1. Land surface phenology versus traditional observations
Márta Hunkár (1) ,
Ildikó Szenyán , Enikő Vincze, Zoltán Dunkel (2)
Tibor Szerdahelyi (3)
(1) Georgikon Faculty University of Pannonia;
(2) Hungarian Meteorological Service;
(3) Szent István University Institute of Botany and Ecophysiolgy;
EMS&ECAM Sept. Reading UK

2. Outline Aims Material Methods Results Conclusions
EMS&ECAM Sept. Reading UK
Outline
Aims
Material
Methods
Results
Conclusions

3. EMS&ECAM 2013 09-13 Sept. Reading UK
Aims of our study
Retrieve land surface phenological data from satellite observations
Comparing traditional phenological observation data with land surface phenological data

4. Traditional phenology
EMS&ECAM Sept. Reading UK
Introduction
Traditional phenology
Land surface phenology
Dates of phenological phases
Based on visual observation
Species-level
Local
Dates of critical values of vegetation indices
Based on satellite observation
Ecosystem level
Areal

5. EMS&ECAM 2013 09-13 Sept. Reading UK
Material
Sample area: Iklad (5 km x 5 km) covered by different agricultural and native plants
47,6802 o N;
19,4217 o E
47,6802 o N;
19,4836 o E
47,6385 o N;
19,4063 o E
47,6385 o N;
19,4681 o E

6. Material Satellite data:
where L is a soil adjustment factor, and C1 and C2 are coefficients used to correct aerosol scattering in the red band by the use of the blue band. The ρblue, ρred, and ρnir represent reflectance at the blue ( μm), red ( μm), and near-infrared (NIR) wavelengths ( μm), respectively. In general, G=2.5, C1=6.0, C2=7.5, and L=1.
where L is a soil adjustment factor, and C1 and C2 are coefficients used to correct aerosol scattering in the red band by the use of the blue band. The ρblue, ρred, and ρnir represent reflectance at the blue ( μm), red ( μm), and near-infrared (NIR) wavelengths ( μm), respectively. In general, G=2.5, C1=6.0, C2=7.5, and L=1.
where L is a soil adjustment factor, and C1 and C2 are coefficients used to correct aerosol scattering in the red band by the use of the blue band. The ρblue, ρred, and ρnir represent reflectance at the blue ( μm), red ( μm), and near-infrared (NIR) wavelengths ( μm), respectively. In general, G=2.5, C1=6.0, C2=7.5, and L=1.
from MODIS placed at Terra and Aqua satellites. Data are provided by NASA Land Processes Distributed Active Archive Center (NASA, LP DAAC, 2011). The MODIS Vegetation Index algorithm operates on a per-pixel basis and relies on multiple observations over a 16-day period to generate a composited Vegetation Index both from Terra and Aqua.
We used high resolution (250m x250m pixels) composite data with 8 day frequency for the last ten years ( ) on a sample area with the size of
EMS&ECAM Sept. Reading UK
Material
Satellite data:
Enhanced Vegetation Index (EVI) from MODIS placed at Terra and Aqua satellites (NASA, LP DAAC, 2011)
The MODIS Vegetation Index algorithm operates on a per-pixel basis and relies on multiple observations over a 16-day period to generate a composited Vegetation Index both from Terra and Aqua satellites overlapped with 8 days.
We got high resolution (250m x250m pixels) composite data with 8 day frequency for the last ten years ( ) .
The average EVI of that 400 pixels was used to characterise land surface vegetation.

7. EMS&ECAM 2013 09-13 Sept. Reading UK
Material
where L is a soil adjustment factor, and C1 and C2 are coefficients used to correct aerosol scattering in the red band by the use of the blue band. The ρblue, ρred, and ρnir represent reflectance at the blue ( μm), red ( μm), and near-infrared (NIR) wavelengths ( μm), respectively. In general, G=2.5, C1=6.0, C2=7.5, and L=1.

8. Material Traditional observations
EMS&ECAM Sept. Reading UK
Material
Traditional observations
Within the same sample area in 2011 and 2012
Plants:
locust (Robinia pseudacacia);
poplar (Populus spp);
sessile oak, (Quercus petraea);
winter wheat (Triticum aestivum);
maize (Zea Mays);
sunflower (Helianthus annuus);
native plants
agricultural plants

9. EMS&ECAM 2013 09-13 Sept. Reading UK
Material
The site of the traditional observations were identified by pixel-level (250m x 250m)
The EVI values of those pixels were analysed.

10. EMS&ECAM 2013 09-13 Sept. Reading UK
Methods
Spatial average of high resolution EVI data is used to characterize of the vegetation dynamics.
Temporal variation in EVI data are modelled using piecewise sigmoid models. Each growth cycle is modelled using two sigmoid functions: one for the growth phase, one for the senescence phase.

11. EMS&ECAM 2013 09-13 Sept. Reading UK
To identify the land surface phenological transition dates, the rate of change in the curvature of the fitted logistic models is used for each year.
Specifically, transition dates correspond to the times at which the rate of change in curvature in the EVI data exhibits local minima or maximums.

12. Time course of the spatial average EVI values for the sample area
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Time course of the spatial average EVI values for the sample area

13. rate of change in the curvature of the fitted logistic models
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rate of change in the curvature of the fitted logistic models
Increasing period of EVI

14. EMS&ECAM 2013 09-13 Sept. Reading UK
Causes of shifting?

15. The corresponding phenological transition dates are defined as
EMS&ECAM Sept. Reading UK
The corresponding phenological transition dates are defined as
the onset of greenness increase (F1),
the onset of greenness maximum (F2),
the onset of greenness decrease (F3), and
the onset of greenness minimum (F4).

16. Trends of the length of the growing season (F4-F1, F3-F2)
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Trends of the length of the growing season (F4-F1, F3-F2)

17. Traditional observations of trees
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Traditional observations of trees
BBCH 10
Sprouting of leaves 19
Beginning of the unfolding of leaves 60
Beginning of flowering 65
Full flowering 69
End of flowering 93
Fall of leaves 97
End of falling leaves

18. Traditional observations of trees
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Traditional observations of trees

19. EVI values on pixel level
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EVI values on pixel level

20. EVI values on pixel level
EMS&ECAM Sept. Reading UK
EVI values on pixel level

21. Traditional observation of agricultural plants
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Traditional observation of agricultural plants
BBCH wheat
BBCH maize
BBCH sunflower 00
sowing 09
Emergence 21
Beginning of tillering 13
3 leaves unfolded 14
4 leaves unfolded 31
First node at least 17
7 leaves unfolded 53
Inflorescence 55
Middle of heading 59
59 End of tassel emergence 65
Full flowering 67
Flowering declining 85
Soft dough
85 dough stage 69
End of flowering 92
Over-ripe 89
Fully ripe 99
Harvest
99 Harvest

22. Traditional observation of agricultural plants
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Traditional observation of agricultural plants

23. EVI values on pixel level
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EVI values on pixel level
Heading or flowering
Harvest

24. EVI values on pixel level
EMS&ECAM Sept. Reading UK
EVI values on pixel level

25. EMS&ECAM 2013 09-13 Sept. Reading UK
Conclusions
Landscape phenology based on EVI is suitable to evaluate the vegetation dynamic of the season.
Traditional phenology is more sophisticated but it is difficult to integrate.
EVI values for native plants (trees) can be modeled by logistic curves.
Flowering time relating to EVI is plant specific
EVI values for agricultural plants show different shape (not logistic).
The maximum EVI is around flowering and then the decreasing phase has rather convex curvature.

26. Thank you for your attention!
EMS&ECAM Sept. Reading UK
Thank you for your attention!