CS 128/ES Lecture 4a1 Spatial Data Models
CS 128/ES 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
CS 128/ES Lecture 4a3 What do you see out the window? Naïve view: a blur of colors on my retina Topological view: a collection of points, lines & areas in geometric relation to each other Object-oriented view: sidewalks, buildings, trees, people … Western NY view: a lot of snow
CS 128/ES Lecture 4a4 Two types of features Discrete Continuous
CS 128/ES Lecture 4a5 What is data?
CS 128/ES Lecture 4a6 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?)
CS 128/ES Lecture 4a7 Model dimensionality: 2-D X-Y coordinates No elevations Road crossings…
CS 128/ES Lecture 4a8 Model dimensionality: 3-D X-Y-Z coordinates False relief
CS 128/ES Lecture 4a9 More sophisticated 3-D models Wire frame model “draped” with aerial photograph or other surface feature Thematic material can be layered on
CS 128/ES Lecture 4a10 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 BlackfeetJackson 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
CS 128/ES Lecture 4a11 Stages of development: 1.Conceptual model: select the features of reality to be modeled and decide what entities will represent them 2.Spatial data model: select a format that will represent the model entities 3.Spatial data structure: decide how to code the entities in the model’s data files
CS 128/ES Lecture 4a12 The modeling process 1.Conceptual model 2.Spatial data model
CS 128/ES Lecture 4a13 Our local “Happy Valley”
CS 128/ES Lecture 4a14 1. Conceptual models Decide the model’s purpose Select the features to be modeled
CS 128/ES Lecture 4a15 Spatial entities: 5 types 1.Points 2.Lines 3.Areas (polygons) 4.Networks 5.Surfaces
CS 128/ES Lecture 4a16 Happy Valley spatial entities
CS 128/ES Lecture 4a17 Discrete vs. continuous features Points Lines Areas Networks Discrete features: Continuous features: Surfaces
CS 128/ES Lecture 4a18 Networks Line entity Used to model features along which material, energy, or information flow Special components: nodes, stops, turns, direction, impedance
CS 128/ES Lecture 4a19 Impedance
CS 128/ES Lecture 4a20 Surfaces Continuous feature Every location has a value, even if only interpolated from discrete samples
CS 128/ES Lecture 4a21 Digital terrain models
CS 128/ES Lecture 4a22 Precision agriculture Aerial photographSoil pH Crop yield
CS 128/ES Lecture 4a23 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).