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Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

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Page 1: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Stat 406 – Statistical Methods for Spatial Data

Spring 2008

Topics overview

Stat 4066 (Spring 2008) Spatial Statistics Topics overview 1 / 24

Page 2: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Part I: Geostatistics

Precision agriculture

(data and images courtesy of M. Perez-Bidegain and P.Barbagelata)

Stat 4066 (Spring 2008) Spatial Statistics Topics overview 2 / 24

Page 3: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture: Analysis of soil fertility

0 100 200 300 400

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oord

inat

e(m

)

South Field−−−sampled locations

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Multiple measurements for eachsample:

SOM (soil organic matter)

soil Ph, P (Phosphorus)

K (Potassium)

CEC (Cation exchange capacity)

Mg (Magnesium)

Stat 4066 (Spring 2008) Spatial Statistics Topics overview 3 / 24

Page 4: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture

Histogram of mg.z

mg.z

Fre

quen

cy

50 100 150 200 250 300

05

1015

2025

Stat 4066 (Spring 2008) Spatial Statistics Topics overview 4 / 24

Page 5: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture

0 100 200 300 400

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X coordinate(m)

MG

0 50 100 150 200 250

100

200

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MG

Stat 4066 (Spring 2008) Spatial Statistics Topics overview 5 / 24

Page 6: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture

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oord

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data

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rd Y

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data

data

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quen

cy

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Stat 4066 (Spring 2008) Spatial Statistics Topics overview 6 / 24

Page 7: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture

0 100 200 300 400

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00

100

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Y C

oord

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South field−−−Magnitude of MG

Stat 4066 (Spring 2008) Spatial Statistics Topics overview 7 / 24

Page 8: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture

0 100 200 300 400

010

020

030

0

●●

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X coordinate(m)

Y c

oord

inat

e(m

)

South field: Contour Plot of MG

Stat 4066 (Spring 2008) Spatial Statistics Topics overview 8 / 24

Page 9: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture

0 100 200 300 400

010

020

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Stat 4066 (Spring 2008) Spatial Statistics Topics overview 9 / 24

Page 10: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture

0 100 200 300 400

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Stat 4066 (Spring 2008) Spatial Statistics Topics overview 10 / 24

Page 11: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Precision agriculture

X coordinate(m)

Y c

oord

inat

e(m

)

MG

South plot: Perspective Plot of MG

Stat 4066 (Spring 2008) Spatial Statistics Topics overview 11 / 24

Page 12: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Meteorology and Climatology

Data sets that encompass hundreds of location sites are common. (e.g.Historical Climate Network (HCN) developed and maintained by NOAA)now has several hundreds location sites:

The Precipitation Network: 5873 sites

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Meteorology and Climatology

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Page 14: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Agriculture: Pollen Disspersal

–data collected by S. A. Goggi (ISU, Department of Agronomy) and herteam, in 2003 and 2004

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Page 15: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Agriculture: Pollen Disspersal

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Part II: Areal(Lattice) data

Map of proficiency in Math for 8-th graders in Wisconsin, 2003

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Page 17: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Spatial distribution of herbivorous mites

Consider a situation in which the attribute variable of interest correspondsto small counts on a spatial grid. Such a situation is represented by astudy of the spatial distribution of herbivorous mites (Hairston, N.G., Hill,R.W. and Ritte, U. (1971). The interpretation of aggregation patterns, InPatil, G., Pielou, E.C. and Waters, W.E., eds., Statistical Ecology Volume1: Spatial Patterns and Statistical Distributions, the Pennsylvania StateUniversity Press, University Park, Pennsylvania.).

Data were collected from an 8× 8× 1 inch piece of old field habitat, fromwhich mites were extracted and recorded as from one of 64 quadratsdefined by a two-dimensional 1× 1 inch grid place over the exposedsurface of the sampled habitat.

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The data are reproduced below, showing the spatial distribution of thesesmall counts.

ui

vi 1 2 3 4 5 6 7 8

1 2 1 2 1 0 0 1 22 1 1 1 1 3 4 1 43 0 1 0 2 2 1 3 14 0 0 0 3 3 0 1 25 2 1 0 1 1 1 0 06 1 1 0 1 2 1 0 17 0 3 1 0 1 3 3 38 0 0 0 0 1 5 0 1

Hairston, Hill and Ritte analyzed these data with varying quadrat sizes bypooling adjacent 1× 1 inch squares, and computing for each an index ofaggregation. In a comment on that analysis, R.M. Cormack points outthat patterns of aggregation are fundamentally a question of “the behaviorof neighbors”.

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Page 19: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Part III: Point Patterns

Plant Pathology–Infection in Papaya:(data and images courtesy of Paul Esker)

–due to phytoplasmas (phytoplasma are microorganisms that are notculturable (i.e., they cannot be grown on agar media), however, they cancause devastating effects in crops).

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Page 20: Stat 406 -- Statistical Methods for Spatial Datapcaragea/S40608/Notes/intro_examples_08.pdf · Stat 406 – Statistical Methods for Spatial Data Spring 2008 Topics overview Stat 4066

Plant Pathology

This data was collected by Anna Padovan and Karen Gibb from CharlesDarwin University (Darwin, Northern Territories, Australia), in conjunctionwith Forrest W. Nutter, Jr., Department of Plant Pathology (Iowa StateUniversity) in the the Northern Territories of Australia. Plants wereexamined monthly and those suspected of being infected had samplestaken for further testing to verify if the plant was infected. The use ofmolecular tools was used and results indicated that two dominantphytoplasma types were found: TBB (tomato big bud) and SPLL-V4(sweet potato little leaf V4). These two pathogens are genetically similarto the yellow crinkle disease and based on the genetic makeup are in thefaba bean phyllody. At the end of the 3-year study period, there were atotal of 230 infected papaya (this includes both TBB and SPLL-V4). Ofthat, 76 were TBB while 154 were V4. This is approximately 6.2% of thetotal plants in the plantation. From these 3 plots, it appears that theremay be something interesting spatially, especially when examining allinfected trees or the V4-infected trees.

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Plant Pathology

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Ecology

Nest initiation or nest destruction: (data and images courtesy ofDale Tessin)

Waterfowl nesting data collected during the breeding season of 1997 inSaskatchewan, Canada. The one fourth section field of nesting habitatsearched contained 154 total nests, or nests initiated during the season,and 50 nests destroyed by predators. After nests were found, they werefollowed until the young successfully fledged or the nest was depredated.

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Ecology

This is a habitat map for the field, where greens represent grasslandnesting habitat and blues represent open water. Both the black and yellowdots represent nest locations (black: initiation, yellow: depredated).

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Ecology

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