CFR 250/590 Introduction to GIS © Phil Hurvitz, 1999-2000intro_gis.ppt 1 Introduction to GIS...

© Phil Hurvitz, 1999-2000

CFR 250/590 Introduction to GIS

intro_gis.ppt 1

Introduction to GIS

• Spatial (coordinate) data model

• Relational (tabular) data model

• Scale issues

• Sample data_

Overview



intro_gis.ppt 2

Spatial Data Model

• GIS are driven by spatial data

• 2 basic spatial data models exist

• vector• points• lines • polygons

• raster• grid cells (images, bitmaps, DEMs)

_



intro_gis.ppt 3

Vector Data Model

• Characteristics of the vector data model:

• Features positioned accurately

• Shape of features represented correctly

• Features represented discretely (no fuzzy boundaries)

• Complex data structure (especially for polygons)_



intro_gis.ppt 4

Vector Data Model

Points: represent discrete point features



intro_gis.ppt 5

Vector Data Model

Lines: represent linear features



intro_gis.ppt 6

Vector Data Model

Lines: represent linear features

• Lines start and end at nodes• line #1 goes from node #2 to node #1

• Vertices determine shape of line_



intro_gis.ppt 7

Vector Data Model

Polygons: represent bounded areas



intro_gis.ppt 8

Vector Data Model


• Polygon #2 is bounded by lines 1 & 2• Line 2 has polygon 1 on left and polygon 2 on right

_



intro_gis.ppt 9

Vector Data Model

• complex data model• “arc/node topology”

_




intro_gis.ppt 10

Vector Data Model

Types (formats) of vector data available in ArcView

• ArcView shapefiles

• ArcInfo coverages and libraries

• CAD files (AutoCAD DWG, DXF;Microstation DGN)

• StreetMap files

• Spatial Database Engine (SDE) data

• ASCII point coordinate data_



intro_gis.ppt 11

Vector Data Model

• A relatively new vector data format

• Preferred in ArcView• Draws fast• Fully editable in ArcView

• Simple in structure

• Does not use arc-node topology• “Connected” lines do not necessarily share a common node• Adjacent polygons do not share common bounding arcs• Data sets are either point or line or polygon

_

ArcView shapefiles



intro_gis.ppt 12

Vector Data Model

• A commonly found format

• Data model more complex

• Draws more slowly in ArcView

• Coordinate data not editable in ArcView

• Can be used in both ArcView and ArcInfo

• Polymorphic

• Problematic file structure (more on this later in the term)_

ArcInfo coverages



intro_gis.ppt 13

Vector Data Model

• CAD data are very common (industry standard)

• DXF, DWG, and DGN formats supported in ArcView

• Coordinate data not editable in ArcView

• Frequently contain “sloppy” data• No enforced topology rules• Gaps in data

• Frequently contain little or no useful attribute data_

AutoCAD & Microstation CAD drawing data



intro_gis.ppt 14

Vector Data Model

• Easy to obtain from a variety of sources• GPS• Traverse• Direct reading from maps

• OS, architecture, and application independent

ASCII coordinate data



intro_gis.ppt 15

Raster Data Model

• Rectangular grid of square cells

• Shape of features generalized by cells

• Continuous (surface) data represented easily

• Simple data structure_

Characteristics of the raster data model:



intro_gis.ppt 16

Raster Data Model

• Wind speed

• Elevation, slope, aspect

• Chemical concentration

• Likelihood of existence of a certain species

• Electromagnetic reflectance (photographic or satellite imagery)_

Raster data are good at representing continuous phenomena



intro_gis.ppt 17

Raster Data Model

• origin is set explicitly

• cell size is known

• cell references (row/column locations)are known

• cell values are referencedto row/column location

• values represent numerical phenomena orindex codes for non-numerical phenomena_

Raster spatial data model



intro_gis.ppt 18

Raster Data Model

• digital orthophoto

• digital elevation model (DEM)_

A few different types of raster data



intro_gis.ppt 19

• The “where” of GIS is determined by coordinate (map) data structures, but …

• The “what” of GIS is determined by tabular (relational database) data structures

• Thus, tabular data are just as important as coordinate data_

Relational Database Model & Attribute Data Structures



intro_gis.ppt 20


• Tables are composed of:

• fields

and

• records_

Attribute data are stored in database tables.



intro_gis.ppt 21


• dBase

• rBase

• Access

• Excel (database functionality)

• Oracle, INFORMIX, INGRES, SQL Server

• INFO (in ArcInfo)_

You may already be familiar with relational databases



intro_gis.ppt 22


• tables are stored on the disk as

• .dbf,

• .txt, or

• in INFO directories_

ArcView uses tabular data formats from dBase, ASCII text, and INFO files



intro_gis.ppt 23


Tables can be linked and joined (“related”) by use of common values in fields



intro_gis.ppt 24


• Vector• point attribute tables• polygon attribute• line attribute

• node attribute* • text attribute*• route & event tables*

* in ArcInfo coverage data only

Different types of attribute tables in ArcView

• Raster• value attribute

_



intro_gis.ppt 25


Relationship between tabular and map data

• one-to-one between features and records_



intro_gis.ppt 26

Scale Issues

Be aware of:

• Data’s source scale

• Mixing data from different source scales

• Appropriateness of output scale_

Scale of data plays an important role, and frequently causes problems



intro_gis.ppt 27

Scale Issues

• A 1/40th in line on a 1:24,000 scale map is 50 ft on the ground

50' * * 0.025" 12"1'

1"24,000"

• A .30 mm line on a 1:200,000 scale map is almost 2,000 ft on the ground_

1,969' * * * * mm 0.30 12"1'

2.54cm1"

mm 101cm

12,000,000

Map measurement and true ground measurement



intro_gis.ppt 28

Scale Issues

• 1:100,000 scale data from USGS DLG

Data from different sources and scales can vary widely



intro_gis.ppt 29

Scale Issues

• 1:1,000,000 scale data from DCW (DMA)




intro_gis.ppt 30

Scale Issues

•1:2,000,000 scale data from USGS DLG




intro_gis.ppt 31

Scale Issues

• one inch on the map equals 200 inches on the ground?

or

• one inch on the map equals 200 feet on the ground?_

• “one to two-hundred”: does this mean

Beware of scale statements



intro_gis.ppt 32

Course Sample Data

• Original data sources

• Legacy maps

• USGS digital line graphs

• DNR data

• GPS surveys

• Digital orthophoto interpretation_

Pack Forest GIS database



intro_gis.ppt 33

Course Sample Data

• CD directory pfdata• Forest stands• Streams• Roads, trails• Soils• Elevation contours• Culverts• Forest inventory data• Digital orthophotos• Digital elevation model• …

_

Pack Forest GIS database



intro_gis.ppt 34

Course Sample Data

• CD directory esridata• Worldwide data sets

• countries• major rivers

• United States data• states• counties• cities• rivers• roads

• Canada• Mexico

_

ESRI Sample Data



intro_gis.ppt 35

Sample Data

Unless otherwise specified,

Projection STATEPLANEWashington South Zone (State Plane 5626 or FIPSZone 4602)

Datum HPGN (a.k.a. NAD83/91)Units FEET Spheroid GRS1980_

Pack Forest GIS database projection & coordinate definition

Date post:	26-Dec-2015
Category:	Documents
Upload:	sylvia-manning
View:	225 times
Download:	1 times

CFR 250/590 Introduction to GIS © Phil Hurvitz, 1999-2000intro_gis.ppt 1 Introduction to GIS...

Documents