OUTLINE:  geocoding  digitizing terms and methods  scanning methods  adding attributes OUTLINE:  geocoding  digitizing terms and methods  scanning.

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Presentation transcript:

OUTLINE:  geocoding  digitizing terms and methods  scanning methods  adding attributes OUTLINE:  geocoding  digitizing terms and methods  scanning methods  adding attributes D IGITIZING AND S CANNING

 we can buy data, steal it, download it over the internet or collect it ourselves D IGITIZING AND S CANNING

G EOCODING D ATA  conversion of spatial information into digital form  involves capturing the map, and sometimes also capturing the attributes  often involves address matching  method can influence the structure and error associated with the spatial information which results

G EOCODING D ATA  digitizing  scanning  field data collection (remote sensing, geographic databases, field work)

G EOMATIC D ATA Two aspects of geodata:  Spatial: points, lines, and polygons that are referenced to a position on the earth  Attribute: characteristics of the spatial data

D IGITIZING T ERMS TermsExampleDescription ArcLine feature: a node at each end; vertices at each change of direction. NodeEndpoint of an arc (also found at intersections between lines). VertexA point on an arc that signals a change of direction. Pseudo NodeOn an (island) arc that connects to itself. Dangling NodeArc endpoint that is not connected. Label pointIdentifies a point feature or polygon. TicGeographic control point; coverage features can be registered to the same coordinate system.

D IGITIZING AND S CANNING  convert map (analog) data to digital data.  collecting the geometry, attributes, topology.  establishing a geographic frame of reference.

V ECTOR/ M ANUAL D IGITIZING  captures map data by tracing lines from a map by hand  components:  electronically-sensitive tablet or digitizing surface (sizes 12" x 18" -> 36" x 48").  curser with crosshairs and keypad  computer interface

V ECTOR/ M ANUAL D IGITIZING

 trace paper map line by line (vertices and nodes)  one layer at a time  if you have a map with roads, parks, building – do all roads first  control or reference points (3-6) – help line up work from day to day, layer to layer

V ECTOR/ M ANUAL D IGITIZING Vector digitizing steps:  fix to tablet  digitize control  determine coordinate transformation  trace features  proof plot  edit  clean and build (code and add attributes)

V ECTOR/ M ANUAL D IGITIZING  smoothness of lines depends on number of vertices created

D IGITIZING T ABLE  no point in having a table that is much more precise than an operator can point to  digitizing tables need to be calibrated regularly  if map is larger than table, will have problems trying to take the digitized pieces and knit them together

V ECTOR D IGITIZING Point mode: mouse used to record points, points are digitized by placing the cross hairs over the point one wishes to digitize and pressing the button.  record point features  minimizing the size of the data file  accuracy mostly controlled by skill of operators and line weights

V ECTOR D IGITIZING Line mode: (automated mode) – points are recorded at a fixed rate  straight lines usually have few points recorded. Complex areas more points  more operator time, data storage capability and computer processing time

P ROBLEMS  labour intensive  operator fatigue; requirements for accuracy and errors.  topology requirements force extra specifications  sheet matching and registration.  specialized equipment

D IGITIZING E RRORS 1. Missing line

D IGITIZING E RRORS 2. Undershoot

D IGITIZING E RRORS 3. Overshoot

D IGITIZING E RRORS 4. Multiple Identifies (attributes)  associated with undershoots or missing lines

D IGITIZING E RRORS 5. No Identifiers  from simple omission

D IGITIZING E RRORS 6. Extraneous Linework  creates unlabelled polygons

D IGITIZING C ONTROLS  a lot of visual inspection  use software to verify relationships expected to occur  attributes verified by other relationships or brute force inspection.

D IGITIZING C ONTROLS Fuzzy tolerance - minimum distance between all (nodes and vertices) arc coordinates.  typical minimum distance between coordinates.002 inches.  handles small overshoots or undershoots, automatic sliver removal, and coordinate thinning of arcs.  exercise caution when using the fuzzy tolerance

D IGITIZING C ONTROLS Dangle Length - minimum distance between arc coordinates.  a dangling arc has the same polygon on its left and right side. Node match tolerance (snap tolerance) - minimum distance between node features. Weed tolerance - distance between coordinates (vertices) within each arc

H EADS-UP D IGITIZING  looking at monitor  creating new maps by editing existing layers  create zip codes from blocks, create bus line from streets  caution – new maps only as accurate as original  precision dependent on  resolution of the screen (at normal zoom)  resolution of the data on the screen  how easily the operator can point to things.

S CANNING  device that converts maps into digital form  originally single sensor on a drum  uses CCD arrays to record information in binary form (a semi- conductor that translates photons into counts of electrons)

S CANNING

 places a map on a glass plate, and passes a light beam over it  measures the reflected light intensity  result is a grid of pixels  image size and resolution are important  use software to clean up image and transform it from image to data set

S CANNING E XAMPLE

S CANNING  caution – scanner will include the whole map, not individual layers (also include coffee stains, map folds, pencil marks…)  individual layers must be re-traced in computer or extra layers must be digitally erased (cleaned)

A DDING A TTRIBUTES  simple attributes – can be coded at time of digitizing  cursor buttons or menu  extensive attributes – held in a relational database management system (RDMS)  attach feature codes to graphic entities.  attach unique identifiers then enter no-spatial data afterwards.

A VOIDING D IGITIZING/ S CANNING  you can avoid digitizing by finding a source for the digital database "somewhere" out there.  remote sensing or geographical databases