A.1 BACKGROUND
A considerable part of the input data for the Access model is concerned with defining the geographical characteristics of Sweden, in particular those aspects that have an effect on the cost of provisioning and maintaining the access network. These items include:
• Number of lines.
• The amount if trench required.
• The mix of digging surfaces.
• The distances from NTP14 to SDP/PDP15 and from there to the switch.
This section provides an overview of how these values were derived.
A.2 OVERVIEW
All of the data starts from published or other well known statistics about the country, e.g. the total area, total number of lines, number of scorched nodes. However, customers are not evenly distributed across the country. For example;
• some 80% of the population live in towns and villages (Tatort) of 200 or more people; these 2000 or so Tatort account for just 1-2% of the land area of Sweden. Digging surfaces are likely to be different inside Tatort (more asphalt and concrete) vs., outside Tatort (mostly open terrain).
• a proportion of the country is empty of population and of demand for fixed line telephony; forests (over 50%), mountains (about 15%), lakes (10%), marshland (5%?), etc. Dividing the country into grid squares of 1km2 each, some 75% of these 1km squares are unpopulated. Thinly populated areas will be relatively expensive to service.
• The network of routes for digging trenches can be expected to follow the road network with an additional component for the final drop from street to house. In urban areas, a significant proportion of the road network will require a trench on each side of the road; in rural areas, few roads will require trench on both sides and some road segments with no customers will not require any trench.
This diversity of terrain and population distribution needs to be reflected in the input data used in the model. Most of these calculations were done by selecting a representative sample of 25 of the switch zones in Sweden, in which a wide range of characteristics were to be found – in particular, covering the wide range of teledensities (lines per km2) that occur in Sweden, ranging from city centres with over 10,000 lines per km2 down to remote rural areas with about 0.1 lines per km2.
14 Network Termination Point
A.3 SOURCE DATA: LIST OF SITES WITH GRID REFERENCES AND VOLUMES
The data requested from Telia in September was a list of scorched node sites giving (as a minimum) the following data for each scorched node site:
• Grid reference (nearest 100m grid point would be acceptable).
• Unique identifier for the scorched node site.
• Number of lines.
• plus the area served in km2 and the zone boundary data.
The data was not made available in exactly this form. Instead, the source data for the analysis of switch zones in Sweden was a pair of data files containing the following items:
• File 1 (grid references): a list of scorched node sites containing the following data for each site:
− Grid reference, nearest metre
− Node signature – only about 80% of them unique
− Place name (not all unique).
• File 2 (volumes): a list of scorched node sites containing:
− Node signature, again, not unique
− Place name – again, not unique
− Number of lines.
Match-merging of these two files, to get the definitive list of sites with grid references and volumes, was left to the BUMT.
This was conducted as follows:
• Some 6500 sites could be matched uniquely on node signature to give usable data – grid reference and numbers of lines.
• A number of sites were at the same grid reference, or very close to each other – within 100m. These sites were merged (adding volumes together)
• A number of other sites had grid references but no matching volume data. BUMT decided that these should be counted as sites but that a special handling method was required.
• A number of “sites” had volumes data but no grid references. These present more of a headache; they could be (among other possibilities);
- the unmatched other halves of the sites with gridrefs but no volumes; or
- other genuine sites with missing (but distinct) grid references; or
- additional volumes, that should be added to the existing list of 6500 sites, for example because these sites are FAMs.
…
This gave a list of some 7300 sites, 6500 of which had volumes, as the starting point for the analysis of the zones.
A.4 ESTIMATING THE CATCHMENT AREA OF EACH ZONE
For each scorched node we need to estimate the size of the catchment area that it serves, so that it can be assigned to a geotype (geotypes are based on number of lines per km2). These zone areas were estimated for each zone, based on the following principles:
• Customers can generally be allocated to the switch site nearest to them (with the odd exception where physical barriers make an alternative more economical);
• The catchment area for a switch site will share its borders with (typically) 4-7 neighbouring switch sites;
• The shape of the catchment area for a switch site will typically be an irregular shape of (typically) 4-7 sides, bounded by the borders beyond which a different scorched node is the closest to the customer;
• Limitations of copper technology put a practical limit of about 5km as the crow flies, or 6-7km as the cable route runs, as an upper limit on the boundary of the zone.
The calculations were done as follows:
• Calculate the crow flight distance from each zone to its six nearest neighbours
• For zones that do not have six other sites nearby, set an upper limit on the distance to their nearest neighbours. The figure chosen for this was10km, i.e. a default boundary is drawn at 5km from the node. This also helps to avoid overestimating the area of the zones at the edge of the country as well as those bordering on large empty areas.
• Estimate the size of the catchment area from these distances. The distance to the nearest neighbour has the biggest impact on the size of the catchment area, then the second nearest, etcetera. The overall estimate of the area of the zone is a weighted average of these figures.
A.5 ASSIGNING ZONES TO GEOTYPES BASED ON DISTANCES TO NEAREST