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8/14/2019 Sand Final Presentation

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A COMPARISON OFA COMPARISON OFSPECTRAL INDICESSPECTRAL INDICES

FOR DIFFERENTFOR DIFFERENT

TREATMENTSTREATMENTS

Callie SandCarleton College

Student Airborne Research Program


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Overview IntroductionCalifornia DroughtMassive Agriculture IndustryMaximization of Water Resources

Experiment

Case Study: Paramount FarmsMASTERField DataIndices!

ResultsComparison of fieldsCalculated Indices

Conclusions and Future Experiments


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The Central Valley and KernCount

Major agriculturalregion in CentralValley

Central Valley:

530,000 acres ofalmonds

$2 billion industry 100% of USs supply

75% of worlds supply Soil and climate


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Water shortages in California3rd year of drought

Increasing populationAlmonds = long-term investments

How to produce more produce with lesswater?

Central Valley Project: 10% allocation Constant observation of plant stress levels Satellite models versus time-consuming

ground-based measurements


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Paramount Farms

Nitrogen/Calcium/Potassium Treatments

Different Water Stress Levels

Part of a larger experiment going on for

several yearsPreviously discovered data: almonds

require more water than previously

thought for optimal production Field Health and Crop Indices


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MASTER

MODIS/ASTER airborne simulator

50 spectral bands in four spectral regionsVisible through thermal infrared


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6.6 n. mi./min65,000 ft

8 n. mi.

24 in.

LENS 12 in.

LENS

6 in.

LENS

4 n. mi

8 n. mi.

21.4 n. mi.

2 n. mi.

at NADIR

IRIS II

Panoramic Camera

16 n. mi

20 n. mi.

16 n. mi

TMS

MAS, MASTER,

AOCI, MAMS

ER-2 Sensor Coverage

Image courtesy of Jeff Myers


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DC-8 Flight

11,500 ft altitude Flew over Paramount Farms and Sheely

Farms

Field data taken July 20-25 Flight data used from FridayCloud coverageMissed ROI

Rough calibration performed to smooth outimage7 meter resolution


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Indices: MethodologyOverview

Three types: greenness/canopy health,water, and foliar chemistryWay of analyzing remote sensing

measurementsMultiple ways to analyze various properties of

the image

Limitations in the spectral band

measurements dictated what ones could becalculatedGap from ~1000 to 1600 nm


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Indices

Calculate indices using ENVI software

Make each band a different index

Test for correlations: r>.9 indicatessimilar dataOnly use one of the correlated

indices

Pick best choiceFinal indices: NDVI, PI2, WBI


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Indices

Comparison of WBI/PI2/NDVI

WBI

PI2: Plant Stress StatusMore fluorescence ~ more stressShort-term health

NDVI: Ranges from -1 to 1

Closer to 1 indicates denser canopy


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Treatments & Indices

Use GPS points to map out regionscorresponding to the different treatments12 treatments in all

Take the average of each treatment area


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Comparisons


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Conclusions

Plots in the best current health overall aretreated with UN 275/KTS 120

Best vegetation coverage (indicator of futurehealth) is UN 275/KTS 75, though UN275/KTS 120 is second-best

However, no strong correlations betweendata

- Wrong map?

- Need more indices that are notavailable

through our MASTER data


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Water & Indices


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Acknowledgements

NSERC, NASA, UC Davis and everyone involved in datameasurements, Susan Ustin, Shawn Kefauver, entireevapotranspiration team, SARP etc.


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References

Almond history.Almond Board of California,

http://www.almond-board.com/index.cfm Glenn, E.; Huete, A.; Nagler, P.; Nelson, S. Relationship between

remotely-sensed vegetation indices, canopy attributes and plantphysiological process. Sensors2008, 8, 2136-2160.

Peuelas, J.; Piol, J.; Ogaya, R.; Filella, I. Estimation of the plantwater concentration by the reflectance Water Index WI(R900/R970). Int. J. Remote Sensing1997, 18:13, 2869-2875.

Zarco-Tejada, P.J. et al. Vegetation stress detection throughchlorophyll a+b estimation and fluorescence effects onhyperspectral imagery. J. Environ. Qual. 2002, 31, 1433-1441.

Petropoulos, G.; Carlson, T.N.; Wooster, M.J.; Islam, S. A reviewof Ts/VI remote-sensing based methods for the retrieval of landsurface energy fluxes and soil surface moisture. Progress inPhysical Geography2009, 33, 224-252:


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