land surface phenology versus traditional observations

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; [email protected](2) Hungarian Meteorological Service; [email protected]; [email protected]; [email protected](3) Szent István University Institute of Botany and Ecophysiolgy; [email protected]

EMS&ECAM 2013 09-13 Sept. Reading UK

mailto:[email protected]













2

Outline•Aims•Material•Methods•Results•Conclusions


3

Aims of our study•Retrieve land surface phenological data

from satellite observations•Comparing traditional phenological

observation data with land surface phenological data

4


IntroductionTraditional 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

Material

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

• Sample area: Iklad (5 km x 5 km) covered by different agricultural and native plants


6

Material• Satellite data:

▫ Enhanced Vegetation Index (EVI) from MODIS placed at Terra and Aqua satellites (NASA, LP DAAC, 2011)

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

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.

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.




7

• 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.

redred

blue

red

nir

red

nir

LCCGEVI

21

1

Material


8

•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);

Material

native plants

agricultural plants


9

•The site of the traditional observations were identified by pixel-level (250m x 250m)

•The EVI values of those pixels were analysed.

Material


10

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

•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

1 15 29 43 57 71 85 99 1131271411551691831972112252392532672812953093233373513650

0.1

0.2

0.3

0.4

0.5

0.6

fitted 2011fitted 2012obs 2011obs 2012


13

rate of change in the curvature of the fitted logistic models

1 17 33 49 65 81 97 113129145161177193

20112012

DOY

129143157171185199213227241255269283297311325339353

DOY

F1

F2

F3

F4

Decreasing period of EVIIncreasing period of EVI


14

Causes of shifting?

32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 650.0

10.0

20.0

30.0

40.0

50.0

60.0

Above zero temperature sum from 1st of February

20112012

DOY

oC


15

•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).

2002 2004 2006 2008 2010 2012 20140

50

100

150

200

250

300

350

F1F2F3F4D

OY


16

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

2003 2004 2005 2006 2007 2008 2009 2010 2011 20120

50

100

150

200

250

f(x) = 2.76363636363636 x + 192.2R² = 0.357935180021069

f(x) = 1.89090909090909 x + 99R² = 0.147905043211902

length of growing seasonLinear (length of growing season)duration of max greennessLinear (duration of max greenness)

DAYS

Significant (5%)


17

BBCH

10 Sprouting of leaves

19 Beginning of the unfolding of leaves

60 Beginning of flowering

65 Full flowering

69 End of flowering93 Fall of leaves

97 End of falling leaves

Traditional observations of trees


18

Traditional observations of trees

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 3410

50

100

150

2012

locustpoplaroak

DOY

BBCH

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 3410

50

100

150

2011

locustpoplaroak

DOY

BBCH


19

EVI values on pixel level

1 17 33 49 65 81 97 113

129

145

161

177

193

209

225

241

257

273

289

305

321

337

353

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

2011

locustpoplaroakFL loc.FL pop.FL oak

DOY

EVI


20


1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 450

0.1

0.2

0.3

0.4

0.5

0.6

2012

locustpoplaroakFL locFL popFL oak

DOY

EVI


21

Traditional observation of agricultural plantsBBCH wheat

BBCH maize

BBCH sunflower

00 sowing 00 sowing 00 sowing

09 Emergence 09 Emergence 09 Emergence

21Beginning of tillering 13 3 leaves

unfolded 144 leaves unfolded

31First node at least 17 7 leaves

unfolded 53 Inflorescence

55Middle of heading 59 59 End of tassel

emergence 65 Full flowering

65 Full flowering 67 Flowering declining

85 Soft dough 85 85 dough stage 69 End of flowering

92 Over-ripe 89 Fully ripe

99 Harvest99

Harvest99 99 Harvest


22

Traditional observation of agricultural plants

-100 -50 0 50 100 150 200 250 300 350 4000

50

100

150

2011

wheatmaizesunflower

DOY

BBCH

-100 -50 0 50 100 150 200 250 300 350 4000

50

100

150

2012

wheatmaizesunflower

DOY

BBCH


23


1 17 33 49 65 81 97 113

129

145

161

177

193

209

225

241

257

273

289

305

321

337

353

-0.1000

0.0000

0.1000

0.2000

0.3000

0.4000

0.5000

0.6000

0.7000

2011

wheatmaizesunflower

DOY

EVI

Heading or flowering

Harvest


24


1 17 33 49 65 81 97 113

129

145

161

177

193

209

225

241

257

273

289

305

321

337

353

0.0000

0.1000

0.2000

0.3000

0.4000

0.5000

0.6000

0.7000

2012

wheatmaizesunflower

DOY

EVI

Heading or floweringHarvest


25

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!

land surface phenology versus traditional observations

Documents