Introduction to Geographic Information Science. Updates/News. Last Lecture 1/23/2017. Geography 4103 / Spatial Data Representations

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1 Geography 4103 / 5103 Introduction to Geographic Information Science Spatial Data Representations Updates/News Waitlisted students First graded lab this week: skills learning Instructional labs vs. independence Reading discussion groups Reading discussion writing, questions? Last Lecture GIS in general, its usefulness for society and its impact for different fields of application Main GIS components that ensure working with spatial data, manage, store, edit and analyze them as needed; in an institutional context You have seen that GIS is nowadays an established technology that can help us managing, protecting and changing our world 1

2 Today s Outline We will talk about spatial data and their representations You will see how to represent physical entities in the real world in a GIS and some problems How to choose the most appropriate representation and thematic description of spatial phenomena Learning Objectives Spatial data representations Conceptualizations of spatial entities (Field and object view) Types of attribute data Common data models Remember GIS components? How can we make attributes spatial? Why are metadata important? Are they? Explain on this example: 2

3 GIS Components In practice, (i.e. when you work on a project) you don t think about GIS this way. In designing a project or a database, you do. A Very Brief History of GIS 1950s in Geography Quantitative revolution Computer cartography 1960s: individual development efforts Minnesota land management info sys. (MLMIS) Harvard Lab for Computer Graphics (and 70s) SYMAP, GRID, ODYSSEY C(anada)GIS Roger Tomlinson coins term GIS A Very Brief History of GIS 1970s: The federal government USGS US Census: DIME & TIGER file formats 1980s and 1990s: A GIS industry Commercial vendors, GIS on the desktop Rapid adoption of GIS technologies Academia: NCGIA & UCGIS 2000 and beyond. Ubiquitous geospatial technologies Integration with mainstream database technologies The Internet 3

4 Latest News & Trends Online: (from ESRI, a good place to start) (Colorado gisco list) Careers: Academic Journals: Internat l Journal of Geographic Information Science Photogrammetric Eng. and Remote Sensing (PE&RS) Cartography and Geographic Information Science Natural Hazards Research and Applications Annals of the Association of American Geographers Applied Geography TGIS GIScience & RS The Broad Street Pump Cholera outbreak in Soho / London, England 1854 Dr. Snow and his theory of contaminated water in wells Monitored the epidemic by interviews Leads to the pump at Broad Street Removal of the handle saved an unknown number of live Find more at: Or in: Tufte, E.R Visual Explanations Snow s Map Snow mapped the monitored cases and could determine the location of the well closest to these cases This was genius-like! Snow as the pioneer of disease mapping in modern epidemiology Detection Representation 4

5 The Picture of the World Complexity in the real world To represent information about this world in maps or digital systems we need to simplify what we see Generalized, abstracted, approximate information about entities, their location and properties Why do we have to simplify? Consequences? Mapping/Modeling Reality Entities: Things in the real world Entities are represented by (cartographic) objects that contain essential characteristics Biased by GIS data developer and purpose (Why?) Objects : abstract, imperfect representations of reality stored in a spatial database Let s try to create one object? Object Entity Show & create water body Data Model Data Model A consistent way of defining and representing objects in a database, and of representing the relationships among the objects. Spatial Data models typically include at least two parts Coordinate data - pairs or triplets of numbers defining location Attribute data - text, numbers, images ( non-spatial data) 5

6 Spatial Data Model Representation of objects in a spatial database and spatial relationships among them!!! Point of origin + spatial location + extent defined by coordinate data Attribute data US crop: spatial query adjacent/ combined w/ attribute Spatial Object Types Representation of entities graphically as spatial objects: Points (0-dimensional) Lines (1-dimensional) Areas (2-dimensional) Surfaces (2.5 dimensional) Volumes (3-dimensional) 6

7 Attribute Data Non-spatial data for describing the characteristics of objects ( scale types, Stevens, 1946) Nominal: descriptive (land use) Ordinal: ranked (city size - small, medium, large) Interval/ Ratio: ranked and absolute differences Interval: meaningful diffs btw. Values (T in F or C, ph) Ratio: Also a Zero point (height/weight, T in K) Multiple Objects from a Single Entity A lake may be a municipal water source recreation area flood control sink wildlife habitat We typically store different object types (even from the same entity) in different layers. Thematic Layers Separate layers for each view (thematically) On top of each other objects relate to the same spatial locations but represent different thematic entities Combining information from different spatial datasets Multiple objects from one entity (or several ones) Query: cnties w/in state 7

8 Common Data Models Raster and vector data models We will come back to each of them in more detail Back to water/nlcd Issues for representation? Conceptualizations of Spatial Phenomena 8

9 Soil maps 9

10 Soil surveys and maps? How homogeneous is our world? How much detail? 10

11 Where does it begin & end? Conceptualizations of Spatial Phenomena Object view: Empty space contains discrete objects (lakes, land cover) Field view: phenomena varying over space continuously (elevation, RS data?) Object vs. Field CONTINUOUS? 11

12 Raster Data (surfaces) as Fields and Objects Data q lc vs. dem Remember? What is a spatial data model and which (main) types of data models do you know? What is a spatial object and which types do we know in vector data? What is the difference to an entity? What are the different conceptualizations of spatial phenomena? How would you conceptualize the following in terms of data model and conceptualization? Why?: land cover information precipitation municipality boundaries? More! So what are obvious implications from choosing (1) a certain data model, (2) a particular conceptualization for representing your spatial information. Explain some advantages / disadvantages of different data models. Why does this matter? What could go wrong? 12

13 Summary Physical entities are represented by spatial objects Abstracted simplified and imperfect We use coordinate information and attribute data to define location, extent and properties of these spatial objects The two common data models are raster and vector Two common conceptualizations of geographic phenomena are: the field view and the object view Next Time We will talk about scale and resolution of spatial data We will try to understand these terms and implications resulting from them We will talk about scale and resolution in GIS and GIScience 13

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