1. CS 128/ES 228 - Lecture 4a1 Spatial Data Models Section 2: lift the lid & look inside a GIS

2. CS 128/ES 228 - Lecture 4a2 What is a spatial model? A simplified representation of part of the real world, referenced to spatial coordinates, and created for a specific purpose

3. CS 128/ES 228 - Lecture 4a3 Two types of features (“entities”) Discrete Continuous

4. CS 128/ES 228 - Lecture 4a4 are What are data? Observations or measurements of the real world Three “modes” (or 3 questions to answer): 1.Spatial mode (where is it?) 2.Thematic mode (what is it?) 3.Temporal mode (when was it observed?)

5. CS 128/ES 228 - Lecture 4a5 Model dimensionality: 2-D X-Y coordinates No elevations Road crossings…

6. CS 128/ES 228 - Lecture 4a6 Model dimensionality: 3-D X-Y-Z coordinates False relief http://earth.esa.int/p ub/INSAR/dem/ves_d em.gif

7. CS 128/ES 228 - Lecture 4a7 More sophisticated 3-D models Wire frame model “draped” with aerial photograph or other surface feature Thematic material can be layered on http://biology.usgs.gov/stt/SNT/noframe/cl111.htm

8. CS 128/ES 228 - Lecture 4a8 Model dimensionality: 4-D X-Y-Z coordinates + temporal dimension Fig. 7. A geographic information system representation of glacier shrinkage from 1850 to 1993 in Glacier National Park. The Blackfeet­ Jackson glaciers are in the center. The yellow areas reflect the current area of each glacier; other colors represent the extent of the glaciers at various times in the past. Courtesy C. Key, USGS and R. Menicke, National Park Service http://biology.usgs.gov/stt/SNT/noframe/cl111.htm

9. CS 128/ES 228 - Lecture 4a9 Stages of development: 1.Conceptual model: select the features of reality to be modeled and decide what entities will represent them. Driven by the purpose of the model. 2.Spatial data model: select a format that will represent the model entities. Driven by the conceptual model and by data availability. 3.Spatial data structure: decide how to code the entities in the model’s data files. CS concern.

10. CS 128/ES 228 - Lecture 4a10 The modeling process 1.Conceptual model 2.Spatial data model Decisions….. More decisions…

11. CS 128/ES 228 - Lecture 4a11 Our local “Happy Valley”

12. CS 128/ES 228 - Lecture 4a12 1. Conceptual models  Decide the model’s purpose  Select the features to be modeled

13. CS 128/ES 228 - Lecture 4a13 Spatial entities: 5 types 1.Points 2.Lines (= “polylines”) 3.Areas (= “polygons”) 4.Networks 5.Surfaces

14. CS 128/ES 228 - Lecture 4a14 Happy Valley spatial entities

15. CS 128/ES 228 - Lecture 4a15 Discrete vs. continuous features Points Lines Areas Networks Discrete features: Continuous features:  Surfaces

16. CS 128/ES 228 - Lecture 4a16 Networks Line entity Used to model features along which material, energy, or information flow Special components: nodes, stops, turns, direction, impedance

17. CS 128/ES 228 - Lecture 4a17 Impedance

18. CS 128/ES 228 - Lecture 4a18 Surfaces Models entity as a continuous feature Every location has a value, even if only interpolated from discrete samples Both: http://snobear.colorado.edu/Mark w/Research/ESRI/ESRI.html

19. CS 128/ES 228 - Lecture 4a19 Digital terrain models

20. CS 128/ES 228 - Lecture 4a20 Precision agriculture Aerial photographSoil pH Crop yield

21. CS 128/ES 228 - Lecture 4a21 Oceanography Estimate of phytoplankton distribution in the surface ocean: global composite image of surface chlorophyll a concentration (mg m-3) estimated from SeaWiFS data (Source: NASA Goddard Space Flight Center, Maryland, USA and ORBIMAGE, Virginia, USA).