CS 128/ES 228 - Lecture 4b1 Spatial Data Formats.

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Presentation transcript:

CS 128/ES Lecture 4b1 Spatial Data Formats

CS 128/ES Lecture 4b2 Need data for a GIS? Just photograph a topographic map Better yet, download one from the internet But are the roads, buildings, and other “objects” on this photo GIS layers?

CS 128/ES Lecture 4b3 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 4b4 2. Spatial data models 1.Raster 2.Vector 3.Object-oriented and… attribute data Spatial data formats: Fig. 3.1 in 3 rd ed.

CS 128/ES Lecture 4b5 Raster format  Features represented by cell contents  Spatial precision limited by cell size  Surfaces modeled as continuous values (almost) Fig. 3.9 in 3 rd ed.

CS 128/ES Lecture 4b6 Vector format  Discrete features explicitly represented  Spatial precision limited by number format  Surfaces shown by contours rather than continuous values Fig. 3.9 in 3 rd ed.

CS 128/ES Lecture 4b7 Object-oriented formats Leave details for CS majors Fig in 3 rd ed.

CS 128/ES Lecture 4b8 Thematic data (a.k.a. “attribute data”) Quantitative or descriptive May represent 1 or many themes Tied to a spatial reference Represented differently in raster vs. vector formats

CS 128/ES Lecture 4b9 Scales of measurement DataUnitScale Resort nametextNominal Resort rankingvalueOrdinal Winter temp. oCoCInterval Size of ski aream2m2 Ratio Heywood et. al – Table 2.1

CS 128/ES Lecture 4b10 Spatial modeling in raster format  Basic entity is the cell  Region represented by a tiling of cells  Cell size = resolution  Attribute data linked to individual cells

CS 128/ES Lecture 4b11 Attribute data in raster format Attribute data are used to create symbology for each cell

CS 128/ES Lecture 4b12 Additional attribute data  Some GISs provide a VAT linked to individual cells (e.g. ArcInfo GRID)  VAT data then accessible to database management system Unlimited additional fields 

CS 128/ES Lecture 4b13 Attribute data for a vector layer  Each entity is linked to a row in an attribute table  Themes not (usually) displayed but available via Identify tool

CS 128/ES Lecture 4a14 Vectors are good at modeling … roadways or wiring consist of discrete components; types and order of the connections are key Spaces between the network components generally not of interest Bottom : … networks

CS 128/ES Lecture 4a15 Rasters are good at modeling … they model a continuous feature as a 2- or 3-D layer every location has a value, even if only interpolated from discrete samples Both: … surfaces

CS 128/ES Lecture 4a16 Topographic maps use contours… …but the elevation between contour lines is undefined

CS 128/ES Lecture 4a17 Digital terrain models Every cell has an elevation value Fig in 3 rd ed.

CS 128/ES Lecture 4a18 Precision agriculture Aerial photographSoil pH Crop yield

CS 128/ES Lecture 4a19 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).

CS 128/ES Lecture 4b20 Rasters are a type of Tesselation A closed shape or polygon that repeats on all sides without any gaps or overlaps Three regular polygons tesselate the plane: Square Equilateral triangle Hexagon

CS 128/ES Lecture 4b21 Tilings In 1922 Escher visited the Alhambra palace and saw the wall tilings of the Moors. He was excited to find other artists who had been captivated by tilings, but also made this revealing comment: "What a pity their religion forbade them to make graven images."

CS 128/ES Lecture 4b22 Escher’s “tesselations”

CS 128/ES Lecture 4b23 Quilters also tesselate Designing Tesselations by Jinny Beyer

CS 128/ES Lecture 4b24 Effects of resolution – raster Larger cells:  less precise spatial fix  line + boundary thickening  features too close overlap - less detail possible Fig in 3 rd ed.

CS 128/ES Lecture 4b25 Advantages of raster format many data sets available easy to overlay multiple themes able to represent multiple continuous surfaces  different file formats readily inter-converted fast computer lookup and display

CS 128/ES Lecture 4b26 Limitations of raster format  poor representation of discrete objects exact boundary location difficult constant resolution throughout the region modeled generates very large data sets difficult to change projection or coordinate system

CS 128/ES Lecture 4b27 Raster layers don’t share well

CS 128/ES Lecture 4b28 Raster layers are normally projected Note the datum and projection/ coordinate system Special software needed to re-project

CS 128/ES Lecture 4b29 Summary: Raster format Huge amounts of spatial data are available in raster format Rasters are the format of choice for continuous features Rasters do a poor job of representing discrete features