Patterns of tree and
grass leaf display in the
Lowveld revealed by a
new MISR dataset
Lee-Ann Sinden¹, Bob Scholes¹, Michel
Verstraete² and Sally Archibald¹
¹Global Change and Ecosystem Dynamics, Natural Resources and the Environment, CSIR, South Africa
²European Commission, DG Joint Research Centre (JRC), Italy
Observed Climatevegetation Relationships
• Climate variables important in initiation
of growing stages (Wessels et al, 2006)
• Distinction of tree leaf-out from grass
leaf-out not biologically realistic (Chidumayo,
2001)
• Day length and temperature → tree leafout (Archibald and Scholes, 2007)
• Rainfall → grass leaf-out (Archibald and
Scholes, 2007)
• Relevance for the future
Site Selection and Data
• Sites: differences in geology, soil and
dominant woody vegetation
• Weather data:
• few irregularly-spaced stations,
missing data, no station
• interpolated station data temporally
then spatially for sites without stations
• FAPAR data:
• MISR FAPAR from 2002 to present
• missing values created from
rescaled MERIS FAPAR data series
MSc Research
Goal: identify climate cue for each
phenological metric
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FAPAR index
Rain (mm) and temperature (°C)
Skukuza
Punda Maria PCA
Accumulated rain
rain
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Satara PCA
Accumulated rain
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Ondersabie PCA
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fapar
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Phenological metric
Calculating the metric
1 evergreen fraction
Lowest FAPAR limit for non-riverine pixels
2 start of tree leaf-out
When a four time-step moving average is
exceeded by the FAPAR signal
3 maximum tree FAPAR
Find woody cover % for each pixel using
the woody cover map by Bucini et al, 2010;
assume that tree leaf-out is complete in
three weeks
4 start of grass leaf-out
Subtract the tree signal from the total
FAPAR. When a four time-step moving
average is exceeded by a value in the
grass greenness dataset, grass leaf-out
has begun
5 maximum grass FAPAR
Intercept of y axis
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FAPAR index
Rain (mm) and temperature (°C)
Skukuza 2005/06 growing season
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minT
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fapar
FAPAR index
Rain (mm) and temperature (°C)
Skukuza 2005/06 growing season
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maxT
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Dekad dates
FAPAR index
Rain (mm) and temperature (°C)
Skukuza 2005/06 growing season
rain
tree leaf-out
grass leaf-out
Conclusions and Future Work
• The findings from this work will be used to
suggest how savanna systems are likely to
respond to changing future climates projected by
climate models
• Statistically link each metric with a climate cue –
wavelet analysis may be an option
• Find these climate cues in future climate
projections and suggest future productivity for trees
and grasses in the KNP
Acknowledgements
• South African Weather Service, Agricultural Research
Council: raw weather data
• Marc Pienaar: assistance with interpolation of weather
data
• Linda Hunt: extraction of MISR FAPAR data
• CSIR: funding
References
Archibald, S. and Scholes, R.J. (2007) Leaf leaf-out in a semi-arid African
savanna – separating tree and grass responses to environmental cues, Journal of
Vegetation Science, 18, pp. 583-594.
Chidumayo, E.N. (2001) Climate and phenology of savanna vegetation in southern
Africa, Journal of Vegetation Science, 12, pp. 347-354.
Wessels, K.J., Prince, S.D., Zambatis, N., MacFadyen, S., Frost, P.E., and Van Zyl, D.
(2006) Relationship Between Herbaceous Biomass and 1-km² Advanced Very High
Resolution Radiometer (AVHRR) NDVI in Kruger National Park, South Africa,
International Journal of Remote Sensing, 27(5), pp. 951-973, DOI:
10.1080/01431160500169098.