ICPA_Keynote08-Berry-So Where is Precision Ag

8/3/2019 ICPA_Keynote08-Berry-So Where is Precision Ag

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So Where Is Precision Ag?a brief history, current expression and future directions

Joseph K. Berry

W. M. Keck Visiting Scholar in Geosciences, Geography, University of Denver

Principal, Berry & Associates // Spatial Information [email protected] Web www.innovativegis.com/basis/

9th International Conference on Precision Agriculture

July 20-23, 2008Denver, Colorado
mailto:[email protected]://www.innovativegis.com/basis/http://www.innovativegis.com/basis/mailto:[email protected]


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What Is Precision Agriculture?

Things to keep in mind

PA is about doing the right thing at the

right place and at the right time

itidentifies and responds to the

variability within a field

itaugments indigenous knowledge

(not a replacement)

(PA has been around awhile, Circa 1992)

(Berry)

it is a radicallydifferent technology

with extremelyhigh expectations


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Historical Setting and Evolution

Spatial Database Managementlinkscomputer mapping techniques with traditional database capabilities (80s)

CM + SDBM of the first two decades is often referred to as Desktop GIS

Multimedia Mappingfull integration of GIS, GPS, RS,Internet and visualization technologies (00s)

Computer Mappingautomates thecartographic process (70s)

8,000 years of mapping

(Berry)

Toolbox supporting Precision Agfocus of this presentation

Map Analysisrepresentation ofrelationships within and among mapped data (90s)

Mapping and InventoryWhat is WhereMap AnalysisWhy and So What

Note: U.S. Dept. of Labor identifiesGeotechnology(GPS, GIS, RS)as one of three "mega technologies"for the 21st century and promises to change how we conceptualize, utilize and visualize spatial relationships

in scientific research and commercial applications(the other two are Biotechnologyand Nanotechnology)


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Yield Limiting Factors (the basis of PA)

Water

Weather

Topography

Nutrients

Weeds

Pests

Genetics Seeding Rate

Other

(Berry)

Candidate for Precision Agriculture andSite-specific Management

if and only if

the factor is a significantdriving variable

it has measurablespatial variability

its variability can be explainedandspatial relationships established

it exhibits a spatial responseto practical management actions

and results in

production gains, increased profitability and/or improved stewardship

On-Farm Studies (Research?)


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Whole Field vs. Site Specific Management

Whole-fieldassumes the average conditions are the

same everywhere within the field (uniform/homogenous)

Management action is the same throughout the field

Z1

Z3

Z2

Z1

Z2

Discrete Management Zones

break the field into areas ofsimilar conditions (zones)

Management action is the

same within each zone

Continuous Surfacesbreak the field into smallconsistent pieces (cells) that track specific

conditions at each location

Management action varies throughout the field

(Berry)

The bulk of agriculturalresearch has been

non-spatial

but PA is all about

spatial relationships/patterns

Research Opportunity

Is Smart Sampling really dumb?


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MAP Analysis Framework (Keystone Concept)

(Berry)

Click on

Zoom Pan Rotate Display

Shading

Manager

Analysis

Frame(Grid )each map layer

is organized as a

geo-registered

matrix of numbers

Map

Stack

Continuous regular grid cells (objects)

:

--, --, --, --,

--, --, --, --,

--, --, --, --,

--, 149.0, --,

--, --, --, --,

:

Grid

Table


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Surface Modeling Techniques

(Berry)

Surface Modelingmaps the spatial distribution and pattern of point dataMap Generalizationcharacterizes spatial trends (tilted plane)

Spatial Interpolationderiving spatial distributions (e.g. IDW, Krig)

Otherroving windows and facets (e.g., density surface; tessellation)

Spatial Data Mininginvestigates the numerical relationships in mapped data

Descriptiveaggregate statistics (e.g. average, stdev, similarity; clustering)

Predictiverelationships among maps (e.g., regression)

Prescriptionappropriate actions (e.g., decision rules; optimization)

Spatial Analysisinvestigates the contextual relationships in mapped data

Reclassifyreassigns map values (position, value, size, shape, contiguity)

Overlaymap coincidence (point-by-point; region-wide; map-wide)

Distanceproximity and connection (movement; optimal paths; visibility)

Neighborsroving windows (slope; aspect; diversity; anomaly)

Grid-Based Map Analysis (workshop topics)


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Geographic Distribution(Mapping the Variance)

The iterative smoothing process is similar to slapping a big chunk of

modelers clay over the data spikes, then taking a knife and cutting away

the excess to leave acontinuous surface that encapsulates thepeaks and valleys implied in the original field samples

Continuous SurfaceGeographic Distribution

Numeric Distribution Average, Standard Deviation

(Berry)
http://links/SStat2.ppthttp://links/SStat2.ppthttp://links/SStat2.ppthttp://links/SStat2.ppthttp://links/SStat2.ppthttp://links/SStat2.ppthttp://links/SStat2.ppthttp://links/SStat2.ppthttp://links/SStat2.ppthttp://links/SStat2.ppt


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Spatial Interpolation (soil nutrient levels)

(Berry)

Spatial Interpolation maps the geographic distribution inherent in the data

IDW SurfaceData Spikes

Corn Field Phosphorous (P)


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Comparing Spatial Interpolation Results

Comparison of the

IDWinterpolated surfaceto the

whole field average

shows large differences

in localized estimates

(-16.6 to 80.4 ppm)

Comparison of the

IDW interpolated surface

to theKrig interpolated surface

shows small differences

in localized estimates(-13.3 to 11.7 ppm)

(Berry)


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Spatial Data Mining Techniques

(Berry)















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Visualizing Spatial Relationships

What spatial relationships

do you see?

Interpolated Spatial Distribution

Phosphorous (P)

do relatively high levels

of P often occur with high

levels of K and N?

how often? where?

HUMANS can see broad

generalized patterns

in a single map variable

(Berry)


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Clustering Maps for Data Zones

groups of floating balls in data space identify locations in the field

with similar data patternsdata zones

COMPUTERS can seedetailed patterns in multiple map variables

(Berry)


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The Precision Ag Process(Fertility example)As a combine moves through a field1) it uses GPS to

check its location then2) checks the yield at that

location to3) create a continuous map of the yield

variation every few feet (dependent map variable).

On-the-Fly

Yield Map

Steps 13)

Derived

Nutrient Maps

Step 4)

Prescription Map

Zone 3

Zone 2

Zone 1

The yield map4) is analyzed in combination with

soil, terrain and other maps (independent map

variables) to derive a Prescription Map

(Berry)

Variable Rate Application

Step 5)

5)that is used to adjust fertilization levels every

few feet in the field (action).

Intelligent Implements

As-applied maps

more generally termed the Spatial Data Mining Process(e.g., Geo-Business application)


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ContinuousSpatial Distribution

(Detailed)

Map Analysis

SpatiallyInterpolated data

(Geographic Space Spatial Statistics)

Data Analysis Perspectives(Data vs. Geographic Space)

Identifies the Central Tendency Maps the Variance

Central Tendency

Average = 22.0

StDev = 18.7

TypicalHow Typical

DiscreteSpatial Object

(Generalized)22.0 28.2

Traditional Analysis

Field DataStandard Normal Curve

fit to the data

(Data Space Non-spatial Statistics)

(Berry)


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So Where Are We in Precision Ag?

Yield Mapping done deal for many crops

Soil Nutrient Mapping procedures need validation

Mgt Zone Mapping alternative approaches need study & validation

The Full Precision Farming Process a fair piece to go

IF THEN based onspatial relationships

(Berry)

Description (Where is What) coming on line

Prediction (Why and So What) needs lots of work

Prescription (Do What Where) barely on the research radar Action (Precisely Here) done deal for many farm inputs

PA Nugget


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Spatial Analysis Techniques

(Berry)















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times 10 plus

renumber

Micro Terrain Analysis(a simple erosion model)

(Berry)

Determining Erosion Potential:slope and flow classes arecombined into a single map identifying erosion potential

Field

Elevationisformed by

assigning an

elevation value

to each cell in an

analysis grid

(1cm Lidar)


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Precision Ag

(Individual Field Focus)

Terrain

Soils

Yield

Potassium

CIR Image

Precision Conservation(compared to Precision Ag)

Isolated Perspective2-dimensional

Precision Conservation

(Farm, Watershed, Focus)

Wind Erosion

Runoff

Leaching Leaching

Leaching

Soil

Erosion

Chemicals

(Stewardship Focus) (Production Focus)

Interconnected Perspective

3-dimensional

(Berry)


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Deriving Erosion Potential(regional scale)

Maps of surfaceflow confluence andslope are calculated by

considering relative elevation differences throughout a project area

(Berry)


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Calculating Effective Distance(variable-width buffers)

Effective erosion buffers around a stream expand and contract

depending on the erosion potential of the intervening terrain

(Berry)
http://links/VBUFF.ppt


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Revisit Geo-reference

(2010s)

Map Analysis(1990s)

Computer Mapping(1970s)

Spatial dB Mgt(1980s)

The Early Years

Contemporary GIS

Future Directions

Mapping focus

Data/Structure focus

Analysis focus

Multimedia Mapping(2000s)

Revisit Analytics(2020s)

Hexagon(6 sides)

Square(4 sides)

2D Planar(X,Y Data)

Dodecahedron(12 pentagons)

Hexahedron(6 squares)

3D Solid(X,Y,Z Data)

Cyclical Development(future directions)


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Is GIS Technology Ahead of Science?

2)Is the random thing pertinent in deriving

mapped data?

3)Aregeographic distributions a natural

extension of numerical distributions?

4)Can spatial dependencies within a map variable (spatialautocorrelation) and among map variables (spatial correlation) be

modeled?

5)How can site-specific analysis and on-farm studies contribute

to thescientific body of knowledge?(Berry)

1)Is the scientific method relevant in the data-rich age of knowledge engineering?

Five critical questions underlying Precision Agriculture


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ICPA_Keynote08-Berry-So Where is Precision Ag

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