A few thoughts: 1. The technologies used by OpenSolarMap by Christian Quest and others Etalab.could be applied to OS OpenLocal buildings with a suitable training set. The original French data used high quality imagery classified by cloud sourcing as to roof orientation (flat, E-W or N-S) and then applied this to the rest of France. 2. The available data on installations is via the FIT scheme itself, but is only broken down by postcode district which is really too large for basic searching. A breakdown by postcode sector would be much more helpful & not likely to infringe any privacy aspects. I put a list of the top 25 districts on the wiki. 3. Additional information which could be used to identify candidates are: road orientation (E-W being best); housing age (available for most but not all MSOAs IIRC) with Victorian & pre WWI semis & detached houses being poor candidates, 30s & 70s council house terraces good ones; social housing (I have shape files for England based on NROSH data) as many HAs and at-length council housing arms have been very active in installing solar. 4. I canvassed social housing experts on twitter for likely sites, again skimpily listed on the wiki. 5. The new DG Vivid layers, at least near me, are much more recent and better for seeing rooftop solar installations. 6. Scanning an area you know for rooftop solar installations is not too arduous, and could be done more systematically for smaller areas over the course of the quarter. I think Colm suggested mapping rooftop installations as nodes & I support this (at least in first instance). The huge benefit is that it often highlights other things which may be out-of-date or obviously in need of a survey, so it can fit well with 'local patch' mapping. 7. I hope to soon blog about my analysis of Nottingham solar in terms of these external parameters (FIT installations, housing age, road orientation, social housing etc.). 8. For ground solar, moisture index on Sentinel imagery can be useful to suggest candidates. We now also have access to a cloud free composite of 2018 Sentinel in OSM editors.
Regards, Jerry On Thu, 23 May 2019 at 10:04, Jez Nicholson <jez.nichol...@gmail.com> wrote: > Obviously we are talking about home/small-scale solar here. It could get > quite involved, I'm sure that people are running whole businesses trying to > analyse satellite imagery for this. Need to keep it simple and practical > for this project, unless people have lots of time and energy to spare. > > An analysis (or link to an analysis) of the official stats could be > useful. Exactly how did they make their estimates? > > Another idea: councils are making an effort to put panels on their > properties. Could we FOI request them? or maybe someone has already done so. > > > > On Thu, May 23, 2019 at 8:59 AM Dan S <danstowell+...@gmail.com> wrote: > >> Hi >> >> Related to the idea of solar panel mapping, I've had a request for >> info about what sort of software tools might help support this work. >> We might be using some of the familiar tools (e.g. streetcomplete, >> openinframap, ... even tasking manager?). >> >> It'd be useful to have something like >> completeness-by-postcode-district. Unlike Robert's postbox tools, we >> don't have any official ID numbers for the items-to-map, we just have >> some official stats (to be taken with a pinch of salt) about how many >> are in each postcode district - but still, that could be a start. >> >> I'd also be interested in some tool that predicts where to look, which >> might be based on analysing imagery, but perhaps more realistically >> based on some mix of heuristics and official data. >> >> Any thoughts? >> >> Best >> Dan >> >> _______________________________________________ >> Talk-GB mailing list >> Talk-GB@openstreetmap.org >> https://lists.openstreetmap.org/listinfo/talk-gb >> > _______________________________________________ > Talk-GB mailing list > Talk-GB@openstreetmap.org > https://lists.openstreetmap.org/listinfo/talk-gb >
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