The Input Subsystem

GEOG 370

Instructor: Christine Erlien

Building a GIS database

Data selection– Quality– Cost – Input method

Data acquisition

Data transformation

GIS Data: Primary & Secondary Sources Primary data sources

– Created “in house”• Through your own or your team’s field data

collection• By transforming data from sources not yet

available digitally• For use by the same organization

– High level quality control– Often customized for specific

project/application– Costly

GIS Data: Primary & Secondary Sources

Secondary data sources

– Outside data providers• Government• Third party vendor

– Format conversion often required

Government data providers

U.S. Census Bureau– TIGER

U.S. Geological Survey– Imagery, DEMs, DRGs, DLGs

Natural Resource Conservation Service– STATSGO (U.S. General Soil Map)

National Oceanic & Atmospheric Agency– Coastal management– Oil & chemical spills– Coral reef conservation

Third Party Vendors

ESRI

TeleAtlas Map Databases

DeLorme Street Atlas & Topo Usa

GeoCommunity Data Bundles

Input Devices

Manual input devices– Digitizing

• Transforms information from analog format (e.g., paper, Mylar) digital format for computer storage & display

• Vector data capture • Methods

– Digitizing tablet – On screen digitizing using PC

– GPS• Vector data capture

– Scanners• Vector & raster data capture (depends on scanner type)

Digitizing w/ digitizing tablet

http://www.calmit.unl.edu/geog412/Digitizing.pdf

Input Devices : Small format digitizer

http://www.digitizerpro.com/calcomp.htm

Digitizing Tablet

Electronically active table surface– Fine grid of wires acts as a Cartesian

coordinate system – Small & large formats available

http://www.calmit.unl.edu/geog412/Digitizing.pdf

Digitizing Tablet

Puck– Connected to tablet– Records locations from map– Crosshair feature locator– Buttons indicate beginning/ending of

lines/polygons, left/right polygons

Also called “heads-up” digitizing

On-screen digitizing w/ PC

http://www.esri.com/news/arcnews/winter0102articles/epas-clean-water.html

Selection & Use of Digitizers Qualities to be aware of

– Repeatability– Linearity– Resolution– Skew– Stability

Repeatability: Precision; expectation that location data recorded for a single location will be same – Good = 0.001 inch

Linearity: Measure of digitizer’s ability to be within a specified distance (tolerance) of the correct value as the puck is move over large distance– Common tolerance level: 0.003 in over 60 in

Selection & Use of Digitizers Resolution: Digitizer’s ability to record increments of

space– Smaller value higher resolution

For an existing digitizer: Stability: Tendency of reading to change as digitizer

warms up

Skew: Do the results produced have the intended shape?– Rectangular coordinates input rectangular output– Some portions of the tablet can wear out

Input devices: Scanners Types:

– Line-following vector output• Placed on line, moves on small wheels

– Requires technician

• Distance/time intervals dictate coordinates recorded– Problem when line is complex

• Can get confused (convergence/divergence, color contrast)

– Flatbed raster output– Drum scanners

Automated but edits require user intervention

http://www.liv.ac.uk/abe/students/photoshop/images/f05_scanner.jpg

Flatbed scanner & CCD

Inexpensive & commonly available

Use CCD (charge-coupled device)

Output: raster image– Can be converted to vector

CCD

http://www.nortekonline.com/eng/Product/

Input devices: Drum scanner

Scans one line at a time Drum rotates & sensor moves perpendicular to

direction of rotation Can take longer maps than flatbed Output: raster image

– Can be converted to vector

From Fundamentals of Geographic Information Systems, Demers (2005)

Raster, Vector, or both?

Does the project necessitate raster or vector GIS?

Is the system you’ll be using capable of converting back & forth?– Most commercial programs are– Need to be aware of the decision rules

associated with conversion– Might want to test

Conversions

Vector raster “rasterization”– Results good visually– Can be problematic for attribution

• Edges & raster decision rules (“last come, last coded”)

Raster vector “vectorization”– Blocky-looking– Preserves majority of attribute data

Vector raster

http://www.yale.edu/gis/serv_r2v.htm

Raster Vector

Reference Frameworks &Transformations

Digitizing– Records Cartesian coordinates

– Providing projection & zone allows later transformation back to projection

– Inverse map projection: 2-D map projection coord. Decimal Degrees (3-D)

From Fundamentals of Geographic Information Systems, Demers (2005)

Coordinate transformations

Input Output

Coordinate transformations

http://www.progonos.com/furuti/MapProj/Normal/CartHow/cartHow.html

Reference Frameworks & Transformations Primary processes for manipulating

graphics– Translation

– Scale change

– Rotation

With these types of graphical manipulation all necessary transformations

Translation

Relocation of origin on Cartesian surface (X, Y offset values)

From Fundamentals of Geographic Information Systems, Demers (2005)

Scale Change

From Fundamentals of Geographic Information Systems, Demers (2005)

X & Y coordinates are multiplied by a scale factor

Rotation

From Fundamentals of Geographic Information Systems, Demers (2005)

Angular displacement

Used in projection & inverse projection processes

Map Preparation & Digitizing

Map preparation– Have projection, zone, etc. info handy– Identify polygons to digitize & order in which they’ll

be digitized – Plan how to track which sections have been

digitized– Unroll map several hours in advance – Fasten map firmly

• Tape shouldn’t be terribly sticky stretching• Location: several inches from edge

– Identify tic marks– Set tolerance level appropriate for project

Digitizing: Registration

Registration points/tic marks– Tell software where your map area is & its

coordinates– Should be outside any feature to be digitized– Should be located precisely

RMSE: root mean square error– Measure of deviation between known point

location & digitized location– Lower more accurate

Digitizing: What to input

Define project purpose– Make sure data sources address it

Use most accurate maps needed for job– Not necessarily the most accurate existing

Keep coverages simple & specific– Input from same map when reasonable

• Example: USGS topo maps

Digitizing: How much to input Line & polygon complexity

– Record more points for complex objects than for simple lines

– Simple line: 2 points (beginning & end)

From Fundamentals of Geographic Information Systems, Demers (2005)

Digitizing: Inputs & scale

Scale-dependent error: Spatial data error as f(scale of input data)– Lines & symbols take up physical space– Amount of error is related to the scale of

the map• Example: Same size line/symbol takes up

greater amount of space on ground in small-scale map than in large-scale

– Amount of error allowable needs to be taken into account in map preparation process

DigitizingMethods of Input: Vector Tic marks & sequence Puck keys used to indicate

– Points– Lines: beginning & ending– Polygon closure

Inputs may be related to software’s data structure– Examples: Nodes, topology– Note: ArcGIS builds topology on-the-fly

Attribute data: keyboard entry– Make sure they’re attached to entities!

DigitizingMethods of Input: Raster Digitizer records vector & converts to raster Entities & attributes entered at same time

Decisions: Raster cell size Whether compaction method is appropriate & which

to use How grid cells will represent entities

– Class codes & method for assignment Data input method:

– Presence/Absence method– Centroid-of-cell method– Dominant type method– Percent occurrence method

Presence/absence method

From Fundamentals of Geographic Information Systems, Demers (2005)

Decisions made based on whether entity exists within a grid cellEasyBest method for coding points & lines

Centroid of cell method

From Fundamentals of Geographic Information Systems, Demers (2005)

Entity recorded for call only if portion occurs at center of grid cellIntense computationally Should be restricted to polygonal entities

Dominant type method

From Fundamentals of Geographic Information Systems, Demers (2005)

Entity recorded if occupies > 50% grid cellIntense computationally Can be problematic with detailed/complex maps

Percent occurrence method

From Fundamentals of Geographic Information Systems, Demers (2005)

Used only for polygonal dataEach attribute separate coverage greater detailIntense for either computational or visual approach

Notes on--Raster Data Input: Remote Sensing

Image processing software as complementary to GIS– GIS not a substitute

Each grid cell records electromagnetic radiation

Does not need to drive choice of raster data model over vector– Choice should be based on database

purpose

Raster Data Input: Remote Sensing

Aerial photography– Source of base map data for many products check

products 1st

– Distortions caused by scale, relief, tilt

Orthophotos/orthophotoquads– Type of aerial photo

• Corrected for scale, relief, tilt distortion• Available in analog & digital formats

Satellite Imagery– Requires geometric & radiometric processing

• Geometric processing: GCPs

– Classification & accuracy assessment

GPS Data Input

Supports development of highly accurate geodetic control

Links field data collection to locations

Cost & accuracy vary

Secondary Data

Format conversion often required Datasets may be difficult to find

– Result: Data reproduced costly redundancy Data costs & sensitivity may limit access Need to be aware of vendor’s quality control

procedures to be able to judge data quality What type of information included about

data?– Scale, resolution, field names & descriptions,

codes & meaning– Need enough info to be able to make decisions

about whether data use is appropriate

Metadata

Data about data– Content, quality, condition

Component of the GIS data input process ArcCatalog

Why?– Organizations want to maintain their investment– To share information about available data

• Data catalogs & clearinghouses

– To aid data transfer & appropriate use

Pulling it all together Data sources

– Primary – Secondary

Input Methods– Scanners– GPS– Digitizing

Digitizing Process– Vector– Raster

Using Data– Within & across organizations– Metadata!

Raster vs. vector

Raster vs. vector