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Subject:

Data and positional accuracy issues - Digitising Polygons

From:

Iles Peter <[log in to unmask]>

Reply-To:

The Forum for Information Standards in Heritage (FISH)

Date:

Fri, 12 Oct 2001 11:16:13 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (99 lines)

Tactics in Lancashire - I've digitised all the SAM, RPG and Conservation
Area boundaries from maps of different scales, ages and qualities.

First I try and get as modern, clean and clear map as possible from the
responsible body - not always easy, e.g. some SAM maps are still only
available as county series (i.e. pre-national grid) 1:10,560 extracts that
have been copied, written on and copied again and again.  Then I compare the
supplied maps with the 1:10,000 raster maps and OS Landline mapping on my
GIS.  Where there is a reasonable correspondence of Landline Arcs with the
data on the supplied map I then digitise on screen using the Landline data
at 1:500, and follow the appropriate boundaries.  Where there is no
reasonable correspondence - usually due to redevelopment in the area then
you have to make a judgement of which mapping on the GIS to use, or if it is
more appropriate to estimate where the lines should fall, or, in extreme
cases, scan in the supplied map and rubber-sheet it to fit with your GIS
mapping and then digitise over the top of that.  I have also on occasion
used aerial photographic data on a moorland site to try and make the line
drawn around a barrow mean something.  Where possible I digitise at 1:500,
not to give a spurious accuracy to the data but to make sure that I follow
the boundary lines used on the original map.

In all cases it is important to record the scale of the original paper map
and the scale that the digitising was done at.  I also add a date, so that
we know when they were last revised.

Attribute data is attached to the polygons in the same way that you would
add any such data to your GIS, but again acknowledging the source.

In any case I always emphasise that this data is *not* the statutory
information, but a guide to it and if anyone needs a Barrister-Proof
document or map, then they will have to go back to the statutory body, be it
Local Authority or EH.

I presume that this approach is not unique as other SMRs have added these
datasets to their GIS, but thought it might be useful for those who haven't
had to do it yet.

This isn't an real answer to Nick's question/points, but rather a pragmatic
response - i.e. when possible use the most accurate digital dataset but
where that's not possible then use the fuzzy raster ***but make sure you
document it***

Pete Iles
Lancashire SMR

-----Original Message-----
From: garibaldino [mailto:[log in to unmask]]
Sent: 10 October 2001 22:42
To: [log in to unmask]
Subject: Re: Where we are. Understanding data and positional accuracy
issues a t RCAHMS - Part 2 and Summary


Ok as its gone quiet I'll ask a quick question.

When digitising SAM's should we be digitising them based on Raster data or
digital data? As E Lee pointed out, it is only neccessary to put on both
maps to see the disrepancies between the two. And whilst we have argued
about the SAM polygons versus the full description being the monument, I am
using this example, I think, to highlight a wider point.

Given that something is mapped/planned on a more inaccurate base map(ie
raster data), should we correct that in the office to match to more accurate
digital data, or should we be using the same standard for polygonising (ie
stick to the Raster data) until/unless we can re-survey to a more accurate
standard whatever the polygon is supposed to represent? As an example, if a
polygon of an event covers a field on the raster map, can it be mapped using
the digital boundaries of that field and still be correct? Is that even a
valid question or have I missed the point here?

My gut reaction would be to stick to the more inaccurate standard until the
original data can be re-surveyed (if that is possible, which in the case of
eg Excavation trenches it may not be), to represent the fuzziness of the
data. Any other views?

Nick Boldrini


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