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GIS in Natural Resources & Agriculture: Bridging Differences with Map Analysis & Modeling

This seminar explores how advanced map analysis and GIS modeling applications are bridging the differences between natural resources and agriculture. It covers topics such as mapping, spatial analysis, and spatial statistics in the context of both industries.

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GIS in Natural Resources & Agriculture: Bridging Differences with Map Analysis & Modeling

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  1. GIS in Natural Resources and Agriculture GIS Centroid Seminar Colorado State University — October 17, 2014 Premise: While Natural Resources and Agriculture have significant differences in their respective motivations, goals, decision environments, and technological approaches, advanced Map Analysis and GIS Modelingapplications are bridging these differences. Premise: While Natural Resources and Agriculture have significant differences in their respective motivations, goals, decision environments, and technological approaches, advanced Map Analysis and GIS Modelingapplications are bridging these differences. This PowerPoint with notes and online links to further reading is posted at www.innovativegis.com/basis/Present/CentroidCSU2014/ Presented byJoseph K. Berry Principal, Berry & Associates // Spatial Information Systems Adjunct Faculty in Geosciences, Department of Geography, University of Denver Adjunct Faculty in Natural Resources, Warner College of Natural Resources, Colorado State UniversityEmail: jberry@innovativegis.com— Website: www.innovativegis.com/basis

  2. Mapping vs. Analyzing (Processing Mapped Data …review from “Future Directions” seminar) • …GISis a Technological Tool involving — • Mappingthat creates a spatial representation of an area • Displaythat generates visual renderings of a mapped area • Geo-querythat searches for map locations having a specified classification, condition or characteristic • …and an Analytical Tool involving — • Spatial Mathematics that applies scalar mathematical formulae to account for geometric positioning, scaling, measurement and transformations of mapped data • Spatial Analysis that investigates the contextual relationships within and among mapped data layers • Spatial Statistics that investigates the numerical relationships within and among mapped data layers “Map” “Analyze” Geographic Information Systems (map and analyze) (Descriptive Mapping) (Prescriptive Modeling) Global Positioning System (locate and navigate) Remote Sensing (measure and classify) GPS/GIS/RS (Biotechnology) (Nanotechnology) (Berry)

  3. A Mathematical Structure for Map Analysis/Modeling (…review from “Future Directions” seminar) GeotechnologyRS – GIS – GPS Technological Tool Analytical Tool (Continuous, Map Surfaces) Map Analysis/Modeling Mapping/Geo-Query(Discrete, Spatial Objects) Geo-registered Analysis Frame Map Stack  Matrix of Numbers “Map-ematics” Maps as Data, not Pictures Vector & Raster — Aggregated & Disaggregated Qualitative &Quantitative …organized set of numbers Grid-based Map Analysis Toolbox Spatial Analysis Operations Spatial Statistics Operations SpatialSTEM A Map-ematical Framework Traditional math/stat procedures can be extended into geographic space to support Quantitative Analysis of Mapped Data “…thinking analytically with maps” ArcGIS Spatial Analyst operations …over 170 individual “tools” www.innovativegis.com/basis/BeyondMappingSeries/, Book IV, Topic 9 for more discussion (Berry)

  4. Comparing Natural Resources and Agriculture (a GIS perspective) vs. Analytical Tool(Prescriptive “Why, So What and What if”) “Technical Tool” (Descriptive “Where is What”) Geo-registered Analysis Frame Map Analysis/Modeling (ContinuousMap Surfaces) Mapping/Geo-Query (Discrete Spatial Objects) Map Stack (geo-registered)  Matrix of Numbers …organized set of numbers Spatial Analysis Spatial Statistics Spatial Statisticsseeks to map the variation in a data set instead of focusing on a single typical response (central tendency), thereby providing a Statistical Frameworkfor investigating the NumericalSpatial Relationships within and among grid map layers Spatial Analysisextends the basic set of discrete map features (points, lines and polygons) to map surfaces that represent continuous geographic space (matrix), thereby providing a Mathematical Frameworkfor investigating ContextualSpatial Relationships within and among grid map layers Statistical Framework Mathematical Framework Natural Resources Mapping/Geo-query Terrain Analysis Variable-width Buffers Emergency Response Visual Exposure Shape/Patterns Consensus Building : Agriculture Navigation Yield Mapping Nutrient Surfaces Prescription Map Spatial T-test Clustering Regression : Relative Positioning within map variables Spatial Coincidence among map variables (Berry)

  5. Spatial Analysis Operations(Math Examples …review from “Future Directions” seminar) TheSpatial Derivativeidentifies the localized inclination (slope) and orientation (aspect) at every grid cell on a map surface. Spatial Analyst commands Slope and Aspect. Advanced Grid Mathapplies mathematical operations (add, subtract, multiply, divide, power, log, cosine, Boolean AND, Bitwise AND, etc.). Spatial Analyst commands Math and Map Algebra toolsets. TheSpatial Integralcalculates the volume (or other statistical summary) for an area. Spatial AnalystZonal Statistics commands. Video of “Future Directions in Map Analysis and Modeling” seminar can be viewed at https://www.youtube.com/watch?v=YA-mGpc20vc (Berry)

  6. Spatial Analysis Operations(Distance Examples …review from “Future Directions” seminar) Distance, Proximityand MovementDistance identifies “shortest straight line between two points”; Proximity relaxes 2P (S, SL, 2P) Movement relaxes SL (S, SL, 2P) considering intervening absolute and relative barriers. Spatial Analyst commands Euclidean Distance and Cost Distance. Optimal Path identifies the “shortest not-necessary-straight route”. Spatial Analyst command Cost Path. Visual Connectivityidentifies cells visually connected to an observer location (Viewshed) or the number of cells (Visual Exposure). Spatial Analyst command Viewshed. Video of “Future Directions in Map Analysis and Modeling” seminar can be viewed at https://www.youtube.com/watch?v=YA-mGpc20vc (Berry)

  7. Spatial Analysis Operations(Travel-time Surface backcountry emergency response) Movement …around and through absolute and relative barriers (click) …animated time steps in construction of a Travel-time Surface Least Cost Path(optimal movement) Travel-time Surface(accumulated movement) (Berry)

  8. Wildfire Risk/Behavior Modeling(Example of an advanced NR application) Wildfire Risk Modeling …WildfireRisk integrates numerous map layers such as weather factors, historical fire occurrence, surface and canopy fuels, terrain, and suppression effectiveness. Economic Impact of wildfire is based on probability/intensity of a wildfire (Risk) times assessor data (Value). Risk Wildfire Risk Value Rebuild Value Risk times $Value = $Exposure Wildfire Behavior Modeling The consequences of wildfires have never been greater as more people move into wildfire-prone areas. There is an increasing need forwildfire risk assessment, fuel treatments, mitigation planning, prevention awareness, wildfire behavior modeling, real-time suppression response and recovery preparedness to reduce risk and impacts to communities and sensitive areas. Fire ignites and moves SW …analysis of Wildfire Spread and Behavior, integrates current weather, fuel characteristics, and topography. Simulation results are in real time, providing capabilities to adjust simulations with observed data and proposed suppression activities. After Scott, Pyrologix; Buckley and Ramirez, Tecnosylva (Berry)

  9. Comparing Natural Resources and Agriculture (a GIS perspective)

  10. Spatial Statistics (Linking Data Space with Geographic Space …review from “Future Directions” seminar) Traditional Statisticsfits a Standard Normal Curve (2D density function) to identify the typical value in a data set (Mean) and its typical variation (Standard Deviation) in abstract data space. Surface Modelinguses Spatial Interpolation to fit a continuous surface (3D density function) that maps the spatial distribution (variation) in geographic space. Spatial AnalystIDW, Kriging, Spline and Natural Neighbors commands. Unusually High Locations are identified as locations greater than the Mean plus one Standard Deviation (upper tail). Spatial AnalystReclass command. Video of “Future Directions in Map Analysis and Modeling” seminar can be viewed at https://www.youtube.com/watch?v=YA-mGpc20vc (Berry)

  11. Spatial Statistics Operations(Data Mining Examples …review from “Future Directions” seminar) Data Spaceplots pairs of spatially coincident data values (2D scatter plot) in abstract data space to identify data pairing relationships (e.g., low-low, …, high-high) but can be expanded to tuples in n-dimensional space. Clusteringuses the Pythagorean Theorem in calculating Data Distance between data parings to quantitatively establish Clusters (groupings with minimal inter-cluster distances). Spatial AnalystIso Cluster command. ACorrelation Map is generated by repetitive evaluation of the Correlation Equation within a Roving Window of nearby data pairings. Spatial Analyst dropped Correlation AML command. 2D Video of “Future Directions in Map Analysis and Modeling” seminar can be viewed at https://www.youtube.com/watch?v=YA-mGpc20vc (Berry)

  12. Interpolated Spatial Distribution of soil nutrient concentrations Phosphorous (P) Visualizing Spatial Relationships Continuous Grid-Map Surfaces (Data Layers) Multivariate Coincidence 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 only “see” broad Generalized Patterns in a single map variable (Map Stack) (Berry)

  13. Clustering Maps for Data Zones …but computers can “see” detailed numeric patterns in multiple map variables using Data Space Note: can be expanded to N-dimensional Data Space Data Distance = SQRT (a2 + b2 + c2 + …) Geographic Space Data Distance = SQRT (a2 + b2 + c2) 3D Data Space Distance calculated using the Pythagorean Theorem …groups of relatively close “floating balls” in data space identify locations in the field with similar data patterns– Data Zones(Data Clusters) …the IsoData algorithm minimizes Intra-Cluster distances (within a cluster— similar) while at the same time maximizing Inter-Cluster distances (between clusters— different) (Berry)

  14. Prescription Map Step 6) Derived Soil Nutrient Maps Zone 3 Zone 2 Variable Rate Application Zone 1 The Precision Ag Process As a combine moves through a field it… 1) uses GPS to check its locationevery second then 2) records the yield monitor valueat that location to Steps 1–3) 3) create a continuous Yield Map surface identifying the variation in crop yield every few feet throughout the field (dependent map variable). Step 5) “As-applied” maps On-the-Fly Yield Map Intelligent Implements 4) …soil samplesare interpolated for continuous Nutrient Map surfaces. Step 4) 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 levelsapplied every few feet in the field (If <condition> then <action>). …more generally termed the Spatial Data Mining Process(e.g., Geo-Business application) (Berry)

  15. Precision Conservation (Landscape Focus) Precision Ag (Individual Field Focus) Wind Erosion Chemicals 2-dimensional SoilErosion Terrain Runoff Leaching Soils Leaching Leaching Yield Potassium 3-dimensional CIR Image Interconnected Perspective Precision Conservation(compared to Precision Ag) …intertwined disciplines Coincidence Isolated Perspective (Production Emphasis) (Stewardship Emphasis) https://www.sensorsandsystems.com/article/features/5662-precision-agricultures-success-yields-precision-conservation.html (Berry)

  16. Deriving Erosion Potential(Common Ground Example …terrain modeling) Simple Buffer – fixed geographic reach 33 = Heavy, Steep= High : 11 = Light, Gentle= Low Erosion Potentialfn(S,F) Slopemap Erosion_potenti Erosion_potential Slope_classes Flowmap Derived Maps of Slope and surface Flow Erosion Buffers Flow_classes Streams 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” Simpleapproach tor protecting the stream But all buffer-feet are not the same… Need to reach farther under some conditions and not as far under others— common sense? Variable-width Buffer (Landscape Level) On/Off-Field Flows (Field Level) Surface Flowsfn(S,F) The combined map identifies where surface flows likely move/deposit materials (e.g., organic, fine particles, chemicals) within a field. Locations with a lot of movement at the edge of a field are identified as potential problem areas. Elevation Slopemap Flowmap Surface_flows (Berry)

  17. Water Conservation Modeling (Conservation = “wise use”) “First in time, First in Right” Water Rights Historic Crop Water Allocation Alternative Water Budget Crop Water Allocation Crops City Farm Purchase Water Rights Sell or Lease Drought Monitor Farm Income City Water March 2014 “Buy andDry” “Win-Win-Win” To River To River Temporary Monitored Transfers Abnormally Dry Exceptional Drought Farmland Farmland Wireless Connectivity Weather Station Landsat Satellite Images Off-Farm Data Collection Solar Irradiance Evapotranspiration Monitors Weather Station Auto-Flume Adjustment Fully Irrigated Tree Crop under Drip Irrigation Soil Moisture Probes Deficit Irrigated Crop under Center Pivot Sprinkler Low Altitude Aerial Photos 100th Meridian Fallowed Field On-Farm Instrumentation Management Actions New/Expanded Data Collection /Instrumentation: Remote Sensing Weather/Climate Water Flow Evapotranspiration Soil Moisture Fully Irrigated Vegetables under Drip Irrigation Full Irrigation Deficit Irrigation www.regenmg.com/Home.aspx Sustainable Water and Innovative Irrigation Management (SWIIM) (Berry)

  18. 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 Toolsutilizing mapping, geo-query and display for NR and GPS navigation, implement control and data collection for Ag. However… • Ag’s analytical applications currently tend to focus on stewardship and economicsat the individual field level utilizing Spatial Statistics operations (numerical context; spatial coincidence) for analysis of spatial relationships among factors affecting crop production and management actions. • NR’s analytical applications currently tend to focus more on ecology and environmental impacts • at the landscape level utilizing Spatial Analysisoperations (geographical context; relative position) for analysis of spatial relationships among factors affecting 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 movementsof soil and water (Spatial Analysis). (Berry)

  19. So Where to Head from Here? Online Materials (www.innovativegis.com/Basis/Courses/SpatialSTEM/) ) Website (www.innovativegis.com) 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/CentroidCSU2014/ 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 jberry@innovativegis.com

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