Presentation by Joseph K. Berry W.M. Keck Scholar in Geosciences, University of Denver Special Faculty in Natural Resources, Colorado State University Principal, Berry & Associates // Spatial Information Systems 2000 S. College Ave, Suite 300, Fort Collins, CO Phone: (970) Website at Geotechnology in Transition: Evolution, Current Practice, Trends and Future Directions that are Moving Us Beyond Mapping GIS Seminar – Colorado State University – April 11, 2011 Understanding… 1) What GIS IS …and Isn’t, 2) Nature of Grid-based Mapped Data, 3) Grid-based Map Analysis and Modeling, 4) Where GIS is Headed, and 5) Where Might You be Headed in GIS

(Nanotechnology) Geotechnology (Biotechnology) GPS/GIS/RS Modeling involves analysis of spatial relationships and patterns (numerical analysis) PrescriptiveModeling Mapping involves precise placement (delineation) of physical features (graphical inventory) DescriptiveMapping Geotechnology is one of the three "mega technologies" for the 21st century and promises to forever change how we conceptualize, utilize and visualize spatial relationships in scientific research and commercial applications (U.S. Department of Labor) Why So What and What Global Positioning System (location and navigation) Geographic Information Systems (map and analyze) Where is What (Berry) Remote Sensing (measure and classify) The Spatial Triad

Historical Setting and GIS Evolution Spatial Database Management links computer mapping techniques with traditional database capabilities (80s) Multimedia Mapping full integration of GIS, Internet and visualization technologies (00s) Map Analysis representation of relationships within and among mapped data (90s) Computer Mapping automates the cartographic process (70s) Geotechnology (GPS, GIS, RS) DIGITAL Manual Mapping for 8,000 years ANALOG Focus of this presentation (Berry)

Desktop Mapping Framework (Vector, Discrete) Click on… Select Theme Zoom Pan InfoToolThemeTable Distance QueryBuilder …identify tall aspen stands Big …over 400,000m 2 (40ha)? : Object ID X,YX,YX,Y : Feature Species etc. Feature Species etc. : : : : Object ID Aw : : : :SpatialTableAttributeTable Discrete, irregular map features (objects) Points, Lines and Areas (Berry)

Map Analysis Framework (Raster, Continuous) Click on… Zoom Pan Rotate Display ShadingManager Continuous, regular grid cells (objects) Points, Lines, Areas and Surfaces : --, --, --, --, --, 2438, --, --, --, --, --, : Grid Table GridAnalysis …calculate a slope map and drape on the elevation surface Map Stack (Berry)

Traditional Statistics Mean, StDev (Normal Curve) Mean, StDev (Normal Curve) Central Tendency Central Tendency Typical Response (scalar) Typical Response (scalar) Minimum= 5.4 ppm Maximum= ppm Mean= 22.4 ppm StDEV= 15.5 Spatial Statistics Map of Variance (gradient) Map of Variance (gradient) Spatial Distribution Spatial Distribution Numerical Spatial Relationships Numerical Spatial Relationships Spatial Distribution (Surface) Mapped Data Analysis Evolution (Revolution) Traditional GIS Points, Lines, Polygons Points, Lines, Polygons Discrete Objects Discrete Objects Mapping and Geo-query Mapping and Geo-query Forest Inventory Map Spatial Analysis Cells, Surfaces Cells, Surfaces Continuous Geographic Space Continuous Geographic Space Contextual Spatial Relationships Contextual Spatial Relationships Elevation(Surface) (Berry)

Elevation Surface (Berry) Calculating Slope and Flow (map analysis) Inclination of a fitted plane to a location and its eight surrounding elevation values (Neighbors) Total number of the steepest downhill paths flowing into each location Total number of the steepest downhill paths flowing into each location (Distance) Slope (47,64) = 33.23% Slope map draped on Elevation Slope map Flow (28,46) = 451 Paths Flow map draped on Elevation Flow map (Berry)

Erosion Potential Flowmap Slopemap Deriving Erosion Potential & Buffers Erosion_potentialFlow/Slope Slope_classes Flow_classes Reclassify Overlay Reclassify Protective Buffers Simple Buffer StreamsSimple Buffer Erosion_potential But all buffer-feet are not the same… (slope/flow Erosion_potential) …reach farther in areas of high erosion potential (Berry)

Erosion_potential Streams Erosion Buffers Distance 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” Calculating Effective Distance (variable-width buffers) Effective Buffers (digital slide show VBuff) VBuff Effective Erosion Distance CloseFar Heavy/Steep (far from stream) Light/Gentle (close) Simple Buffer (Berry)

Traditional Statistics Mean, StDev (Normal Curve) Mean, StDev (Normal Curve) Central Tendency Central Tendency Typical Response (scalar) Typical Response (scalar) Minimum= 5.4 ppm Maximum= ppm Mean= 22.4 ppm StDEV= 15.5 Spatial Statistics Map of Variance (gradient) Map of Variance (gradient) Spatial Distribution Spatial Distribution Numerical Spatial Relationships Numerical Spatial Relationships Spatial Distribution (Surface) Mapped Data Analysis Evolution (Revolution) Traditional GIS Points, Lines, Polygons Points, Lines, Polygons Discrete Objects Discrete Objects Mapping and Geo-query Mapping and Geo-query Forest Inventory Map Spatial Analysis Cells, Surfaces Cells, Surfaces Continuous Geographic Space Continuous Geographic Space Contextual Spatial Relationships Contextual Spatial Relationships EffectiveDistance(Surface) (Berry)

GeoExploration vs. GeoScience Continuous Spatial Distribution Discrete Spatial Object Map Analysis Geographic Space Map Analysis map-ematically relates patterns within and among continuous spatial distributions (Map Surfaces) — spatial analysis and statistics (GeoScience) (Geographic Distribution) Average = 22.0 StDev = 18.7 Desktop Mapping Data Space Field Data Standard Normal Curve Desktop Mapping graphically links generalized statistics to discrete spatial objects (Points, Lines, Polygons) — non-spatial analysis (GeoExploration) X, Y, Value Point Sampled Data (Numeric Distribution) “Maps are numbers first, pictures later” 22.0 Spatially Generalized Spatially Detailed 40.7 …not a problem Adjacent Parcels High Pocket Discovery of sub-area… (See Beyond Mapping III, “Epilog”,, ) (See Beyond Mapping III, “Epilog”, Technical and Cultural Shifts in the GIS Paradigm, )(Berry)

Spatial Interpolation (Smoothing the Variability) The iterative smoothing process is similar to slapping a big chunk of modeler’s clay over the “data spikes”… …repeated smoothing slowly “erodes” the data surface to a flat plane = = AVERAGE (digital slide show SStat2) SStat2 …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 (Berry)

Visualizing Spatial Relationships What spatial relationships do you SEE? …do relatively high levels of P often occur with high levels of K and N? …how often? …where? Phosphorous (P) Geographic Distribution Multivariate Analysis— each map layer is a Multivariate Analysis— each map layer is a continuous variable with all of the math/stat continuous variable with all of the math/stat “rights, privileges and responsibilities” therewith …simply “spatially organized “ sets of numbers (matrix) “rights, privileges and responsibilities” therewith …simply “spatially organized “ sets of numbers (matrix) “Maps are numbers first, pictures later” (Berry)

Calculating Data Distance …an n-dimensional plot depicts the multivariate distribution— the distance between points determines the relative similarity in data patterns PythagoreanTheorem 2D Data Space: Dist = SQRT (a 2 + b 2 ) Dist = SQRT (a 2 + b 2 ) 3D Data Space: Dist = SQRT (a 2 + b 2 + c 2 ) Dist = SQRT (a 2 + b 2 + c 2 ) …expandable to N-space …this response pattern (high, high, medium) is the least similar point as it has the largest data distance from the comparison point (low, low, medium) (See Beyond Mapping III, “Topic 16”, Characterizing Spatial Patterns and Relationships, (See Beyond Mapping III, “Topic 16”, Characterizing Spatial Patterns and Relationships,

Clustering Maps for Data Zones Groups of “floating balls” in data space identify locations in the field with similar data patterns – data zones or Clusters …data distances are minimized within a group (intra-cluster distance) and maximized between groups (inter-cluster distance) using an optimization procedure (See Beyond Mapping III, “Topic 7”, Linking Data Space and Geographic Space, (See Beyond Mapping III, “Topic 7”, Linking Data Space and Geographic Space, (See Beyond Mapping III, “Topic 16”, Characterizing Spatial Patterns and Relationships, (See Beyond Mapping III, “Topic 16”, Characterizing Spatial Patterns and Relationships,

The Precision Ag Process (Fertility example) As a combine moves through a field it 1) uses GPS to check its location then 2) checks the yield at that location to 3) create a continuous map of the 2) checks the yield at that location to 3) create a continuous map of the yield variation every few feet. This map is yield variation every few feet. This map is 4) combined with soil, terrain and other maps to 4) combined with soil, terrain and other maps to derive 5) a “Prescription Map” that is used to derive 5) a “Prescription Map” that is used to 6) adjust fertilization levels every few feet 6) adjust fertilization levels every few feet in the field (variable rate application). in the field (variable rate application). Farm dB Step 4) Map Analysis On-the-Fly Yield Map Steps 1) – 3) Step 6) Variable Rate Application Cyber-Farmer, Circa 1992 Prescription Map Step 5) (See Beyond Mapping III, “Topic 16”, Characterizing Spatial Patterns and Relationships, (See Beyond Mapping III, “Topic 16”, Characterizing Spatial Patterns and Relationships,

Map Analysis Evolution (four-square summary) Traditional GIS Points, Lines, Polygons Points, Lines, Polygons Discrete Objects Discrete Objects Mapping and Geo-query Mapping and Geo-query Forest Inventory Map Spatial Analysis Cells, Surfaces Cells, Surfaces Continuous Geographic Space Continuous Geographic Space Contextual Spatial Relationships Contextual Spatial Relationships StoreTravel-Time(Surface) Traditional Statistics Mean, StDev (Normal Curve) Mean, StDev (Normal Curve) Central Tendency Central Tendency Typical Response (scalar) Typical Response (scalar) Minimum= 5.4 ppm Maximum= ppm Mean= 22.4 ppm StDEV= 15.5 Spatial Statistics Map of Variance (gradient) Map of Variance (gradient) Spatial Distribution Spatial Distribution Numerical Spatial Relationships Numerical Spatial Relationships Spatial Distribution (Surface) (Berry)

A Peek at the Bleeding Edge (2010 and beyond) Multimedia Mapping (IV -2000s) Revisit Analytics (VI -2020s) GIS Modeling (III -1990s) Computer Mapping (Decade I -1970s) Spatial dB Mgt (II -1980s) The Early Years Contemporary GIS Future Directions Revisit Geo-reference (V -2010s) Mapping focus Data/Structure focus Analysis focus …but those who live by the Crystal Ball are bound to eat ground glass Evan Vlachos (Berry)

Dominant GIS Forces (three game changers) #2 Universal Spatial Key — use of the new referencing system to automatically join all databases by serving as a “spatially-enabled” Universal Key (Implicit Spatial Topology) #2 Universal Spatial Key — use of the new referencing system to automatically join all databases by serving as a “spatially-enabled” Universal Key (Implicit Spatial Topology) …sort of like a three- dimensional UTM grid cell (1 m 2 ) #1 Alternative Geographic Referencing (3D GIS) — our current “rectangular-based” coordinate system will be replaced by a 3-dimensional coordinate system of columns (X), rows (Y), and verticals (Z) defining an imaginary matrix of grid elements #1 Alternative Geographic Referencing (3D GIS) — our current “rectangular-based” coordinate system will be replaced by a 3-dimensional coordinate system of columns (X), rows (Y), and verticals (Z) defining an imaginary matrix of grid elements #3 Boutique to Big Box — continued movement of GIS from a “boutique discipline” to increased mainstream use and subsequent redefinition of What GIS Is and its Industry Leaders #3 Boutique to Big Box — continued movement of GIS from a “boutique discipline” to increased mainstream use and subsequent redefinition of What GIS Is and its Industry Leaders Today Tomorrow CAD, dBase and Visualization Industries …etc. GIS Industry (Berry)

Consistent distances and adjacency to surrounding grid elements Consistent distances and adjacency to surrounding grid elements Inconsistent distances and adjacency to surrounding grid elements (Orthogonal and Diagonal) Inconsistent distances and adjacency to surrounding grid elements (Orthogonal and Diagonal) Tightly Clustered Groupings Continuous Nested Grid Elements Cubic Grid (26 facets) Square Grid (8 facets) Hexagonal Grid (6 facets) Hexagon Dodecahedral Grid (12 facets) Dodecahedral #1 Alternative Geographic Referencing 2D Grid Element (Planimetric) Square 3D Grid Element (Volumetric) Cube Cartesian Coordinate System Square Cube (Berry)

…that form a complex Address Code (x,y,z) for spatial reference of any record in a database that can be used to join any other spatially referenced table– Spatially-enabled Universal Key #2 Universal Spatial Key (grid space as key) Entire 3D volume containing the earth is pre-partitioned into small Grid Elements using basic geometry equations… 100km, 10km, …1m UTM gridlines WHERE is WHAT Planimetric Volumetric (Berry)

#3 Boutique to Big Box ScienceSystems SpecialistSolutions GIS …four main perspectives of the trailing “S” GISystems — At the birth of the discipline, the “S” unequivocally stood for the hardware, software and dataware with little or no reference to people or uses GISystems — At the birth of the discipline, the “S” unequivocally stood for the hardware, software and dataware with little or no reference to people or uses GISpecialists — The idea that the trailing “S” defines specialists took hold in the 1990s as the result of two major forces, uniqueness and utility GISpecialists — The idea that the trailing “S” defines specialists took hold in the 1990s as the result of two major forces, uniqueness and utility …etc. GIS Industry GIScience — recognition of a more in-depth discipline has evolved the “practitioner” role (what does it take to keep a GIS alive and how can it be used?) into a more “theoretical” role (how does GIS work, how could it be improved and what else could it do?) GIScience — recognition of a more in-depth discipline has evolved the “practitioner” role (what does it take to keep a GIS alive and how can it be used?) into a more “theoretical” role (how does GIS work, how could it be improved and what else could it do?) GISolutions — the new focus seems to be on entirely new GIS applications from iPhone crowdsourcing to Google Earth visualizations GISolutions — early GIS solutions focused on mapping and geo-query that primarily automated existing business practices; the new focus seems to be on entirely new GIS applications from iPhone crowdsourcing to Google Earth visualizations to advanced map-ematical models predicting wildfire behavior, customer propensity and optimal routing CAD, dBase and Visualization Industries …etc. (Berry)

Dominant Human Forces (three game changers) #1 The “-ists” and the “-ologists” — a continuing “Tool” versus “Science” dichotomy of perspective of what GIS is and isn’t #1 The “-ists” and the “-ologists” — a continuing “Tool” versus “Science” dichotomy of perspective of what GIS is and isn’t The “-ists” focus a GIS specialist’s command of the tools needed to display, query and process spatial data. The “-ologists,” focus on users (e.g., ecologists, sociologists, hydrologists, epidemiologists, etc.) who understand the science behind the spatial relationships. The “-ists” focus a GIS specialist’s command of the tools needed to display, query and process spatial data. The “-ologists,” focus on users (e.g., ecologists, sociologists, hydrologists, epidemiologists, etc.) who understand the science behind the spatial relationships. The Softer Side if GIS the data-centric perspective of the specialists (mapping and geo-query) dominated the analysis-centric needs of the managers, policy and decision makers (spatial reasoning and modeling) #2 The Softer Side if GIS — the data-centric perspective of the specialists (mapping and geo-query) dominated the analysis-centric needs of the managers, policy and decision makers (spatial reasoning and modeling) #3 Enlarging GIS Education — need to engage applied “domain expertise” in GIS education through outreach across campus that is as important (and quite possibly more important) than honing technical skills of core professionals #3 Enlarging GIS Education — need to engage applied “domain expertise” in GIS education through outreach across campus that is as important (and quite possibly more important) than honing technical skills of core professionals The “Bookends “ are currently driving GIS (Berry)

TechnologyExperts “-ists” DomainExperts “-ologists” Solution Space Together the “-ists” and the “-ologists” frame and develop the Solution for an application. …understand the “tools” that can be used to display, query and analyze spatial data Data and Information focus …understand the “science” behind spatial relationships that can be used for decision-making Knowledge and Wisdom focus The “-ists ” The “-ologists ” — and — #1 The “-ists” and the “-ologists” (Berry)

“Policy Makers” “Stakeholders” “Decision Makers” Decision Makers utilize the Solution under Stakeholder, Policy & Public auspices. TechnologyExperts “-ists” DomainExperts “-ologists” SolutionSpace Application Space Geotechnology’s Core #1 The “-ists” and the “-ologists” (a larger tent) (Berry)

Knowledge/Perceptions (interrelationships among relevant facts) Wisdom/Opinions and Values (actionable knowledge) Philosopher’s Progression of Understanding — Data (all facts) Information (facts within a context) … GeoExploration emphasizes tools for data access and visualization (general user) … GeoScience emphasizes tools for spatial reasoning and understanding of spatial patterns and relationships (application specialist) Mapping focus Analysis and Modeling focus #2 The Softer Side of GIS (Berry)

Future Directions:  Social Acceptability as 3 rd filter #2 The Softer Side of GIS (the NR experience) Podium Historically Ecosystem Sustainability and Economic Viability have dominated Natural Resources discussion, policy and management. But Social Acceptability has become the critical third filter needed for successful decision-making. Spatial Reasoning, Dialog and Consensus Building Increasing Social Science & Public Involvement 1970s2010s Inter-disciplinary Science Team Table Analysis of Data and Information (Berry)

GIS User Community Evolving and Enlarging GIS Community 1970s2010s #3 Enlarging GIS Education (historical evolution) (Berry)

Computer Programmer– …develops GIS tools; …mostly computer science (CS) skills with some experience in GIS Solutions Developer– …develops applications that link GIS to real-world problems; …mostly GIS/CS background with some discipline expertise Systems Manager– …develops and maintains spatial databases and connections within (LAN) and outside (Internet) the organization; …CS and GIS balance Data Provider– …develops GIS databases; …good skills in GPS and Remote Sensing with strong skills in GIS data formats and geodetic referencing GIS Specialist– …interacts with other GIS professionals and users to implement spatial solutions; …GIS with considerable discipline expertise GeneralUser– …applies GIS operations, techniques, procedures and models to address real world processes in support of decision- making; …strong discipline expertise with GIS awareness #3 Enlarging GIS Education (historical evolution) (Berry) The “Bookends “ are currently driving GIS

Where From Here? GIS Seminar – Colorado State University – April 11, 2011 GIS Seminar – Colorado State University – April 11, ) What GIS IS …and Isn’t 1) What GIS IS …and Isn’t 2) Nature of Grid-based Mapped Data 2) Nature of Grid-based Mapped Data 3) Grid-based Map Analysis and Modeling 3) Grid-based Map Analysis and Modeling 4) Where GIS is Headed 4) Where GIS is Headed 5) Where Might You be Headed in GIS 5) Where Might You be Headed in GIS Additional Information: A Brief History and Probable Future of Geotechnology, a white paper that distills several keynotes, presentations and papers, BASIS, Fort Collins, Colorado, July, J.K. Berry. An Analytical Framework for GIS Modeling, a white paper describing a conceptual framework for Map Analysis and Modeling, BASIS, Fort Collins, Colorado, October, J.K. Berry. Beyond Mapping III, an online book containing Introduction, 28 Chapters and Epilog as a compilation of the popular Beyond Mapping columns published in GeoWorld magazine from 1996 through present, BASIS, Fort Collins, Colorado, J.K. Berry. PowerPoint slide set is posted at Graduate level GIS Modeling course materials are posted at Joseph K. Berry — Website: (Berry)