As outlined in Chapter 3, most GIS adopt a layer view of the world. Each thematic layer in the data-
base must be encoded, corrected and transformed to create a GIS ready for analysis. To explore how such an integrated database might be created in practice, the Happy Valley case study is considered in Box 5.10.
STAGE 4 – EDITING AND IMPROVEMENT PRISM has search facilities similar to GMS2, together with data editing functions and the ability to create queries. At the end of the surveying various types of analysis can be undertaken in PRISM. On the topo- graphic layer, analysis can be used to assess the quality of the data – for example the number of under- or overshoots, whether features are correctly coded or if the topology is built properly. Drop down menus are used to create queries and results appear as lists of errors that need attention. Each feature on the map also has attribute information attached which indicates when the feature was created or altered and the survey accuracy.
A crucial component in the data is the Topographical Identifier (TOID®). This is an unique identifier for each feature on the map (see Box 3.3). The surveyor has to be aware of this throughout the survey in order to main- tain the lifecycle of a feature. Customers attach their own data to TOIDs, therefore TOIDs need to be main- tained correctly so that customers do not lose the link between the OS and their data.
When the surveyor has finished the data capture and is happy with the editing and improvement func- tions, the data are then transferred back from PRISM to the office server and eventually back to Head Office.
STAGE 5 – EVALUATION
GMS2 is updated to indicate that the footbridge has been surveyed. The attribute data are amended. This
could take the form of archiving the job from GMS2 or amending it if the site needs a further visit in the future (for example to survey additional roads and paths leading to the footbridge).
When both GIS systems have been successfully updated the new data are made available to cus- tomers and the footbridge has finished its journey from plan to MasterMap. The data collection cycle can then begin again for another job.
The future?
The next generation of Pen Tablets should help the OS to develop a seamless database which would benefit Central and Local Government as well as other users.
At the moment, surveyors are restricted to extracting whole maps. When they do this other users in the OS are prevented from accessing the information and carrying out their own processes. The OS wants sur- veyors to use TOIDs to extract only the specific area of data they need thus leaving other information avail- able for others to use. Ultimately, this would benefit customers, because if surveyors can order parts of maps, then customers can be delivered parts of maps, for instance changes only. This reduces the amount of
‘digital traffic’ and makes the whole process cleaner and more efficient for all users.
(Source: Adapted from material provided by Paul Corcoran, Ordnance Survey)
BOX 5.9
The Happy Valley GIS team have a list of data require- ments (Table 5.6). This includes details of the sources and uses of data and details of the entities, data models and attributes required. The data are from
several different sources and require the use of a range of encoding and editing techniques. Some of the data are already in digital form whilst other data are from analogue sources.
BOX 5.10 An integrated GIS
for Happy Valley C ASE STUD
Y
Survey data in analogue form (the ski school and hotel surveys) are encoded by manual keyboard encoding. The roads are manually digitized in-house, and the team experiment with line-following software to automatically digitize the resort boundary. An exter- nal supplier of DTM data is sought and the digital data purchased at a scale compatible with the topographic map used for digitizing roads. An appropriate data format is documented in the licence agreement, which entitles the GIS team to any corrections to the data.
Meteorological station locations are downloaded from a GPS receiver. After processing in the GPS software they are imported to the GIS. In this case attribute
data are available as computer files downloaded from the automatic weather stations. However, only sum- mary data are required in the GIS, so summary statistics are calculated and entered by keyboard encoding to an attribute database. Stereoscopic pairs of aerial photographs are interpreted to produce maps of the ski pistes. These are then encoded by manual digitizing. Finally, the land use data are purchased as a classified satellite image from the local remote sensing data supplier. The team transfer the data electronically to their GIS, then check the data by undertaking some ground truthing of their own using GPS receivers to navigate to predefined sites.
BOX 5.10
TABLE 5.6 Data in the Happy Valley GIS
Name of Source Uses Entity type Data model Attributes
data layer
Infrastructure Scanned from Detailed resort Mixed Raster None 1:5000 scale planning and
plans management
Hotels Accommodation Customer service Point Vector Name, address,
survey carried planning and category (basic,
out by GIS team, management standard or luxury),
postcodes used number of rooms
to identify point locations for hotels
Ski schools GIS team survey Customer service Point Vector Ski school name,
– point locations planning and address, number
as for hotels management of instructors
Meteorological Downloaded from Skiing forecasts and Point Vector Meteorological
GPS readings conditions reporting, Station reference
ski run planning and number, snow cover,
management precipitation, wind
speed and direction,
temperature and sunshine hours
Roads Digitized from Resort planning, Lines Vector Road name and number
1:25,000 paper maps traffic management (network)
Ski pistes Digitized from Ski run planning and Lines Vector Grade of run (green,
aerial photographs management blue, red, black)
Ski resort Digitized from Resort planning and Area Vector Name of resort boundary 1:25,000 paper map management
Topography Downloaded from Ski run and resort Surface Vector/Raster Height purchased 1:25,000 management
DTM
Land use 10-m resolution Vegetation surveys Areas Vector/Raster Land use class
SPOT image, and monitoring, (including agricultural,
ground-truthed environmental forestry, settlement,
with GPS readings assessment, ski run water)
and resort planning/
management
Whilst Box 5.10 provides a hypothetical example of the work involved in the creation of an inte- grated GIS database, the variety and range of methods suggested is typical of real-world GIS applications. For example Petch et al. (1995) describe
how over 30 different data sources to build the GIS database and an equal number of data encoding and editing techniques were necessary to create a GIS for environmental characterization in Zdarske Vrchy (Czech Republic). A map of ecological land-
After considerable effort, the Happy Valley GIS team now have a GIS database populated with data from a range of sources and in various formats and co-ordinate systems. There are vector data input by both manual and automatic digitizing; there are 10- metre resolution raster data sourced from satellite imagery; and there are a number of attribute files attached to vector point, line and area data. The task of the Happy Valley GIS team is to process these data so that they are free from errors (as far as is possible) and are in a common format and frame of spatial ref- erence. The 1:25,000 data from which the DTM and
valley infrastructure data originate are based on the Lambert Conformal Conic projection. This is chosen as the spatial frame of reference onto which all other data not based on this projection will be re-projected.
The roads and boundary data were digitized from more than one map sheet. Thus, edge matching is required. Table 5.7 summarizes all the processes that were necessary for a selection of the data sets.
Datasets and activities relating to the Happy Valley Case Study can be found online at www.pearsoned.
co.uk/heywood.
BOX 5.10
TABLE 5.7 Creating an integrated database for Happy Valley Data set Encoding and editing processes required
Survey data Keyboard encoding of co-ordinate data points into data file
Conversion of data file into GIS data layer
Design and implementation of attribute database
Linking of spatial and attribute data using unique identifiers Meteorological GPS data downloaded into GPS software
stations Processed data transferred to GIS in compatible format
Point data layer created
Processing of attribute data in statistical package
Keyboard encoding of summary attribute data
Linking of spatial and attribute data using unique identifiers Vector road data Manual digitizing
Automatic cleaning and topology generation
Manual on-screen editing to check errors missed and/or created by automatic procedure
Joining of map sheets and edge matching
Re-projection onto Lambert Conformal Conic projection
Creation of attribute database
Linking of spatial and attribute data
Ski pistes Photogrammetric interpretation of stereo pairs of aerial photographs
Manual digitizing of ski pistes
Automatic cleaning and topology generation
Manual on-screen editing to check errors missed and/or created by automatic procedures
Rubber sheeting
Creation of attribute database
Linking of spatial and attribute data
scape zones was encoded by manual digitizing from a paper map (see Figure 1.10a). This map was itself a generalization of field surveys. A forest cover map was captured from remotely sensed data (Landsat TM) updated from more recent aerial photographs (Figure 5.23). The DTM used was interpolated (see Chapter 6) from contours which had been digitized
from topographic maps. These data sets, and the others in the GIS, were re-projected to a common Transverse Mercator projection and transformed to a common scale of 1:50,000. The Zdarske Vrchy project lasted for four years in total, and the first two of these were almost entirely devoted to the data encoding and editing phase of the work.
Figure 5.23 Zdarske Vrchy case study: forest cover, created by reclassifying a Landstat TM scene for the area
Think about your own experiences of data entry and encoding, or the data entry and encoding used in an application with which you are familiar. What errors do you think may have been introduced as data were encoded and edited?
For an application or GIS project of your own choice, make a list of all the data sources you would like to include in your database. Identify all the encoding and editing processes that might be required and create a table with following headings:
REFLECTION BOX
Data set Source Encoding method needed Editing processes required