#### Transcript Map Analysis

GIS Modeling Week 1 — Overview GEOG 3110 –University of Denver Presented by Joseph K. Berry W. M. Keck Scholar, Department of Geography, University of Denver Course overview; GIS mapping, management and modeling; Discrete (map objects) vs. continuous (map surfaces); Linking data and geographic distributions; Framework for map-ematical processing Geotechnology (Nanotechnology) (Biotechnology) 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) Geographic Information Systems (map and analyze) Global Positioning System (location and navigation) Remote Sensing (measure and classify) GPS/GIS/RS The Spatial Triad Mapping involves precise placement (delineation) of physical features (graphical inventory) Where Descriptive Mapping Why is What Prescriptive Modeling So What and What If… Modeling involves analysis of spatial relationships and patterns (numerical analysis) (Berry) Historical Setting and GIS Evolution Manual Mapping for 8,000+ years We have been mapping for thousands of years with the primary of navigation through unfamiliar terrain and seas, with emphasis on precise placement of physical features. …but the last four decades have radically changed the very nature of maps and how they are used— Computer Mapping …automates the cartographic process (70s) Where Spatial Database Management …links computer mapping with database capabilities (80s) Where is What … GIS Modeling course Map Analysis …representation of relationships within and among mapped data (90s) Why, So What and What If… Multimedia Mapping …full integration of GIS, Internet and visualization technologies (00s) Wow!!! …did you see that (Berry) Descriptive Mapping Framework (Vector, Discrete) Click on… Select Theme Zoom Pan Info Tool Theme Table Distance Spatial Table : Object ID X,Y X,Y X,Y : Query Builder …identify tall aspen stands Attribute Table Feature : Object ID : Big …over 400,000m2 (40ha)? Species : Aw : etc. Discrete, irregular map features (objects) Points, Lines and Areas (Berry) Manual GIS (Geo-query circa 1950) 1) Spatial Table and written description/data in the center Hole 15 Notch 14 #11 Index Card with series of numbered holes around the edge 13 12 10 2) a particular characteristic (attribute), such as #11 notch = Douglas fir timber type 3) 9 8 Special Punch was used to notch-out the hole assigned to 7 (spatial objects) Where Pass a long Needle through the stack of cards and lift… Hole 6 Cards pulled up… 5 … DO NOT have characteristic 4 3 2 1 Query Tray holds all of the index cards for a project area Notch What Data Table (attribute records) Cards falling down… 4) … HAVE characteristic Repeat using the search results sub-set for more characteristics 5) Card ID# identifies the timber stand polygons from the search and the appropriate locations are shaded— …a “Database-entry Geo-query” (Berry) Map Analysis Framework (Raster, Continuous) Click on… Zoom Pan Rotate Display Shading Manager Grid Analysis Map Stack …calculate a slope map and drape on the elevation surface Grid Table Continuous, regular grid cells (objects) Points, Lines, Areas and Surfaces : --, --, --, --, --, --, --, --, --, --, --, --, --, 2438, --, --, --, --, --, : (Berry) Course Description and Syllabus www.innovativegis.com/basis/Courses/GMcourse12/ Grading Topics and Schedule Basic Concepts Spatial Analysis GIS Modeling Spatial Statistics Future Directions (Berry) Textbook and Companion CD-ROM Course Textbook …Required Reading …occasional in-class questions on required reading …Other Reading CD Materials Access Default.htm …to view & install materials Online …Further Reading Recommended/ Optional …Text Figure slide set (color) …Optional Exercises at end of each topic …Example Applications …MapCalc software, data, tutorials and manual …Surfer software, sample data and tutorials …SnagIt software (recommended) (Berry) Links to Class Materials (Class Webpage) Class folder in GIS lab http://www.innovativegis.com/basis/Courses/GMcourse12/ The GIS Modeling course’s main page contains links to course Administrative Materials and Readings, Lectures, and Homework assignments Links to Reading Assignments — required readings are from the course Text with some Recommended and Optional readings on the CD and posted online Links to Lecture Notes — lecture slide sets are posted Wednesdays by 5:00pm; available in the GIS Lab Thursdays by 12:00noon Links to Homework Assignments — exercise templates are downloaded then completed in teams and submitted to class Dropbox Links to Software — all of the software/data used in the class are on the class CD or available for download (Berry) History/Evolution of Map Analysis http://www.innovativegis.com/basis/Papers/Other/GISmodelingFramework/ Geotechnology – one of the three “mega-technologies” for the 21st Century (the other two are Nanotechnology and Biotechnology, U.S. Department of Labor) Global Positioning System (Location and Navigation) Remote Sensing (Measure and Classify) Geographic Information Systems (Map and Analyze) 70s Computer Mapping (Automated Cartography) 80s Spatial Database Management (Mapping and Geo-query) 90s Map Analysis (Spatial Relationships and Patterns) Organizational Spatial Analysis (Geographical context) Framework Paper Structure of this Course Reclassify (single map layer; no new spatial information) Overlay (coincidence of two or more map layers; new spatial information) Proximity (simple/effective distance and connectivity; new spatial information) Neighbors (roving window summaries of local vicinity; new spatial information) Spatial Statistics (Numerical context) Surface Modeling (point data to continuous spatial distributions Spatial Data Mining (interrelationships within and among map layers) (Berry) Mapped Data Analysis Evolution (Revolution) Traditional GIS Spatial Analysis Elevation (Surface) Forest Inventory Map • Points, Lines, Polygons • Cells, Surfaces • Discrete Objects • Continuous Geographic Space • Mapping and Geo-query • Contextual Spatial Relationships Traditional Statistics Spatial Statistics Spatial Distribution (Surface) Minimum= 5.4 ppm Maximum= 103.0 ppm Mean= 22.4 ppm StDEV= 15.5 • Mean, StDev (Normal Curve) • Map of Variance (gradient) • Central Tendency • Spatial Distribution • Typical Response (scalar) • Numerical Spatial Relationships (Berry) Calculating Slope and Flow (map analysis) Inclination of a fitted plane to a location and its eight surrounding elevation values Slope (47,64) = 33.23% (Neighbors) Slope map draped on Elevation Slope map Elevation Surface Flow (28,46) = 451 Paths Total number of the steepest downhill paths flowing into each location (Distance) (Berry) Flow map draped on Elevation Flow map Deriving Erosion Potential & Buffers Slope_classes Reclassify Flow/Slope Erosion_potential Reclassify Slopemap Overlay Reclassify Erosion Potential Flowmap Flow_classes Protective Buffers But all buffer-feet are not the same… …reach farther in areas of high erosion potential (slope/flow Erosion_potential) Streams Simple Buffer Erosion_potential Simple Buffer (Berry) Calculating Effective Distance (variable-width buffers) Distance away from the streams is a function of the erosion potential (Flow/Slope Distance Erosion_potential Class) with intervening heavy flow and steep slopes computed as effectively closer than simple distance— “as the crow walks” Erosion Buffers Effective Erosion Distance Streams Close Far Simple Buffer Heavy/Steep (far from stream) Light/Gentle (close) Effective Buffers (digital slide show VBuff) (Berry) Classes of Spatial Analysis Operators …all Spatial Analysis involves generating new map values (numbers) as a mathematical or statistical function of the values on another map layer(s) —sort of a “map-ematics” for analyzing spatial relationships and patterns— (Geographic Context) GIS Toolbox Reclassify operations involve reassigning map values to reflect new information about existing map features on a single map layer Overlay operations involve characterizing the spatial coincidence of mapped data on two or more map layers (Berry) Classes of Spatial Analysis Operators (Geographic) …all Spatial Analysis involves generating new map values (numbers) as a mathematical or statistical function of the values on another map layer(s) —sort of a “map-ematics” for analyzing spatial relationships and patterns— (Geographic Context) GIS Toolbox Proximity operations involve measuring distance and connectivity among map locations Neighborhood operations involve characterizing mapped data within the vicinity of map locations (Berry) Travel-Time for Our Store to Everywhere A store’s Travelshed identifies the relative driving time from every location to the store— …analogous to a “watershed” Relative scale: 1 = .05 minutes OUR STORE …close to the store (blue) (Berry) Travel-Time for Competitor Stores Ocean Ocean Competitor 1 Our Store (#111) Competitor 3 Ocean Ocean Competitor 2 Competitor 4 Ocean Competitor 5 Ocean Travel-Time maps from several stores treating highway travel as four times faster than city streets. Blue tones indicate locations that are close to a store (estimated twelve minute drive or less). Customer data can be appended with travel-time distances and analyzed for spatial relationships in sales and demographic factors. (Berry) Travel-Time Surfaces (Our Store & Competitor #4) Blue tones indicate locations that are close to a store (estimated twelve minute drive or less). Increasingly warmer tones form a bowl-like surface with larger travel-time values identifying locations that are farther away. Our Store Competitor (Berry) Competition Map (Our Store & Competitor #4) The travel-time surfaces for two stores can be compared (subtracted) to identify the relative access advantages throughout the project area. Zero values indicate the same travel-time to both stores (equidistant travel-time) …yellow tones identifying the Combat Zone ; green Our Store advantage; red Competitor #4 advantage Competitor Our Advantage Positive Our Store Negative Competitors (See Location, Location, Location: Retail Sales Competition Analysis, www.innovativegis.com/basis/present/GW06_retail/GW06_Retail.htm) (Berry) Mapped Data Analysis Evolution (Revolution) Exercise #1 Logistics 1) Who are we? (class photo; books; break) 2) just to make sure you are comfortable with Homework Exercises Exercise #0 Setup …and then on to Spatial Statistics (Berry) Setting Up and Using Class Data Moving MapCalc Data to your personal workspace 1) 2) 3) 4) 5) 6) 7) Right click on Start at the bottom left of your screen (Task Bar) Select Windows Explorer Locate your personal workspace as directed by the instructor (Z: drive) Create a new folder in your workspace called …\GISmodeling In the new folder create a sub-folder …\GISmodeling\MapCalc Data Browse to the …\GEOG3110 class directory (I: drive) Highlight all of the files/folders MapCalc Data folder on the class directory and select Copy 8) Go to your new …\GISmodeling\MapCalc Data sub-folder and Paste the MapCalc Data files Suggested folder organization …\GISmodeling\MapCalc Data\ (…just created folder containing MapCalc base data) …\GISmodeling\Week1\ (contains all of the data, scripts, screen grabs, etc. developed for week 1) …\GISmodeling\Week2\ (contains all of the data, scripts, screen grabs, etc. developed for week 2) …etc. Example Exercise …download Exer0.doc to your …\GISmodeling\Week1\ folder and complete under the instructor’s guidance (Berry) Exercise #0 (dry run) …in Lattice display format… Use MapCalc to generate a 3D display of the Elevation surface … …use Snagit to capture plot and paste into document …change to Grid display format… …use Snagit to capture plot and paste into document …briefly describe the differences you see between Lattice and Grid displays …email the document to me (Berry) GIS Modeling Framework (Model Criteria) Where are the best places for a campground? …rows represent Model Criteria (Berry) GIS Modeling Framework (Analysis Levels) “Weighting” …map analysis operations are sequenced on map variables to implement the model’s logic Renumber Slope Analyze Renumber Spread Modeled Renumber Spread Renumber Radiate Orient Base “Calibration” Renumber “Algorithm” Derived Interpreted …columns represent Analysis Levels …column transitions represent Processing Approaches (Berry) Campground Suitability Model (Macro script) …the map analysis logic ingrained in the flowchart is translated into a logical series of map analysis commands (MapCalc) Tutor25_Campground Script Derive (Algorithm) Gentle slopes Near roads Near water Good views Westerly Interpret (Calibrate) Combine (Weight) Mask (Constraints) (See “Short description of the Campground model” and “Helpful hints in Running MapCalc” in the Email Dialog section of the Class Webpage) (Berry) Homework Exercise #1 Question Confirm Homework Team— the #1 Model Criteria class will be divided into teams containing two to three members #2 Analysis Levels Download Exercise #1— “Links #3 Derived Maps to Homework,” right-click on “Exer1.doc” and choose “Save” to download …and then access the exercise in Word #4 Calibrated Maps www.innovativegis.com/basis/Senarios/Campground.htm #5 Analyze Command Complete the exercise: #6 Masking Due next week Thursday 5:00 pm (7 days) (…slippage possible if requested by noon) #7 Fancy Display Optional Questions #1-1 and #1-2 (Berry) Mapped Data Analysis Evolution (Revolution) Traditional GIS Spatial Analysis Effective Distance (Surface) Forest Inventory Map • Points, Lines, Polygons • Cells, Surfaces • Discrete Objects • Continuous Geographic Space • Mapping and Geo-query • Contextual Spatial Relationships Traditional Statistics Spatial Statistics Spatial Distribution (Surface) Minimum= 5.4 ppm Maximum= 103.0 ppm Mean= 22.4 ppm StDEV= 15.5 • Mean, StDev (Normal Curve) • Map of Variance (gradient) • Central Tendency • Spatial Distribution • Typical Response (scalar) • Numerical Spatial Relationships (Berry) Classes of Spatial Statistics Operators (Spatial Statistics) …all Spatial Analysis involves generating new map values (numbers) as a mathematical or statistical function of the values on another map layer(s) —sort of a “map-ematics” for analyzing spatial relationships and patterns— (Numeric Context) GIS Toolbox Surface Modeling operations involve creating continuous spatial distributions from point sampled data Spatial Data Mining operations involve characterizing numerical patterns and relationships within and among mapped data (Berry) GeoExploration vs. GeoScience “Maps are numbers first, pictures later” Desktop Mapping graphically links generalized statistics to discrete spatial objects (Points, Lines, Polygons)— non-spatial analysis (GeoExploration) Desktop Mapping Map Analysis X, Y, Value Data Space Field Data Geographic Space Standard Normal Curve Point Sampled Data (Numeric Distribution) Average = 22.0 StDev = 18.7 40.7 …not a problem Discrete Spatial Object 22.0 Spatially Generalized (Geographic Distribution) High Pocket Continuous Spatial Distribution Spatially Detailed Discovery of sub-area… Adjacent Parcels Map Analysis map-ematically relates patterns within and among continuous spatial distributions (Map Surfaces)— spatial analysis and statistics (GeoScience) (See Beyond Mapping III, “Epilog”, Technical and Cultural Shifts in the GIS Paradigm, www.innovativegis.com/basis ) (Berry) Point Density Analysis Point Density analysis identifies the total number of customers within a specified distance of each grid location Roving Window (count) (See Beyond Mapping III, “Epilog”, Technical and Cultural Shifts in the GIS Paradigm, www.innovativegis.com/basis ) (Berry) Identifying Unusually High Density High Customer Density pockets are identified as more than one standard deviation above the mean Unusually high customer density (>1 Stdev) (See Beyond Mapping III, “Topic 26”, Spatial Data Mining in Geo-business, www.innovativegis.com/basis) (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,” 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 …repeated smoothing slowly “erodes” the data surface to a flat plane = AVERAGE (digital slide show SStat2) (Berry) Visualizing Spatial Relationships Phosphorous (P) Geographic Distribution What spatial relationships do you SEE? …do relatively high levels of P often occur with high levels of K and N? …how often? …where? “Maps are numbers first, pictures later” Multivariate Analysis— each map layer is a continuous variable with all of the math/stat “rights, privileges and responsibilities” therewith …simply “spatially organized “ sets of numbers (matrix) (Berry) Calculating Data Distance …an n-dimensional plot depicts the multivariate distribution— the distance between points determines the relative similarity in data patterns Pythagorean Theorem 2D Data Space: Dist = SQRT (a2 + b2) 3D Data Space: Dist = SQRT (a2 + b2 + c2) …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, www.innovativegis.com/basis) (Berry) 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 …a map stack is a spatially organized set of numbers …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, www.innovativegis.com/basis) (See Beyond Mapping III, “Topic 16”, Characterizing Spatial Patterns and Relationships, www.innovativegis.com/basis) (Berry) 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 yield variation every few feet. This map is Steps 1) – 3) 4) combined with soil, terrain and other maps to derive 5) a “Prescription Map” that is used to 6) adjust fertilization levels every few feet in the field (variable rate application). On-the-Fly Yield Map Step 4) Map Analysis Farm dB Cyber-Farmer, Circa 1992 Prescription Map Variable Rate Application Step 5) Step 6) (Berry) (See Beyond Mapping III, “Topic 16”, Characterizing Spatial Patterns and Relationships, www.innovativegis.com/basis) Spatial Data Mining Precision Farming is just one example of applying spatial statistics and data mining techniques Mapped data that exhibits high spatial dependency create strong prediction functions. As in traditional statistical analysis, spatial relationships can be used to predict outcomes …the difference is that spatial statistics predicts where responses will be high or low (See Beyond Mapping III, “Topic 28”, Spatial Data Mining in Geo-business, www.innovativegis.com/basis) (Berry) (Nanotechnology) Geotechnology (Biotechnology) 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) Geographic Information Systems (map and analyze) Global Positioning System (location and navigation) Remote Sensing (measure and classify) GPS/GIS/RS The Spatial Triad Mapping involves precise placement (delineation) of physical features (graphical inventory) Where Descriptive Mapping Why is What Prescriptive Modeling So What and What If Modeling involves analysis of spatial relationships and patterns (numerical analysis) (Berry)