; Appenzeller, C.; Vidale, P.L. A comparative study of satellite and ground-based phenology. Int. J. Biometeorol. 2007, 51, 405–414. [Google Scholar] [CrossRef] [PubMed]
- White, M.A.; de Beurs, K.M.; Didan, K.; Inouye, D.W.; Richardson, A.D.; Jensen, O.P.; O’Keefe, J.; Zhang, G.; Nemani, R.R.; van Leeuwen, W.J.D.; et al. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006. Glob. Change Biol. 2009, 15, 2335–2359. [Google Scholar] [CrossRef]
- Jeganathan, C.; Dash, J.; Atkinson, P. Characterising the spatial pattern of phenology for the tropical vegetation of India using multi-temporal MERIS chlorophyll data. Landsc. Ecol. 2010, 25, 1125–1141. [Google Scholar] [CrossRef]
- Dash, J.; Jeganathan, C.; Atkinson, P.M. The use of MERIS terrestrial chlorophyll index to study spatio-temporal variation in vegetation phenology over India. Remote Sens. Environ. 2010, 114, 1388–1402. [Google Scholar] [CrossRef]
- Reed, B.C.; Brown, J.F.; VanderZee, D.; Loveland, T.R.; Merchant, J.W.; Ohlen, D.O. Measuring phenological variability from satellite imagery. J. Veg. Sci. 1994, 5, 703–714. [Google Scholar] [CrossRef]
- Maignan, F.; Bréon, F.M.; Vermote, E.; Ciais, P.; Viovy, N. Mild winter and spring 2007 over western Europe led to a widespread early vegetation onset. Geophys. Res. Lett. 2008, 35. [Google Scholar] [CrossRef]
- Dash, J.; Curran, P.J. Evaluation of the MERIS terrestrial chlorophyll index (MTCI). Adv. Space Res. 2007, 39, 100–104. [Google Scholar] [CrossRef]
- Beck, P.S.A.; Atzberger, C.; Høgda, K.A.; Johansen, B.; Skidmore, A.K. Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI. Remote Sens. Environ. 2006, 100, 321–334. [Google Scholar] [CrossRef]
- O’Connor, B.; Dwyer, E.; Cawkwell, F.; Eklundh, L. Spatio-temporal patterns in vegetation start of season across the island of Ireland using the MERIS global vegetation index. ISPRS J. Photogramm. Remote Sens. 2012, 68, 79–94. [Google Scholar] [CrossRef]
- Delbart, N.; Picard, G.; Le Toans, T.; Kergoat, L.; Quegan, S.; Woodward, I.; Dye, D.; Fedotova, V. Spring phenology in Boreal Eurasia over a nearly century time scale. Glob. Change Biol. 2008, 14, 603–614. [Google Scholar] [CrossRef]
- Hamunyela, E.; Verbesselt, J.; Roerink, G.; Herold, M. Trends in spring phenology of western European deciduous forests. Remote Sens. 2013, 5, 6159–6179. [Google Scholar] [CrossRef]
- Han, Q.; Luo, G.; Li, C. Remote sensing-based quantification of spatial variation in canopy phenology of four dominant tree species in Europe. J. Appl. Remote Sens. 2013, 7. [Google Scholar] [CrossRef]
- Klisch, A.; Atzberger, C.; Luminari, L. Satellite-based drought monitoring in Kenya in an operational setting. ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2015, 2015, 433–439. [Google Scholar] [CrossRef]
- Rodriguez-Galiano, V.; Dash, J.; Atkinson, P.M. Inter-comparison of satellite sensor land surface phenology and ground phenology in Europe. Geophys. Res. Lett. 2015, 42, 2253–2260. [Google Scholar] [CrossRef]
- Myneni, R.B.; Keeling, C.D.; Tucker, C.J.; Asrar, G.; Nemani, R.R. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 1997, 386, 698–702. [Google Scholar] [CrossRef]
- Tucker, C.J.; Slayback, D.A.; Pinzon, J.E.; Los, S.O.; Myneni, R.B.; Taylor, M.G. Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999. Int. J. Biometeorol. 2001, 45, 184–190. [Google Scholar] [CrossRef] [PubMed]
- Zhou, L.M.; Tucker, C.J.; Kaufmann, R.K.; Slayback, D.; Shabanov, N.V.; Myneni, R.B. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. J. Geophys. Res. Atmos. 2001, 106, 20069–20083. [Google Scholar] [CrossRef]
- Stockli, R.; Vidale, P.L. European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset. Int. J. Remote Sens. 2004, 25, 3303–3330. [Google Scholar] [CrossRef]
- Tateishi, R.; Ebata, M. Analysis of phenological change patterns using 1982–2000 advanced very high resolution radiometer (AVHRR) data. Int. J. Remote Sens. 2004, 25, 2287–2300. [Google Scholar] [CrossRef]
- Karlsen, S.R.; Solheim, I.; Beck, P.S.A.; Hogda, K.A.; Wielgolaski, F.E.; Tommervik, H. Variability of the start of the growing season in Fennoscandia, 1982–2002. Int. J. Biometeorol. 2007, 51, 513–524. [Google Scholar] [CrossRef] [PubMed]
- Maignan, F.; Bréon, F.M.; Bacour, C.; Demarty, J.; Poirson, A. Interannual vegetation phenology estimates from global AVHRR measurements. Comparison with in situ data and applications. Remote Sens. Environ. 2008, 112, 496–505. [Google Scholar] [CrossRef]
- Julien, Y.; Sobrino, J.A. Global land surface phenology trends from GIMMS database. Int. J. Remote Sens. 2009, 30, 3495–3513. [Google Scholar] [CrossRef]
- De Beurs, K.M.; Henebry, G.M. A land surface phenology assessment of the Northern Polar regions using MODIS reflectance time series. Can. J. Remote Sens. 2010, 36, S87–S110. [Google Scholar] [CrossRef]
- Hogda, K.A.; Tommervik, H.; Karlsen, S.R. Trends in the start of the growing season in Fennoscandia 1982–2011. Remote Sens. 2013, 5, 4304–4318. [Google Scholar] [CrossRef]
- Jeong, S.-J.; Ho, C.-H.; Gim, H.-J.; Brown, M.E. Phenology shifts at start vs. End of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008. Glob. Change Biol. 2011, 17, 2385–2399. [Google Scholar] [CrossRef]
- Ivits, E.; Cherlet, M.; Tóth, G.; Sommer, S.; Mehl, W.; Vogt, J.; Micale, F. Combining satellite derived phenology with climate data for climate change impact assessment. Glob. Planet. Change 2012, 88–89, 85–97. [Google Scholar] [CrossRef]
- Atzberger, C.; Klisch, A.; Mattiuzzi, M.; Vuolo, F. Phenological metrics derived over the European continent from NDVI3G data and MODIS time series. Remote Sens. 2013, 6, 257–284. [Google Scholar] [CrossRef]
- Zhang, X.; Tan, B.; Yu, Y. Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982–2010. Int. J. Biometeorol. 2014, 58, 1–18. [Google Scholar] [CrossRef]
- Defourny, P.; Vancutsem, C.; Bicheron, P.; Brockmann, C.; Nino, F.; Schouten, L.; Leroy, M. Globcover: A 300 m Global Land Cover Product for 2005 Using Envisat MERIS Time Series. Available online: http://dup.esrin.esa.int/files/131-176-131-25_2007510152728.pdf (accessed on 21 July 2015).
- Bicheron, P.; Amberg, V.; Bourg, L.; Petit, D.; Huc, M.; Miras, B.; Brockmann, C.; Hagolle, O.; Delwart, S.; Ranera, F.; et al. Geolocation assessment of MERIS globcover orthorectified products. IEEE Trans. Geosci. Remote Sens. 2011, 49, 2972–2982. [Google Scholar] [CrossRef] [Green Version]
- Verhoef, W.; Menenti, M.; Azzali, S. Cover a colour composite of NOAA-AVHRR-NDVI based on time series analysis (1981–1992). Int. J. Remote Sens. 1996, 17, 231–235. [Google Scholar] [CrossRef]
- Roerink, G.J.; Menenti, M.; Verhoef, W. Reconstructing cloudfree NDVI composites using fourier analysis of time series. Int. J. Remote Sens. 2000, 21, 1911–1917. [Google Scholar] [CrossRef]
- Atkinson, P.M.; Jeganathan, C.; Dash, J.; Atzberger, C. Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology. Remote Sens. Environ. 2012, 123, 400–417. [Google Scholar] [CrossRef]
- Schwartz, M.D.; Ahas, R.; Aasa, A. Onset of spring starting earlier across the Northern Hemisphere. Glob. Change Biol. 2006, 12, 343–351. [Google Scholar] [CrossRef]
- Delbart, N.; Picard, G.; Le Toan, T.; Kergoat, L.; Quegan, S.; Woodward, I.; Dye, D.; Fedotova, V. Spring phenology in Boreal Eurasia over a nearly century time scale. Glob. Change Biol. 2008, 14, 603–614. [Google Scholar] [CrossRef]
- Ryu, Y.; Lee, G.; Jeon, S.; Song, Y.; Kimm, H. Monitoring multi-layer canopy spring phenology of temperate deciduous and evergreen forests using low-cost spectral sensors. Remote Sens. Environ. 2014, 149, 227–238. [Google Scholar] [CrossRef]
- Karnieli, A. Natural vegetation phenology assessment by ground spectral measurements in two semi-arid environments. Int. J. Biometeorol. 2003, 47, 179–187. [Google Scholar] [CrossRef] [PubMed]
- Atzberger, C.; Eilers, P.H.C. Evaluating the effectiveness of smoothing algorithms in the absence of ground reference measurements. Int. J. Remote Sens. 2011, 32, 3689–3709. [Google Scholar] [CrossRef]
- Seixas, J.; Carvalhais, N.; Nunes, C.; Benali, A. Comparative analysis of MODIS-FAPAR and MERIS–MGVI datasets: Potential impacts on ecosystem modeling. Remote Sens. Environ. 2009, 113, 2547–2559. [Google Scholar] [CrossRef]
- Chmielewski, F.-M.; Rötzer, T. Response of tree phenology to climate change across Europe. Agric. For. Meteorol. 2001, 108, 101–112. [Google Scholar] [CrossRef]
© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Rodriguez-Galiano, V.F.; Dash, J.; Atkinson, P.M. Characterising the Land Surface Phenology of Europe Using Decadal MERIS Data. Remote Sens. 2015, 7, 9390-9409. https://doi.org/10.3390/rs70709390
Rodriguez-Galiano VF, Dash J, Atkinson PM. Characterising the Land Surface Phenology of Europe Using Decadal MERIS Data. Remote Sensing. 2015; 7(7):9390-9409. https://doi.org/10.3390/rs70709390
Chicago/Turabian StyleRodriguez-Galiano, Victor F., Jadunandan Dash, and Peter M. Atkinson. 2015. "Characterising the Land Surface Phenology of Europe Using Decadal MERIS Data" Remote Sensing 7, no. 7: 9390-9409. https://doi.org/10.3390/rs70709390