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9th International Conference on Precision Agriculture
July 20-23, 2008 — Denver, Colorado
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 Systems
Email [email protected] — Web www.innovativegis.com/basis/
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
…it identifies and responds to the
variability within a field
…it augments indigenous knowledge
(not a replacement)
(PA has been around awhile, Circa 1992)
…it is a radically different technology
with extremely high expectations
(Berry)
Historical Setting and Evolution
Computer Mapping
automates the
cartographic process (70s)
Spatial Database Management
8,000 years of mapping
links
computer mapping techniques with traditional database capabilities (80s)
…CM + SDBM of the first two decades is often referred to as Desktop
GIS
Mapping and Inventory — What is Where
Map Analysis — Why and So What
Map Analysis
representation of
relationships within and among mapped data (90s)
Toolbox supporting Precision Ag
…focus of this presentation
Multimedia Mapping
full integration of GIS, GPS, RS,
Internet and visualization technologies (00s)
Note: U.S. Dept. of Labor identifies Geotechnology (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 Biotechnology and Nanotechnology)
(Berry)
Yield Limiting Factors (the basis of PA)
 Water
 Weather
 Topography
 Nutrients
 Weeds
 Pests
 Genetics
 Seeding Rate
 Other…
On-Farm Studies (Research?)
Candidate for Precision Agriculture and Site-specific Management
if and only if —
 the factor is a significant driving variable
 it has measurable spatial variability
 its variability can be explained and spatial relationships established
 it exhibits a spatial response to practical management actions
…and results in production gains, increased profitability and/or improved stewardship
(Berry)
Whole Field vs. Site Specific Management
Whole-field assumes the “average” conditions are the
same everywhere within the field (uniform/homogenous)
Management action is the same throughout the field
Discrete Management Zones
Z2
The bulk of agricultural
research has been
“non-spatial”
…but PA is all about
spatial relationships/patterns
Research Opportunity
break the field into areas of
similar conditions (zones)
Z1
Z1
Z3
Management action is the
same within each zone
Z2
Is Smart Sampling really dumb?
Continuous Surfaces break the field into small
consistent pieces (cells) that track specific
conditions at each location
Management action varies throughout the field
(Berry)
MAP Analysis Framework (Keystone Concept)
Shading
Manager
Click on…
Zoom Pan Rotate
Display
Analysis
Frame (Grid )
…each map layer
is organized as a
geo-registered
matrix of numbers
Map
Stack
Grid
Table
Continuous regular grid cells (objects)
:
--, --, --, --,
--, --, --, --,
--, --, --, --,
--, 149.0, --,
--, --, --, --,
:
(Berry)
Surface Modeling Techniques
Grid-Based Map Analysis (workshop topics)
Surface Modeling maps the spatial distribution and pattern of point data…
 Map Generalization— characterizes spatial trends (tilted plane)
 Spatial Interpolation— deriving spatial distributions (e.g. IDW, Krig)
 Other— roving windows and facets (e.g., density surface; tessellation)
Spatial Data Mining investigates the “numerical” relationships in mapped data…
 Descriptive— aggregate statistics (e.g. average, stdev, similarity; clustering)
 Predictive— relationships among maps (e.g., regression)
 Prescription— appropriate actions (e.g., decision rules; optimization)
Spatial Analysis investigates the “contextual” relationships in mapped data…
Reclassify— reassigns map values (position, value, size, shape, contiguity)
Overlay— map coincidence (point-by-point; region-wide; map-wide)
Distance— proximity and connection (movement; optimal paths; visibility)
Neighbors— roving windows (slope; aspect; diversity; anomaly)
(Berry)
Geographic Distribution (Mapping the Variance)
The “iterative smoothing” process is similar to slapping a big chunk of
modeler’s clay over the “data spikes,” then taking a knife and cutting away
the excess to leave a continuous surface that encapsulates the
peaks and valleys implied in the original field samples
Numeric Distribution — Average, Standard Deviation
Continuous Surface — Geographic Distribution
(Berry)
Spatial Interpolation (soil nutrient levels)
Spatial Interpolation maps the geographic distribution inherent in the data
Corn Field Phosphorous (P)
Data “Spikes”
IDW Surface
(Berry)
Comparing Spatial Interpolation Results
Comparison of the
IDW interpolated surface
to the
whole field average
shows large differences
in localized estimates
(-16.6 to 80.4 ppm)
Comparison of the
IDW interpolated surface
to the
Krig interpolated surface
shows small differences
in localized estimates
(-13.3 to 11.7 ppm)
(Berry)
Spatial Data Mining Techniques
Grid-Based Map Analysis (workshop topics)
Surface Modeling maps the spatial distribution and pattern of point data…
 Map Generalization— characterizes spatial trends (tilted plane)
 Spatial Interpolation— deriving spatial distributions (e.g. IDW, Krig)
 Other— roving windows and facets (e.g., density surface; tessellation)
Spatial Data Mining investigates the “numerical” relationships in mapped data…
 Descriptive— aggregate statistics (e.g. average, stdev, similarity; clustering)
 Predictive— relationships among maps (e.g., regression)
 Prescription— appropriate actions (e.g., decision rules; optimization)
Spatial Analysis investigates the “contextual” relationships in mapped data…
Reclassify— reassigns map values (position, value, size, shape, contiguity)
Overlay— map coincidence (point-by-point; region-wide; map-wide)
Distance— proximity and connection (movement; optimal paths; visibility)
Neighbors— roving windows (slope; aspect; diversity; anomaly)
(Berry)
Visualizing Spatial Relationships
Interpolated Spatial Distribution
Phosphorous (P)
What spatial relationships
do you see?
…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)
Clustering Maps for Data Zones
COMPUTERS can “see” detailed patterns in multiple map variables
…groups of “floating balls” in data space identify locations in the field
with similar data patterns– data zones
(Berry)
The Precision Ag Process (Fertility example)
Steps 1–3)
As a combine moves through a field 1) it uses GPS to
check its location then 2) checks the yield at that
location to 3) create a continuous map of the yield
variation every few feet (dependent map variable).
Prescription Map
On-the-Fly
Yield Map
Zone 3
“As-applied” maps
Intelligent Implements
Step 5)
Step 4)
Derived
Nutrient Maps
Zone 2
Zone 1
Variable Rate Application
The yield map 4) is analyzed in combination with
soil, terrain and other maps (independent map
variables) to derive a “Prescription Map” …
5) …that is used to adjust fertilization levels every
few feet in the field (action).
…more generally termed the
Spatial Data Mining Process (e.g., Geo-Business application)
(Berry)
Data Analysis Perspectives
(Data vs. Geographic Space)
Traditional Analysis
Map Analysis
(Data Space — Non-spatial Statistics)
(Geographic Space — Spatial Statistics)
Field Data
Standard Normal Curve
fit to the data
Spatially
Interpolated data
Central Tendency
Typical
How Typical
22.0
28.2
Average = 22.0
StDev = 18.7
Discrete
Spatial Object
Continuous
Spatial Distribution
(Generalized)
(Detailed)
Identifies the Central Tendency
Maps the Variance
(Berry)
So Where Are We in Precision Ag?
Yield Mapping
…done deal for many crops
Soil Nutrient Mapping
Mgt Zone Mapping
…procedures need validation
…alternative approaches need study & validation
The Full Precision Farming Process
IF <condition> THEN <action>
…a fair piece to go
…based on spatial relationships
– Description (Where is What) …coming on line
– Prediction (Why and So What) …needs lots of work PA Nugget
– Prescription (Do What Where) …barely on the research radar
– Action (Precisely Here) …done deal for many farm inputs
(Berry)
Spatial Analysis Techniques
Grid-Based Map Analysis (workshop topics)
Surface Modeling maps the spatial distribution and pattern of point data…
 Map Generalization— characterizes spatial trends (tilted plane)
 Spatial Interpolation— deriving spatial distributions (e.g. IDW, Krig)
 Other— roving windows and facets (e.g., density surface; tessellation)
Spatial Data Mining investigates the “numerical” relationships in mapped data…
 Descriptive— aggregate statistics (e.g. average, stdev, similarity; clustering)
 Predictive— relationships among maps (e.g., regression)
 Prescription— appropriate actions (e.g., decision rules; optimization)
Spatial Analysis investigates the “contextual” relationships in mapped data…
Reclassify— reassigns map values (position, value, size, shape, contiguity)
Overlay— map coincidence (point-by-point; region-wide; map-wide)
Distance— proximity and connection (movement; optimal paths; visibility)
Neighbors— roving windows (slope; aspect; diversity; anomaly)
(Berry)
Micro Terrain Analysis (a simple erosion model)
Determining Erosion Potential: slope and flow classes are
combined into a single map identifying erosion potential
times 10 plus
renumber
Field
Elevation is
formed by
assigning an
elevation value
to each cell in an
analysis grid
(1cm Lidar)
(Berry)
Precision Conservation (compared to Precision Ag)
Precision Conservation
Precision Ag
(Farm, Watershed,… Focus)
(Individual Field Focus)
Wind Erosion
Chemicals
Soil
Erosion
Runoff
Terrain
Leaching
Leaching
Leaching
Soils
Yield
Potassium
3-dimensional
Interconnected Perspective
(Stewardship Focus)
CIR Image
2-dimensional
Isolated Perspective
(Production Focus)
(Berry)
Deriving Erosion Potential (regional scale)
Maps of surface flow confluence and slope are calculated by
considering relative elevation differences throughout a project area
(Berry)
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)
Cyclical Development (future directions)
Revisit Analytics
Future Directions
(2020s)
Multimedia Mapping
2D Planar
3D Solid
(X,Y Data)
(X,Y,Z Data)
Square
(4 sides)
Hexahedron
(6 squares)
Hexagon
(6 sides)
Dodecahedron
(12 pentagons)
(2000s)
Revisit Geo-reference
(2010s)
Contemporary GIS
Spatial dB Mgt (1980s)
Map Analysis
(1990s)
The Early Years
Mapping focus
Data/Structure focus
Analysis focus
Computer Mapping
(1970s)
Is GIS Technology Ahead of Science?
Five critical questions underlying Precision Agriculture…
Is the “scientific method” relevant in the datarich age of knowledge engineering?
1)
Is the “random thing” pertinent in deriving
mapped data?
2)
Are geographic distributions a natural
extension of numerical distributions?
3)
Can spatial dependencies within a map variable (spatial
autocorrelation) and among map variables (spatial correlation) be
modeled?
4)
How can “site-specific” analysis and on-farm studies contribute
to the scientific body of knowledge?
5)
(Berry)
Where To Go From Here…
www.innovativegis.com/basis/
Online References
Analyzing Precision Ag Data
…workbook with hands-on exercises
Textbook
Presentation handout
Workbook