[HOT] Why the HOT obsession with low quality buildings in Africa ?

Wed Jul 4 13:00:20 UTC 2018

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).

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.

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.

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.

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.

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).

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.

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.

2018-07-04 14:15 GMT+02:00 Paul Uithol <paul.uithol at hotosm.org>:

> Hi Jean-Marc,
>
> 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. 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 the making it possible for people to start
> developing and implementing the use cases for this data. 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:
>
>    - 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 (and
>    thus size and shape of buildings) 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
>    https://www.hotosm.org/updates/field-surveying-in-
>    botswana-to-support-the-national-malaria-programme/
>    <https://www.hotosm.org/updates/field-surveying-in-botswana-to-support-the-national-malaria-programme/>
>    ).
>    - 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 relative 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.
>
> 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, 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). 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.
>
> Further down the  line, the real value in having a building dataset that
> includes geometry is that it allows you much more accurately 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 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!
>
> best,
> Paul
>
>
> On 4-7-2018 10:16, Jean-Marc Liotier wrote:
>
> On Tue, July 3, 2018 7:20 pm, john whelan wrote:
>
> I think my concern is more about the 'then a miracle occurs' in the
> project plan to clean up the buildings.
>
> 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.
>
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