<div dir="ltr">You should also not focus too much on the exact level of accuracy of shapes. What is important is to have relative size, correct placement, but minor architectural details which do not remove the possibility of attaching additional data and does not prevent refining it later ('wheen there's a new need for that and actual usage) is not so important. So when detailing buildings, we just want to know initially how they are separated, soi that we can place addresses, POIs, determine the accesses (if there are pathways between them).<div><br></div><div>This is an estimation anyway given the accuracy of images (and the fact that they will improve later, and orthorectification could slightly evolve over time. Given the resolution of the imagery, an error of less than 10 metres is perfectly acceptable ; a later orthorectrification, based on new terrain model data, could force anyway to slightly slide everything a bit. Then new goals will appear we we want to add more fine-tuined details such as recycling bins, signalisation, pedestrian crossings, stops and giveways, urban equipements, lights, water points, accessibility, or even individual trees if they are part of the landscape and can be used to differentiate various similar places (and notably if the streets are not numbered). Finally people will want to add walls, and barriers, and minor paths, will want to designate lanes, locate parking lots.</div><div><br></div><div>All is not in the first goal of HOT, as most of these are for long term development and it often involves long and costly planning (during that time details even will change, notably after a catastrophic event which requires changing things more radically). We cannot achieve immediately the same level of details we can find in developed countries (where there's also a great help coming from various open datasets, and many contributors capable of using accurate tools.</div><div><br></div><div>In msot places where HOT starts, we just have to use initially limited tools, and all our existing sources are have their own errors an imprecision. The precision improves slowly over time when there are more and more observations and new surveys or datasets are organised. Given the level of emergency for action in most HOT projects, we cannot wait that time. So we do lot of estimations, and it's unavoidable that there will be errors of interpretations, or imprecision. The goals are necessarily limited in scope for HOT, but not for OSM as a whole. But HOT cannot solve everything alone in the given short timeframe.</div><div><br></div><div>Anyway, we can make significant progresses so that local details can more easily be located. Adjustments will then be made progressively everywhere. but there's a general goal to have a basic level of data on which we can provide a consistant map. The work in HOT will never be terminated. And people will more easily be able to work on their local area if they don't have to start from scratch. For that HOT helps by unlocking some imagery sources (but for a limited time, and most often they won't be refreshed for long periods). So all the data will (slowly) degrade in quality over time if this was left as is. But everything still continues progressing because now people can more easily focus on their area and optics of interests (which are not in emergency HOT goals). Some buildings will disappear, others will appear, some will be splitted, new barriers will emerge. And everywhere after a dramatic events, things will evolve more rapidly as people have to take into account new lessons for the past and reorganize themselves.</div><div><br></div><div>But we cannot work anywhere based on just statistic reports. People want to get the hand on how their territory is organized and see what is planned and evaluate the impact in their life. OSM allows this when local governements have hidden many decision in the pat or used biased decision by ignoring large part of their territories and used limited surveys. In additions now most governements cnanot do everything they could do in the past : it is too expensive for them, and not even more reliable. Eerywhere we need cooperation with individuals where they live or where they go or plan to go. Everyone wants to take informed decisions. But the information is generally not available ot not easily accessible (or costly to get).</div><div><br></div><div>As well we know that in most cases we are unable to identify for which goal each building is used. We cannot estimate reliably their current state of usability. This can be done only via long surveys, or by existing open data sets based on surveys or statements made by residents and required by local laws.</div><div><br></div><div>But we need some coherence to the map to allow comparing things: a common basic scheme is required even if some areas are more detailed. OSM in HOT oten focuses on areas that have been forgotten or thought to be negligeable withour risks, or thought to have low value to develop (this is often an error that will concentrate all problems on the same hotspots, and all development to onily a few privileged areas). And it's so easy to forget large areas and most minorities within statistic reports. A map unhides that and reveals the truth to deciders, they cannot lie, they can take more informed decisions, and more easily negociate with people when choices of priority have to be made: it should profit to the maximum so these decisions will be accepted, and what is then built will be respected, or will be safe for long term (and less money will be wasted). There are opportunities of development everywhere, and all territories depend largely of their neighbors, so improving the cooperation and discuting decisions to the large public without lying or hiding the truth under opaque numbers will reveal why things can be done or have to be delayed, or what individual people can do themselves without depending on other's decisions and means.</div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">2018-07-04 14:15 GMT+02:00 Paul Uithol <span dir="ltr"><<a href="mailto:paul.uithol@hotosm.org" target="_blank">paul.uithol@hotosm.org</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div text="#000000" bgcolor="#FFFFFF">
<font size="-1"><font face="Calibri">Hi Jean-Marc,<br>
<br>
Thanks for bringing up the topic in a constructive manner! I do
agree it's valuable to question and examine some of our basic
assumptions sometimes. </font></font><font size="-1"><font face="Calibri"><font size="-1"><font face="Calibri">Please do
keep in mind that to some extent this is still a developing
field. Having access to this type & level of data we are
creating is novel in a lot of contexts, and creating as
comprehensive and reliable datasets as we can is also a
method of </font></font></font></font><font size="-1"><font face="Calibri"><font size="-1"><font face="Calibri"><font size="-1"><font face="Calibri"><font size="-1"><font face="Calibri"> the making it possible for people to
start developing and implementing the use cases for
this data</font></font></font></font>.</font></font>
So to address the "why are we mapping buildings" question, let
me sketch two current use cases where the building footprint
data is being used by NGO and gov't partners:<br>
</font></font>
<ul>
<li><font size="-1"><font face="Calibri">Malaria elimination (and
several other health-related use cases). We've been working
in southern Africa and Mali with various partners to
digitize buildings. This data is amended with data
collection and field mapping exercises, where we record
(amongst other attributes) building and roof materials, number
of rooms, and the number of sleeping spaces (where the
latter two are not public/OSM data). The building outlines </font></font><font size="-1"><font face="Calibri"><font size="-1"><font face="Calibri">(and thus size and shape of buildings)</font></font>
in conjunction with this data allow for much better
extrapolation to inform what type of interventions to apply
to which building, to inform procurement and distribution of
bed nets, insecticide, logistics of spraying teams, etc (see
<a class="m_5006563396908484754moz-txt-link-freetext" href="https://www.hotosm.org/updates/field-surveying-in-botswana-to-support-the-national-malaria-programme/" target="_blank">https://www.hotosm.org/<wbr>updates/field-surveying-in-<wbr>botswana-to-support-the-<wbr>national-malaria-programme/</a>).<br>
</font></font></li>
<li><font size="-1"><font face="Calibri">Rural electrification
(including mini-grids and other sustainable energy options).
Information on estimated number of households, size and
density of villages, estimated number of
public/commercial/industrial buildings, estimated </font></font><font size="-1"><font face="Calibri"><font size="-1"><font face="Calibri">relative </font></font>economic activity/wealth
indicators, in combination with datasets on current
electricity grid and grid expansion planning feeds into
analysis on what which sites would be most attractive/feasible
for small, standalone solar, hydro and wind-powered grids.</font></font><br>
</li>
</ul>
<font size="-1"><font face="Calibri">In some areas, where just
having data is the priority and urgency, we do start out by just
marking `landuse=residential` afaik (see Congo/Ebola recently).
There are however also other datasets available that are
relatively reliable in identifying inhabited areas (such as
WorldPop, GPW, </font></font><font size="-1"><font face="Calibri">HRSL, etc) that can also serve as the basis. So
following up and continuing with digitizing building outlines
where time and (relative) lack of urgency allows does provide a
much improved starting point for additional and more 'advanced'
use of these datasets. Even without any further data on building
use, type, or materials, what improves the use for these
analyses are having access to a) the size of the building, in
order to (for example) estimate which are residential, which are
too small & thus more likely storage/shed/pen etc, and which
are large & more likely to be commercial, industrial or
public buildings, and b) shape of the building (for example,
round vs square). </font></font><font size="-1"><font face="Calibri"><font size="-1"><font face="Calibri">And to
acknowledge another point, yes, AI/ML will come into the
equation (relatively soon, even; way earlier than "ten
years") and we will need to think about how to deal with
this type of 'generated' data, with the OSMF.<br>
<br>
</font></font>Further down the line, the real value in having
a building dataset that includes geometry is that it allows you
much more accurately </font></font><font size="-1"><font face="Calibri"><font size="-1"><font face="Calibri">attach
additional attributes/data to these polygons, in the process
creating a historical record of the existence of this
specific building (which is also useful for land rights/ownership
purposes), and</font></font> enter into a process of
refinement and enrichment of that data.I definitely agree that
trying to get "all" buildings mapped is a herculean task - how
many would there be in total, 3 billion or so? At which point we
get into the really difficult task of trying to keep this
dataset updated and accurate. That doesn't take away from your
point that 'low-quality' mapping, due to a number of reasons and
causes, is a large problem. We are/should be working to improve
mapper retention, upskilling, and make validation more
fun/attractive, but this is a topic others can speak to better
than me. Hope this helps a bit in understanding some of the
reasoning!<br>
<br>
best,<br>
Paul<br>
<br>
</font></font><div><div class="h5"><br>
<div class="m_5006563396908484754moz-cite-prefix">On 4-7-2018 10:16, Jean-Marc Liotier
wrote:<br>
</div>
<blockquote type="cite">
<pre>On Tue, July 3, 2018 7:20 pm, john whelan wrote:
</pre>
<blockquote type="cite">
<pre>I think my concern is more about the 'then a miracle occurs' in the
project plan to clean up the buildings.
</pre>
</blockquote>
<pre>Yes because, among other reasons:
- For most people, verifying is not as gratifying as creating
- Correcting entirely incorrect geometries is many ways more work than
re-creating them from scratch
I am not concerned about the most egregious cases: cars & trucks modelled
as buildings, duplicates & superposed, rubbish heaps and vague shadows as
building=yes, buildings found in old imagery... Those I delete with no
hesitation.
I am not concerned either about minor simplifications or errors such as
the shape being traced on the roof of the building rather than its base -
those I let them be and correcting them capitalizes on a good foundation.
I am concerned about the cases where a building does exist in reality, the
shape is less than ten meters from its position, some of the shape
overlaps the building's position on the imagery and some of the shape
resembles some of the building. In those cases, there is some value in the
record: approximate position and area of the building. But there is also
the liability of having introduced a low-quality object in the database.
I am convinced that the immense majority of those buildings will never be
corrected. In ten years, we can expect massive campaigns of automated
image recognition to produce new building layers - but even then the
extensive conflation will be an horribly tedious job.
Meanwhile, for areas with reliable imagery, I can imagine Maproulette
jobs: something in the spirit of "Does this building at least partially
overlap one in the imagery and does it approximately resemble the one in
the imagery ?". Those jobs could be designed at national or regional
levels - under control of the local communities. They could be a way of
systematic quality control. But maybe I'm horribly deluded about how many
people would volunteer for such a mind-numbing task. Also, looking at
buildings one at a time is very inefficient compared to panning through an
area on JOSM - but then again, JOSM-enabled contributors that might be
motivated for this are not exactly in plentiful supply either.
And that does not even answer the question: what to do with the
"low-quality shape but actually exists" cases ? I am at a loss to answer
that.
______________________________<wbr>_________________
HOT mailing list
<a class="m_5006563396908484754moz-txt-link-abbreviated" href="mailto:HOT@openstreetmap.org" target="_blank">HOT@openstreetmap.org</a>
<a class="m_5006563396908484754moz-txt-link-freetext" href="https://lists.openstreetmap.org/listinfo/hot" target="_blank">https://lists.openstreetmap.<wbr>org/listinfo/hot</a>
</pre>
</blockquote>
<br>
</div></div></div>
<br>______________________________<wbr>_________________<br>
HOT mailing list<br>
<a href="mailto:HOT@openstreetmap.org">HOT@openstreetmap.org</a><br>
<a href="https://lists.openstreetmap.org/listinfo/hot" rel="noreferrer" target="_blank">https://lists.openstreetmap.<wbr>org/listinfo/hot</a><br>
<br></blockquote></div><br></div>