icpa_keynote08-berry-so where is precision ag
TRANSCRIPT
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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)
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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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)
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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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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