[Talk-GB] Rooftop Solar & UPRNs

[Dan S]

Hi all

The progress on the solar panel mapping is astonishing. I just have
one small observation to add, from our local checking here in London:

A year ago, it seemed there were not many solar panels to spot in
imagery, in central-ish London, plus the imagery wasn't always clear
enough to be sure. Now, the imagery is better, but also - in our own
area of East London it really is increasingly clear that the builders
of new blocks of flats are putting solar panels on top. These can't be
seen from the ground, and none of the new estates' own websites etc
seem to promote it as green credentials. I'm not aware of any local
authority incentives, so perhaps it is becoming more common for these
to simply be part of the build. Will be looking out for those in new
imagery.

Best
Dan

Op za 1 aug. 2020 om 21:12 schreef SK53 <sk53.osm at gmail.com>:
>
> When I wrote to this list at the end of June I little suspected that we'd achieve 25% completion of solar panels by the end of July. Obviously, access to greatly improved imagery has made a big difference.
>
> The places mentioned by Dan : LAs around Exeter & the Midlands now have good coverage. The Devon LAs are all over 60% and other LAs in the county are also progressing. In the Midlands it's easier to list places with low coverage: N. Staffordhsire, most of Shropshire, East Lincs and Northamptonshire.
>
> One of my concerns mentioned last time was missing installations in rural areas. Even with 60% coverage it is noticeable that rural LSOAs are less well populated. I've recently been experimenting to see if this can now be addressed and have good results.
>
> Initially I used areas where OSM has most buildings mapped (Derbyshire Dales near Bakewell & in South Hams between Kingsbridge & Dartmouth). I pull buildings down into JOSM with an Overpass query, and add existing solar mapping. Buildings are selected and added to the to do list (a plugin) & then I step through each building. This was effective, but the bbox of individual LSOAs resulted in very large numbers of buildings (~8000), which is really too many for a single task.
>
> I then turned to UPRNs. It is relatively easy to filter UPRNs by LSOA (e.g., in QGIS) and numbers are more manageable (say 1,500-2,000). Again stepping through these resulted in finding virtually all the solar installations expected from the FIT numbers (tested on East Devon 0009A - Branscombe & Derbyshire Dales 0008C - Tissington & Parwich). However the number of items is still too high even when divided into batches, and requires quite some time to work through.
>
> One problem is the sheer number of UPRNs which are not related to buildings. Numerous minor tracks, possibly some footpaths, farm ponds, mobile phone masts, old quarries etc. These may make up as much as 40% of all UPRNs.
>
> An obvious solution would be to use only UPRNs which pertain to buildings, but I didnt have an OS Local building layer available and even then the total number of search locations is still too high.
>
> Instead I've used clustering of UPRNs which seems to give reasonable results. A simple clustering based on distance yields around 100 clusters which can be searched visually. The non-building UPRNs tend to move the centroid away from groups of buildings, but not so far as to be unworkable.
>
> I've used QGIS so I thought I'd document that approach in case anyone fancies using it in there own area (obviously it can be used for things other than solar):
>
> * Filter UPRNs by LSOA. I use a clipping operation in QGIS. A shapefile of LSOAs is available from the ONS site, but there is also a file of UPRN=>Administrative Geographies which may enable this to be done on a Unix command line.
> * Cluster. Search for clustering on the Toolbox option of the Processing Menu. A number of clustering techniques are available. The one I used is DBSCAN. Open this can apply settings of minimum cluster size of 1 and maximum distance of 0.0025 (approximating 250 m in WGS assuming 100 km / degree). Run the tool and results appear as a new layer. This appears identical to the original UPRNs, but each is now assigned a cluster id.
> * Group Clusters. From the Vector menu apply Collect Geomtetries from the Geometry Tools menu. This returns a MULTIPOINT layer rather than the original POINT layer.
> * Located Centroid. The centroid of each cluster can be found by applying Centroid from the Geometry Tools Menu. This latter layer can be saved as a geojson file for use in JOSM (or iD or Potlatch).
>
> In JOSM:
>
> * Open the geojson of clustered UPRNs.
> * Download existing solar data using an overpass query within the viewport of the LSOA data. Make sure this is a new layer as this is the layer used for editing.
> * Select all items in the UPRN layer and add them to the to do list.
> * Activate the solar data layer.
> * Step through each item in the todo list searching for buildings within a few hundred metres of where JOSM zooms too. Add any rooftop or ground solar panels missing. Using nodes minimises likely conflicts as not all OSM data is loaded.
>
> In practice I'm very conservative with the first 10 or so items in the todo list  and search in a bigger area, but as one steps through the items one can have greater confidence in the localisation of each cluster.
>
> I'm finding over 80% of installations predicted from FIT in very rural LSOAs with this approach. It still needs a bit of refinement, but I think 30 minutes / LSOA is readily achievable. Taken together with the new imagery this bodes much better for coverage of parts of Britain with dispersed rural settlements.
>
> Jerry
>
>
>
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