Transcript Slide 1

GIS in Natural Resources and Agriculture
2014 Manitoba GIS User Group
Fall Conference | October 1, 2014 | Winnipeg, Manitoba, Canada
Premise: While Natural Resources and Production Agriculture have significant differences in
their respective motivations, goals, decision environments, technological approaches,
advanced Map Analysis and GIS Modeling applications are bridging these differences.
This PowerPoint with notes and online links to further reading is posted at
www.innovativegis.com/basis/Present/Manitoba2014/
Presented by
Joseph K. Berry
Adjunct Faculty in Geosciences, Department of Geography, University of Denver
Adjunct Faculty in Natural Resources, Warner College of Natural Resources, Colorado State University
Principal, Berry & Associates // Spatial Information Systems
Email: [email protected] — Website: www.innovativegis.com/basis
Comparing Natural Resources and Agriculture (a GIS perspective)
“Technical Tool” (Descriptive “Where is What”) vs.
Analytical Tool (Prescriptive “Why, So What and What if”)
Grid Layer
Map Stack
Spatial Analysis extends the basic set of discrete map
Spatial Statistics seeks to map the variation in a data
features (points, lines and polygons) to map surfaces that
represent continuous geographic space (matrix), thereby
providing a Mathematical Framework for investigating
set instead of focusing on a single typical response
(central tendency), thereby providing a
Statistical Framework for investigating the
Contextual Spatial Relationships
Numerical Spatial Relationships
within and among grid map layers
within and among grid map layers
Natural Resources
Agriculture
Mapping/Geo-query
Terrain Analysis
Variable-width Buffers
Emergency Response
Visual Exposure
Shape/Patterns
Consensus Building
:
Navigation
Yield Mapping
Nutrient Surfaces
Prescription Map
Spatial T-test
Clustering
Regression
:
Relative
Positioning
Spatial
Coincidence
within map variables
among map variables
(Berry)
Calculating Slope and Flow (NR example— terrain analysis)
Inclination of a fitted
plane to a location and
its eight surrounding
elevation values
Slope (47,64) = 33.23%
Slope map draped
on Elevation
Slopemap
Elevation Surface
Flow (28,46) = 451 Paths
Total number of the steepest
downhill paths flowing into each
location
Flow map draped
on Elevation
Flow map
(Berry)
Deriving Erosion Potential (terrain modeling)
Erosion Potential
Slopemap
Slope_classes
Flowmap
Flow_classes
Flow/Slope
Erosion_potential
Individual Map
Analysis Operations
But all buffer-feet are not the same…
Need to reach farther under some conditions
and not as far under others— common sense?
Simple approach to
protect the stream
Simple Buffer – fixed geographic reach
(Berry)
Calculating Effective Distance (variable-width buffer)
Distance away from the streams is a function of the
erosion potential (Flow/Slope Class) with intervening
heavy flow and steep slopes computed as effectively
closer than simple distance— as the crow walks”
Erosion_potential
Erosion Buffers
Effective Erosion Distance
Streams
Close
Far
Simple Buffer
Heavy/Steep
(far from stream)
Light/Gentle
(close)
Effective Distance
Variable-width Buffer
(Berry)
Comparing Natural Resources and Agriculture (a GIS perspective)
“Technical Tool” (Descriptive “Where is What”) vs.
Analytical Tool (Prescriptive “Why, So What and What if”)
Grid Layer
Map Stack
Spatial Analysis extends the basic set of discrete map
Spatial Statistics seeks to map the variation in a data
features (points, lines and polygons) to map surfaces that
represent continuous geographic space (matrix), thereby
providing a Mathematical Framework for investigating
set instead of focusing on a single typical response
(central tendency), thereby providing a
Statistical Framework for investigating the
Contextual Spatial Relationships
Numerical Spatial Relationships
within and among grid map layers
within and among grid map layers
(Berry)
Natural Resources
Agriculture
Mapping/Geo-query
Terrain Analysis
Variable-width Buffers
Emergency Response
Visual Exposure
Shape/Patterns
Consensus Building
:
Navigation
Yield Mapping
Nutrient Surfaces
Prescription Map
Spatial T-test
Clustering
Regression
:
Relative
Positioning
Spatial
Coincidence
within map variables
among map variables
Spatial Interpolation (Ag example— fertilization prescription map)
Spatial Interpolation maps the geographic distribution inherent in the data
Corn Field Phosphorous (P)
Data “Spikes”
IDW Surface
(Berry)
The Precision Ag Process
As a combine moves through a field it…
1) uses GPS to check its location every second then
Steps 1–3)
2) records the yield monitor value at that location to
3) create a continuous Yield Map surface identifying the variation in crop
yield every few feet throughout the field (dependent map variable).
Step 5) Prescription Map
On-the-Fly
“As-applied” maps
Yield Map
Zone 3
4) …soil samples are interpolated for
continuous Nutrient Map surfaces.
Intelligent Implements
Step 6)
Step 4)
Derived Soil
Nutrient Maps
Zone 2
Zone 1
Variable Rate Application
5) The yield map is analyzed in combination
with soil nutrient maps, terrain and other mapped factors
(independent map variables)
to derive a Prescription Map…
6) …that is used to adjust fertilization levels applied every few
feet in the field (If <condition> then <action>).
…more generally termed the
Spatial Data Mining Process
(e.g., Geo-Business application)
(Berry)
Precision Conservation (compared to Precision Ag)
…related
disciplines
Precision Conservation
(Landscape Focus)
Precision Ag
Wind Erosion
(Individual Field Focus)
Chemicals
2-dimensional
Soil
Erosion
Runoff
Terrain
Leaching
Leaching
Leaching
Soils
Yield
3-dimensional
Potassium
CIR Image
Isolated Perspective
(Production Focus)
Interconnected Perspective
(Stewardship Focus)
https://www.sensorsandsystems.com/article/features/5662-precision-agricultures-success-yields-precision-conservation.html
(Berry)
Upshot (NR compared to Ag from a GIS perspective)
Historical Setting:
NR was an early adopter of geospatial technology as a direct outgrowth of its long and extensive
mapping/inventory legacy for automated cartography and geoquery of an extended resource base. On the
other hand, Ag had little use for mapping and spatially detailed inventories.
Contemporary GIS Applications and Approaches:
The bulk of GIS applications for both NR and Ag applications involve Technological Tools utilizing
mapping, geo-query and display for NR and GPS navigation, implement control and data collection for Ag.
— Ag’s analytical applications tend to be tightly focused on stewardship and economics at the
individual field level utilizing Spatial Statistics operations (numerical context; spatial coincidence) for
analysis of the spatial relationships among factors affecting crop production and management actions.
— NR’s analytical applications tend to focus more on ecology and environmental impacts at the
landscape level utilizing Spatial Analysis operations (geographical context; relative position) for
analysis of the spatial relationships among factors ecosystem conditions and management actions.
Future Directions:
With increasing understanding of map analysis and GIS
modeling capabilities and spatial reasoning skills both
disciplines will be Pushed/Pulled closer together…
― NR will incorporate more quantitative analysis of
mapped data (Spatial Statistics) in its science, and
— Ag will adopt a more ecological perspective
focusing on the cycles and movements of soil and
water (Spatial Analysis).
(Berry)
So Where to Head from Here?
Website (www.innovativegis.com)
Online Materials
(www.innovativegis.com/Basis/Courses/SpatialSTEM/)
For more papers and presentations
on Geotechnology
)
www.innovativegis.com
This PowerPoint with notes and online links to further reading is posted at
www.innovativegis.com/basis/Present/Manitoba2014/
Beyond Mapping Compilation Series
…nearly 1000 pages and more than 750 figures
in the Series provide a comprehensive and
longitudinal perspective of the underlying
concepts, considerations, issues and
evolutionary development of modern
geotechnology (RS, GIS, GPS).
eMail Contact
Joseph K. Berry
[email protected]