Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Introduction to GIS Modeling Week 10 — Future Directions GEOG 3110 – University of Denver Presented by Joseph K. Berry W. M. Keck Scholar, Department of Geography, University of Denver GIS in Transition; Dominant IT Forces; Dominant GIS Forces; A Peek at The Bleeding Edge; Dominant Human Forces 2nd Exam (begins tomorrow) …can only improve your overall grade (if you blow it, no problem) …same logistics as the midterm Exam is available …from the class website (under Homework Assignments) (Berry) Optional Exercise #10 Awaits Import/Export Grid Data Optional Exercise #10 5 extra credit points Export Basic Formats Import MapCalc to/from Surfer ESRI GridAscii (.asc) Surfer Ascii (.grd) Bare matrix (.dat) Import/Export Vector Data Basic Formats MapInfo (.tab) ArcView (.shp) Dbase (.dbf) Comma Separated Variable (.cvs) MapCalc to/from ArcView (Berry) Exercise #9 Excitement Part 1 – Visualizing Map comparisons Part 2 – Comparing Discrete Maps Part 3 – Comparing Continuous Surface Maps Part 4 – Identifying Unusual Areas Part 5 – Calculating a Similarity Map Part 6 – Calculating a Cluster Map Part 7 – Deriving a Dependent Variable Map Part 8 – Generating Scatter Plots of Map Correlation and Univariate Regression Equation Part 9 – Generating a Multivariate Regression Equation Predicted (Berry) Spatial Data Mining Process (sales) The Spatial Data Mining Process first identifies… Dependent Map Variable Factor of Interest (Sales) Y 1 X1 X2 X3 X4 1) a map of a factor of interest (sales) and 2) related map variables (demographics) are acquired, then 3) analyzed to derive a spatial relationship (regression) that can be used to generate a 4) prediction map (sales) for a different location or future time. Spatial dB Prediction Equation 2 Independent Map Variables Prediction Map Ysales = b0 + b1X1 + b2X2 + … Driving Factors 3 Derive Map-ematical Relationships 4 Evaluate Derived Relationships (Demographics) (Regression) (Sales for other Place/Time) “Data Collection” “Data Analysis” “Implementation” Historical Setting and GIS Evolution Manual Mapping for 8,000 years Geotechnology (GPS, GIS, RS) DIGITAL ANALOG Computer Mapping automates the cartographic process (70s) Spatial Database Management links computer mapping techniques with traditional database capabilities (80s) Map Analysis representation of relationships within and among mapped data (90s) Focus of this course Multimedia Mapping full integration of GIS, Internet and visualization technologies (00s) (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 Focus of this course Mapping involves precise placement (delineation) of physical features (graphical inventory) Where is Descriptive Mapping Why What Prescriptive Modeling So What and What If Modeling involves analysis of spatial relationships and patterns (numerical analysis) (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) 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) 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) Map Analysis Evolution (4 square summary) Traditional GIS Spatial Analysis Store Travel-Time (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) Dominant IT Forces (three game changers) #1 Cloud Computing — Cloud computing is computation, software, data access, and storage services that do not require end-user knowledge of the physical location and configuration of the system that delivers the services #2 Crowdsourcing — Crowdsourcing is the act of outsourcing tasks, traditionally performed by an employee or contractor, to a large group of people or community (a crowd), through an open call. #3 Photosynth — Photosynth takes sets of photos, mashes them together to create a geometrically stable immersive 3D scene that allows the viewer to explore details of places, objects, and events (Berry) #1 Cloud Computing (“Hosted Elsewhere” environment) + Lower operational costs, quicker development times and device independence + Enables heavy duty data crunching to better process and explore Internet information pools + Pay for usage reduces fixed expenses on hardware, software, maintenance and support Devices Pros Buzzwords “Object-Oriented” Technology “Enterprise GIS” “Geography Network” Mobile Old New “Grid Computing” “Interoperability” “Web Services” “Mash-ups” “Distributed Systems” “Mobile GIS” “On-Line Office” Virtualized Scalable Service “3rd Party Integration” Server “Software as a Service” “On-Line Resources and Storage” “On-Demand Apps” Maps and Imagery Databases Capabilities Software Cons Data and processing is at the mercy of the service provider and reliable Internet connection Capabilities limited by marketplace demand, standardization and provider incentives Security concerns, liability, legal position and data/processing ownership/responsibility (Berry) #2 Crowdsourcing for GIS Input Crowdsourcing is the act of outsourcing tasks, traditionally performed by an employee or contractor, to a large group of people or community (a crowd), through an open call. Survey design, implementation and analysis— “Respondent” (independent survey samples, 1980s) — Wikipedia Crowdsourcing Internet Camera GPS "Participant” (group discussions , 1990s) In-house Outsourcing Evolution in developing the Social Science knowledge base for most applications… "Participant” (crowd , 2010s) …a spatially consistent and interactive participatory device in every pocket For example, the public may be invited to develop a new technology, carry out a design task (also known as “community-based design” and “distributed participatory design”), or help capture, systematize or analyze large amounts of data (citizen science). The term has become popular with businesses, authors, and journalists as shorthand for the trend of leveraging mass collaboration enabled by the Internet. (Berry) #3 Phytosynth for GIS Input http://photosynth.net/default.aspx Photosynth takes sets of photos, mashes them together to create a geometrically stable immersive 3D scene that allows the viewer to explore details of places, objects, and events. …in a sense, it is analogous to airborne Lidar as it forms 3-dimensional point clouds that when rectified yields sub-meter XYZ positioning within composited image using standard digital camera photo sets from multiple angles. (Berry) Dominant GIS Forces (three game changers) #1 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 GIS Industry CAD, dBase and Visualization Industries Tomorrow Today …etc. …etc. #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 threedimensional UTM grid cell (1 m2) #3 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 (Berry) #1 Boutique to Big Box 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 GIS …four main perspectives of the trailing “S” Systems Science GIS Industry …etc. CAD, dBase and Visualization Industries Specialist Solutions …etc. 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 — 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 (Berry) #2 Universal Spatial Key (Cartesian coordinate system) North Project Area (Areal Extent) Earth’s Surface Caspian Sea off the coast of Azerbaijan Height (Z) Earth’s Center 40o N W Latitude (Y) E 50o E Longitude (X) … intersection with a mathematically inferred spheroid/ellipsoid/geoid/datum establishes the Height (Z) from the center of the earth to any point on the earth’s surface` S (Berry) #2 Universal Spatial Key (grid space as key) 100km, 10km, …1m UTM gridlines Entire 3D volume containing the earth is pre-partitioned into small Grid Elements using basic geometry equations… WHERE is WHAT …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 (Berry) #3 Alternative Geographic Referencing Tightly Clustered Groupings Continuous Nested Grid Elements Hexagonal Grid Dodecahedral Grid Consistent (6 facets) Hexagon Square Grid (8 facets) distances and adjacency to surrounding grid elements Inconsistent distances and adjacency to surrounding grid elements Dodecahedral (12 facets) Cubic Grid (26 facets) (Orthogonal and Diagonal) Cartesian Coordinate System Square Cube Square Cube 2D Grid Element 3D Grid Element (Planimetric) (Volumetric) A Peek at the Bleeding Edge (2010 and beyond) Revisit Analytics Future Directions (VI -2020s) Multimedia Mapping (IV -2000s) Revisit Geo-reference (V -2010s) Contemporary GIS Spatial dB Mgt (II -1980s) GIS Modeling (III -1990s) …but those who live by the Crystal Ball are bound to eat ground glass Evan Vlachos The Early Years Mapping focus Data/Structure focus Analysis focus Computer Mapping (Decade I -1970s) (Berry) Revamping Geographic Referencing 1) Geo-Referencing …2) data structure The Cartesian Coordinate System based on rectangular grid referencing will be replaced by Hexagon and Dodecahedron (Berry) Revamping Map Analysis Geo-referencing and Data Structure advances will lead to revised/new techniques in… Map Analysis Spatial Analysis— 1) recoding of all operations to take advantage of increased precision/accuracy in the new georeferencing and data structures; 2) incorporate dynamic influences on effective movement/connectivity (e.g., direction, accumulation, momentum); and 3) uncertainty and error propagation handing for all analytical processing. …emphasis on Data Accuracy (vs. Precision) 2) Data Structure …1) geo-referencing Traditional 3D GIS (X,Y and Attribute) to 4D GIS (X,Y,Z and Attribute) and possibly to 5D GIS (X,Y,Z,Time and Attribute) Spatial Statistics— 1) uncertainty and error propagation handing for all analytical processing; 2) CART, Induction and Neural Networks techniques requiring large N will replace traditional multivariate data analysis; and 3) grid-cell will become the de facto primary key for database referencing /analysis (vector for mapping). (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 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. #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 The “Bookends “ are currently driving GIS (Berry) #1 The “-ists” and the “-ologists” Together the “-ists” and the “-ologists” frame and develop the Solution for an application. The “-ists” — and — The “-ologists” …understand the “tools” that can be used to display, query and analyze spatial data …understand the “science” behind spatial relationships that can be used for decision-making Data and Information focus Knowledge and Wisdom focus Application Space Geotechnology’s Core “-ists” Technology Experts Solution Space “-ologists” Domain Experts #1 The “-ists” and the “-ologists” (a larger tent) Decision Makers utilize the Solution under Stakeholder, Policy & Public auspices. “Policy Makers” “Stakeholders” “Decision Makers” Application Space Geotechnology’s Core “-ists” Technology Experts Solution Space “-ologists” Domain Experts #2 The Softer Side of GIS Philosopher’s Progression of Understanding — Data (all facts) Information (facts within a context) …GeoExploration emphasizes tools for data access and visualization (general user) Mapping focus Data/Structure and Analysis focus Knowledge (interrelationships among relevant facts) Wisdom (actionable knowledge) …GeoScience emphasizes tools for spatial reasoning and understanding of spatial patterns and relationships (application specialist) Prescription Increasing Abstraction — Description #2 The Softer Side of GIS (within a GIS context) Judgment Map Types Spatial Processing Facts Base – measured features, conditions and characteristics Collect – Earth circumference is 24,900 mi – Britney Spears was born 12/2/1981 – Britney Spears is 25 years old Philosopher's Levels of Cognitive Levels of Understanding Data – all facts – the temperature is 32o F : Information Relevant Facts – facts within a context – the temperature is 32o F Knowledge – interrelationships among relevant facts Wisdom – actionable knowledge (fact) Derived – inferred conditions and characteristics (implied fact) – direct acquisition of primary information (e.g. elevation) Calculate – uses algorithms to derive secondary information (e.g., slope) Perception Interpreted – it sure is cold – it’s not cold – adjusted to reflect expertise and presumption (Alaskan) (judgment) Opinions/Values Modeled Simulate – I hate this weather – I love this weather – potential solution within model logic and expression – “what if” investigation of alternative scenarios (Alaskan) (conjoined judgment) (multiple perspectives) (Floridian) (Floridian) Calibrate/Weight – translates information into relative scales (preference & importance) #2 The Softer Side of GIS (the NR experience) Future Directions: Social Acceptability as 3rd Spatial Reasoning, Dialog and Consensus Building filter 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. Podium Public Involvement Banquet Table Inter-disciplinary Science Team Table 1970s Increasing Social Science & Public Involvement 2010s #3 Enlarging GIS Education (historical evolution) GIS User Community #3 Enlarging GIS Education (historical evolution) The “Bookends “ are currently driving GIS Computer Programmer– Solutions Developer– Systems Manager– Data Provider– GIS Specialist– General User– …develops GIS tools; …develops applications that link GIS to real-world problems; …develops and maintains spatial databases and connections within (LAN) and outside (Internet) the organization; …develops GIS databases; …interacts with other GIS professionals and users to implement spatial solutions; …applies GIS operations, techniques, procedures and models to address real world processes in support of decisionmaking; …mostly computer science skills with some experience in GIS …mostly GIS/CS background with some discipline expertise …CS and GIS balance …good skills in GPS and Remote Sensing with strong skills in GIS data formats and geodetic referencing …GIS with considerable discipline expertise …strong discipline expertise with GIS awareness Where From Here? …where will you be in GIS 10 years from now? (Berry)