1
Remotely Sensed Estimates of Aboveground Net Primary Production of Cultivated Grasslands in a Suburbanizing Landscape By: Paul A. Pellissier, Scott V. Ollinger, Lucie C. Lepine --Background-- --Methods-- --Grass is More Than Just Green-- Components of Net Primary Production? •In many terrestrial ecosystems Nitrogen (N) is central to, and often limits, net primary production (NPP) of terrestrial plants. •In cultivated grasslands N is often supplied, by way of fertilizer, to achieve management goals. This may lead to other limiting factors such as available water. •Understanding how these systems function in terms of N cycling and carbon storage at the landscape level is important in quantifying their environmental impacts at the regional to global scale. Site Description-- Lamprey River Watershed: • Fifth order river located in southern New Hampshire • Area: 479 square kilometers • Encompasses nine towns • Population density ranges from 0 to 630 people km -2 ,with an average of 129. • 17.5% of land area is non-forested • Surface waters currently impaired from excess N Prepared by Paul A. Pellissier for the NSF EPSCoR National Conference, 4 th November 2013 --Abstract-- The current study aims to determine generalizable relationships between aboveground NPP and spectral reflectance in both turf and agricultural grasslands. Hyperspectral measurements of canopy reflectance collected over two growing seasons are correlated with foliar and environmental attributes. Relationships derived from ground- based canopy reflectance will be applied to watershed-scale airborne imagery. Field Collection: Two summers, two aims: The goal of summer 2012 was to collect data critical to relating airborne and field-based spectra, whereas during summer 2013 efforts were focused on determining relationships between plant /environmental conditions and ground based spectra. Data 2012 •Airborne imagery: approx. 500km 2 , spatial resolution 5m 2 •Eighteen field sites established •Ground-based canopy reflectance •Canopy height •Foliar biomass and N content Data 2013 •Intensive ground based reflectance, sub-meter spatial resolution •Canopy height •Foliar biomass and N content •Leaf water content •Soil moisture •Leaf mass per area •Photosynthetic capacity Spectral Relationships: Attribute Spectral Prediction Important Regions Figure 1: Site location within New Hampshire. Lamprey River Watershed Photo 1: UNH wants to cut my grass? Collecting biomass at one of our sites located in Deerfield, NH. (Photo by L. Lepine) Photo 2: Collecting field measurements of hayfield canopy reflectance with a portable field spectrometer at the UNH Fairchild Dairy, Durham, NH. (Photo by L. Lepine) Looking Forward: Figure 2: Averaged spectral reflectance curves of grass canopies by management regime. Curves represent over 3500 individual spectra taken at 18 sites located within the Lamprey River watershed. Average spectral reflectance differs significantly (P<0.003) for several regions ( 750-920nm*, 920-1150nm, 1151- 1350nm**)in the NIR plateau . *Hay fields and pasture P=0.0165. **Hay field and pasture P=0.6933. 35 0 450 55 0 65 0 750 85 0 95 0 10 5 0 1150 1250 13 5 0 1450 15 5 0 16 5 0 1750 1850 1950 20 5 0 2150 22 5 0 23 5 0 2450 0% 10% 20% 30% 40% 50% 60% Grass Canopy Reflectance by Management Practice Pasture Hayfield Residental Fallow Field Wavelength (nm) Reflectance Visible Light Near Infrared Short-wave Infrared Future efforts will focus using the relationships shown here to predict NPP, scaling these predictions to the watershed scale, and interpreting any observed spatial patterns in NPP. Foliar Water Content Prediction and importance plots based on PLS regression of 5 extracted factors . Sample size, n=29; Root mean PRESS=1.02361. Regions of influence include the blue green transition zone, chlorophyll absorption well, red edge, and NIR plateau. 0 1 2 3 4 5 6 0 1 2 3 4 5 6 f(x) = 0.489265460409941 x + 1.19375181028842 R² = 0.489265460405842 Actual Predicted RMSE=0.61 300 500 700 900 1100 1300 1500 1700 1900 2100 23 00 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 Wavelength (nm) VIP Score Dry Biomass Prediction and importance plots based on PLS regression of 4 extracted factors . Sample size, n=29; Root mean PRESS=0.93348. Importance plot shows the heavy influence throughout the visible wavelengths including blue, green and red edge regions. 0 200 400 600 800 1000 1200 -100 0 100 200 300 400 500 600 700 f(x) = 0.612403107323914 x + 102.869586607326 R² = 0.612404539497647 Actual Predicted RMSE=99.93 300 500 700 900 1100 1300 1500 1700 1900 2100 23 00 0.6 0.8 1 1.2 1.4 1.6 1.8 2 Wavelength (nm) VIP Score Foliar %N Prediction and importance plots based on Partial Least Squares (PLS) regression of 11 extracted factors . Sample size, n=27. Root mean PRESS= 0.73447. The Importance plot shows the heavy influence of chlorophyll absorption in the blue region and reflectance in the green region. The PLS analysis also values the red edge, and a possible water absorption feature near 1300nm. 300 500 700 90 0 110 0 13 00 15 00 1700 1900 210 0 23 00 0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3 2.5 Wavelength (nm) VIP Score 1.00 1.50 2.00 2.50 3.00 3.50 4.00 1.00 1.50 2.00 2.50 3.00 3.50 4.00 f(x) = 0.942313750582443 x + 0.116649322974628 R² = 0.942599729253785 Actual Predicted RMSE=0.1 Photosynthet ic Capacity Prediction and importance plots based on PLS regression of 2 extracted factors. Root mean PRESS=0.589011 PLS regression was preformed using 8 modeled light response curves incorporating 80 instantaneous photosynthetic assimilation readings (plotted) Importance plot shows importance of short wave infrared, red edge, and green regions 12 14 16 18 20 22 24 26 28 12 14 16 18 20 22 24 26 28 f(x) = 0.898108110047342 x + 2.04123767669116 R² = 0.898108110053036 Actual Predicted RMSE=1.48 300 500 700 900 1100 1300 1500 1700 19 00 2100 2300 0.6 0.8 1 1.2 1.4 1.6 1.8 Wavelength (nm) VIP Score

By: Paul A. Pellissier, Scott V. Ollinger, Lucie C. Lepine

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Field Collection: Two summers, two aims : The goal of summer 2012 was to collect data critical to relating airborne and field-based spectra, whereas during summer 2013 efforts were focused on determining relationships between plant /environmental conditions and ground based spectra. - PowerPoint PPT Presentation

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Page 1: By: Paul A. Pellissier, Scott V. Ollinger, Lucie C. Lepine

Remotely Sensed Estimates of Aboveground Net Primary Production of Cultivated Grasslands in a Suburbanizing LandscapeBy: Paul A. Pellissier, Scott V. Ollinger, Lucie C. Lepine

--Background--

--Methods----Grass is More Than Just

Green--

Components of Net Primary Production?• In many terrestrial ecosystems Nitrogen (N) is central to, and often limits, net primary production (NPP) of terrestrial plants.

• In cultivated grasslands N is often supplied, by way of fertilizer, to achieve management goals. This may lead to other limiting factors such as available water.

•Understanding how these systems function in terms of N cycling and carbon storage at the landscape level is important in quantifying their environmental impacts at the regional to global scale.

Site Description-- Lamprey River Watershed:• Fifth order river located in

southern New Hampshire• Area: 479 square kilometers• Encompasses nine towns • Population density ranges

from 0 to 630 people km-2,with an average of 129.

• 17.5% of land area is non-forested

• Surface waters currently impaired from excess N

Prepared by Paul A. Pellissier for the NSF EPSCoR National Conference, 4th November 2013

--Abstract--• The current study aims to determine

generalizable relationships between aboveground NPP and spectral reflectance in both turf and agricultural grasslands.

• Hyperspectral measurements of canopy reflectance collected over two growing seasons are correlated with foliar and environmental attributes.

• Relationships derived from ground-based canopy reflectance will be applied to watershed-scale airborne imagery.

Field Collection:Two summers, two aims: The goal of summer 2012 was to collect data critical to relating airborne and field-based spectra, whereas during summer 2013 efforts were focused on determining relationships between plant /environmental conditions and ground based spectra. Data 2012•Airborne imagery: approx. 500km2 , spatial resolution 5m2

•Eighteen field sites established •Ground-based canopy reflectance•Canopy height•Foliar biomass and N content

Data 2013• Intensive ground based reflectance, sub-meter spatial resolution•Canopy height•Foliar biomass and N content•Leaf water content•Soil moisture•Leaf mass per area•Photosynthetic capacity

Spectral Relationships:Attribute Spectral Prediction Important Regions

Figure 1: Site location within New Hampshire.

Lamprey River Watershed

Photo 1: UNH wants to cut my grass? Collecting biomass at one of our sites located in Deerfield, NH. (Photo by L. Lepine)

Photo 2: Collecting field measurements of hayfield canopy reflectance with a portable field spectrometer at the UNH Fairchild Dairy, Durham, NH. (Photo by L. Lepine)

Looking Forward:

Figure 2: Averaged spectral reflectance curves of grass canopies by management regime. Curves represent over 3500 individual spectra taken at 18 sites located within the Lamprey River watershed. Average spectral reflectance differs significantly (P<0.003) for several regions ( 750-920nm*, 920-1150nm, 1151-1350nm**)in the NIR plateau . *Hay fields and pasture P=0.0165. **Hay field and pasture P=0.6933.

350 450 550 650 750 850 9501050

11501250

13501450

15501650

17501850

19502050

21502250

23502450

0%

10%

20%

30%

40%

50%

60%Grass Canopy Reflectance by Management Practice

Pasture

Hayfield

Residental

Fallow Field

Wavelength (nm)

Ref

lect

ance

Visible Light Near Infrared Short-wave Infrared Future efforts will focus using the relationships shown here to predict NPP, scaling these predictions to the watershed scale, and interpreting any observed spatial patterns in NPP.

Foliar Water ContentPrediction and importance plots based on PLS regression of 5 extracted factors . Sample size, n=29; Root mean PRESS=1.02361. Regions of influence include the blue green transition zone, chlorophyll absorption well, red edge, and NIR plateau.

0 1 2 3 4 5 60

1

2

3

4

5

6

f(x) = 0.489265460409941 x + 1.19375181028842R² = 0.489265460405842

Actual

Pred

icte

d

RMSE=0.61300 500 700 900 1100 1300 1500 1700 1900 2100 2300

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Wavelength (nm)

VIP

Sco

re

Dry BiomassPrediction and importance plots based on PLS regression of 4 extracted factors . Sample size, n=29; Root mean PRESS=0.93348. Importance plot shows the heavy influence throughout the visible wavelengths including blue, green and red edge regions.

0 200 400 600 800 1000 1200

-100

0

100

200

300

400

500

600

700f(x) = 0.612403107323914 x + 102.869586607326R² = 0.612404539497647

Actual

Pred

icte

d

RMSE=99.93

300 500 700 900 1100 1300 1500 1700 1900 2100 23000.6

0.8

1

1.2

1.4

1.6

1.8

2

Wavelength (nm)

VIP

Sco

re

Foliar %NPrediction and importance plots based on Partial Least Squares (PLS) regression of 11 extracted factors . Sample size, n=27. Root mean PRESS= 0.73447. The Importance plot shows the heavy influence of chlorophyll absorption in the blue region and reflectance in the green region. The PLS analysis also values the red edge, and a possible water absorption feature near 1300nm. 300 500 700 900 1100130015001700190021002300

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2.1

2.3

2.5

Wavelength (nm)

VIP

Sco

re

1.00 1.50 2.00 2.50 3.00 3.50 4.001.00

1.50

2.00

2.50

3.00

3.50

4.00

f(x) = 0.942313750582443 x + 0.116649322974627R² = 0.942599729253785

Actual

Pred

icte

d

RMSE=0.1

Photosynthetic Capacity Prediction and importance plots based on PLS regression of 2 extracted factors. Root mean PRESS=0.589011PLS regression was preformed using 8 modeled light response curves incorporating 80 instantaneous photosynthetic assimilation readings (plotted)Importance plot shows importance of short wave infrared, red edge, and green regions

12 14 16 18 20 22 24 26 2812

14

16

18

20

22

24

26

28

f(x) = 0.898108110047342 x + 2.04123767669116R² = 0.898108110053036

Actual

Pred

icte

d

RMSE=1.48 300 500 700 900 1100 1300 1500 1700 1900 2100 23000.6

0.8

1

1.2

1.4

1.6

1.8

Wavelength (nm)

VIP

Sco

re