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; hunkar@georgikon.hu (2) Hungarian Meteorological Service; szenyan.i@met.hu; vincze.e@met.hu; dunkel.z@met.hu (3) Szent István University Institute of Botany and Ecophysiolgy; Szerdahelyi.Tibor@mkk.szie.hu EMS&ECAM 2013 09-13 Sept. Reading UK

Outline Aims Material Methods Results Conclusions EMS&ECAM 2013 09-13 Sept. Reading UK Outline Aims Material Methods Results Conclusions

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

Traditional phenology EMS&ECAM 2013 09-13 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

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

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 (0.45-0.52μm), red (0.6-0.7μm), and near-infrared (NIR) wavelengths (0.7-1.1μm), 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 (0.45-0.52μm), red (0.6-0.7μm), and near-infrared (NIR) wavelengths (0.7-1.1μm), 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 (0.45-0.52μm), red (0.6-0.7μm), and near-infrared (NIR) wavelengths (0.7-1.1μm), 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 (2003-2012) on a sample area with the size of EMS&ECAM 2013 09-13 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 (2003-2012) . The average EVI of that 400 pixels was used to characterise land surface vegetation.

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 (0.45- 0.52μm), red (0.6-0.7μm), and near-infrared (NIR) wavelengths (0.7-1.1μm), respectively. In general, G=2.5, C1=6.0, C2=7.5, and L=1.

Material Traditional observations EMS&ECAM 2013 09-13 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

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.

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.

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.

Time course of the spatial average EVI values for the sample area EMS&ECAM 2013 09-13 Sept. Reading UK Time course of the spatial average EVI values for the sample area

rate of change in the curvature of the fitted logistic models EMS&ECAM 2013 09-13 Sept. Reading UK rate of change in the curvature of the fitted logistic models Increasing period of EVI

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

The corresponding phenological transition dates are defined as EMS&ECAM 2013 09-13 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).

Trends of the length of the growing season (F4-F1, F3-F2) EMS&ECAM 2013 09-13 Sept. Reading UK Trends of the length of the growing season (F4-F1, F3-F2)

Traditional observations of trees EMS&ECAM 2013 09-13 Sept. Reading UK 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

Traditional observations of trees EMS&ECAM 2013 09-13 Sept. Reading UK Traditional observations of trees

EVI values on pixel level EMS&ECAM 2013 09-13 Sept. Reading UK EVI values on pixel level

EVI values on pixel level EMS&ECAM 2013 09-13 Sept. Reading UK EVI values on pixel level

Traditional observation of agricultural plants EMS&ECAM 2013 09-13 Sept. Reading UK 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

Traditional observation of agricultural plants EMS&ECAM 2013 09-13 Sept. Reading UK Traditional observation of agricultural plants

EVI values on pixel level EMS&ECAM 2013 09-13 Sept. Reading UK EVI values on pixel level Heading or flowering Harvest

EVI values on pixel level EMS&ECAM 2013 09-13 Sept. Reading UK EVI values on pixel level

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.

Thank you for your attention! EMS&ECAM 2013 09-13 Sept. Reading UK Thank you for your attention!