10/19/2015
Vegetation, climate and
satellite data
ANNA MARIA JÖNSSON, INST. FÖR NATURGEOGRAFI OCH EKOSYSTEMVETENSKAP, LU
Vegetation, climate and satellite data
• Satellite data properties
• Climate and Biomes
• Annual changes and Phenology
• Ecosystems and human impact
• Kenya - exercise
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10/19/2015
Why use satellites to monitor vegetation?
• Continuous updates, every 1-8-16 day
• Large scale coverage
• Monitor vegetation changes and land use
• Assess climate change impacts
• Study the effect of extreme weather events
Satellite data properties - Resolution
Reflectance (%)
60
Landsat ETM wavebands
3
12
5
4
7
50
40
Senescent leaves
30
20
Yellowing
10
leaves
Green leaves
0.6
1.0
visible
NIR
1.4
1.8
2.2
2.6
1
3
2
Wavelength
(micro meter)
MIR
Temporal
- return time
0.45-0.52 µm
0.52-0.60 µm
5
4
Spatial
0.63-0.69 µm
7
Spectral (radiometric)
- band width, no. of bands
0.76-0.90 µm
10.4-12.5 µm
2.08-2.35 µm
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Relative absorbance
Landsat Thematic Mapper (TM) Sensor
vegetation
other surfaces
400
500
600
700
800
Band 1 Band 2 Band 3
(B)
(G)
(R)
Band 4
(NIR)
2400 nm
Wavelength
Band 5, 6, 7
False Colour Image
Relative reflectance
Landsat TM
900
vegetation
other
400
500
600
700
Band 1 Band 2 Band 3
(B)
(G)
(R)
800
900
Band 4
(NIR)
2400 nm
Wavelength
Band 5, 6, 7
Red (R)
level
RGB
false-colour
image
Green (G)
level
Blue (B)
level
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10/19/2015
Satellite data properties – False color images
Relative reflectance
Vegetation
Rocks
Soil
Clear water
Water with phytoplankton
400
500
600
700
Band 1 Band 2 Band 3
(B)
(G)
(R)
800
Band 4
(NIR)
900
2400 nm
Wavelength
Band 5, 6, 7
Red (R)
level
RGB
false-colour
image
Green (G)
level
Blue (B)
level
Landsat FCC
Near Infrared ref. = Red color
Red ref. = Green color
Green ref. = Blue color
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10/19/2015
Satellite data for calculating Vegetation Indices
Spektral signatur för vatten, skog, jord,
gräsvegetation och moln
VI vegetation index
VI=NIR-R
NDVI normalised VI
NDVI=(NIR-R)/(NIR+R)
- Compensates for
differences in light
conditions between
different times and
places
- Enhancs small
differences e.g.
between soil and
vegetation
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10/19/2015
Comparison FCC & NDVI
NDVI time series to assess annual changes
NDVI (HQ)
○
NDVI (LQ)
Snow or ice
○ NDVI , NDVI (HQ)
○ red reflectance data
○ NIR reflectance data
snow & ice
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10/19/2015
Satellite data - to monitor vegetation responses
• annual changes vs disturbances
• trends in vegetation cover induced by climate
change
• changes in land use & altered availability of
resources, e.g. water and nitrogen
• large scale distribution of vegetation types
Global vegetation pattern - map based on MODIS data
Deciduous Needleleaf
Evergreen Needleleaf
Deciduous Broadleaf
Sulla-Menashe, D et al. (2011), Remote Sensing of Environment 115, 392–403
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10/19/2015
Biom
• Climate influence vegetation
• regional assemblages of plant communities
Figur: wikipedia
Threshold values to depict climate influence on vegetation distribution
Skåne
Annual T mean 6.5-8°C
Annual precipitation 500-800 mm
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10/19/2015
Holdridge (1947) ’Life Zones’ model
Ice
Latitudinal
Belts
Altitudinal
Belts
Desert
Nival
Polar
Biotemperature (°C)
1.5°
1.5°
Dry
Tundra
Subpolar
Moist
Tundra
Wet
Tundra
Rain
Tundra
Alpine
3°
3°
Desert
Boreal
Dry
Scrub
Moist
Forest
Wet
Forest
Rain
Forest
Subalpine
6°
6°
Desert
Cool temperate
12°
Warm temperate
Desert
24°
Subtropical
Tropical
Desert
Desert
Scrub
Steppe
Moist
Forest
Wet
Forest
Rain
Forest
Montane
Thorn
Lower montane
Dry
Wet
Moist
Rain
Steppe
Thorn
Forest
Forest
Forest
Forest Pre-montane
Woodland
Very
Dry
Wet
Thorn
Moist
Rain
Dry
Forest
Forest
Woodland
Forest
Forest
Forest
12°
Desert
Scrub
Desert
Scrub
24°
Annual precipitation (mm)
Temperature as a control on plant distributions
Poleward and alpine biome limits
→ often correspond to low temperature isotherms
→ are often ”hard” physiological limits – result of processes that directly
limit survival in a given environment
Low-latitude and low-altitude biome limits are typically ”soft” – determined by
competition between different plant types within their physiological niches
physiology
determines limits
competition
determines limits
Evergreen broadleaf trees
Summergreen broadleaf trees
Needleleaf trees
Shrubs
-80
-60
-40
-20
-10
0
10
Absolute minimum temperature °C
20
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Temperate evergreen forest, Tasmania
Deciduous beech forest, Poland
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Evergreen coniferous forest, Finland
Alpine tundra, New Zeeland
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Water availability as a control on plant distributions
Potential evapotranspiration
ratio (PET/precipitation)
drier
moister
Vegetation type
forest
savannah
desert
New Zeeland, moist forest
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New Zeeland, steppe
Australian arid shrubland
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Adaptation to water-stressed environment: deep roots
Death Vally, California
Adaptation to water-stressed environment: ephemeral life cycle
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Adaptation to water-stressed environment: drought-deciduous phenology
Adaptation to cold winters
• Deciduous
• Evergreen, development of
cold hardiness
• Annual plants
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10/19/2015
Adaptation to (summer) drought
• Deciduous
• Succulent
• Deep root system
• Ephemeral lifecycle,
green only during the rain period
Adaptation to light competition
• Early in season
• Investment in trunk
• Liana
• Shade tolerant
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Convergent evolution
Where the climate is the same,
the organisms are also very similar
plant structures – leaf types – plant spacing
Fagus sylvatica
Southern hemisphere
Ice
0.
5
0.
25
Northern hemisphere
Nothofagus
1
Desert
2
1.5°
4
3°
Dry
Moist
Wet Rain
Tundra Tundra Tundra Tundra
Desert
6°
Dry
Scrub
Moist
Wet Rain
Forest Forest Forest
8
Rain
Wet
Desert Desert Steppe Moist
Scrub
Forest Forest Forest
Thorn
Wet Rain
Moist
Desert Desert Steppe Dry
Scrub Woodland Forest Forest Forest Forest
80
00
40
00
20
00
10
00
Wet
Desert Thorn Very Dry Dry
Moist
Rain
Scrub Woodland Forest Forest Forest Forest Forest
50
0
12
5
62
.5
Desert
25
0
24°
16
12°
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10/19/2015
Geographic distribution of potential climatic constraints to
plant growth derived from long-term climate statistics
Changes in Terrestrial Net Primary Production
Increased NPP
from 1982 to 1999.
Calculated from GIMMS
and PAL data sets.
R. R. Nemani et al., Science 300, 1560 (2003).
Drought-Induced Reduction
from 2000 to 2009
Satellite data from MODIS
M. Zhao, et al. Science 329, 940(2010)
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Liebligs minimum lag
• Ecological processes are determined by one or
a few resources, i.e. the most limiting factor.
• Resources and raw material that are plentiful
will be partly unexploited.
• The distribution of a species is determined by
the factor that the organism has the least
adaptation to or control over.
Allocation – a way of balancing
supply and need
The root – shoot ratio is influenced by availability of water and nitrogen
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Allocation of biomass
in relation to climate
Leaves
Roots
Drought index (PET/precipitation)
0.2
0.4
0.6
0.8
1.0
Stems
0
20
40
60
80
100 %
Grimes triangle: different species in different environments
Ruderals
Competitors
Stress tolerators
Occurrence of environmental stress
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10/19/2015
Impact of average climate conditions & extreme events
The response curve depends on
species specific adaptations and ability of acclimatization
Summary
Annual plants
Perennial plants
Seasonal dormancy
Adaptation
(root/shoot ratio)
Bio-indicators
Sensitive
Avoidance/Tolererance
Climate conditions
Species specific stress response
Stress factor
Inter-specific competition
Too little or too much?
Dominating vegetation
Temperature
Oxygen
Heavy metals
Light
Water
Salt
Air pollutants
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