Why the HOT obsession with low quality buildings in Africa ?

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Why the HOT obsession with low quality buildings in Africa ?

Jean-Marc Liotier
Active in Senegal and Mali, I have noticed that changesets tagged with
tasking-manager HOT projects produce very large numbers of buildings.
Those buildings appear to be of very low quality. I wonder: who uses
this data ?

If it is only necessary to assess that people live there, then a
landuse=residential is sufficient

If it is necessary to count the number of dwelling units to infer
population, then a node is sufficient (maybe along with an attribute to
discriminate single or multi-tenancy)

If the geometry is actually necessary, then I wonder if anyone is
satisfied with those semi-random shapes that, with some optimism, may be
identified as being in the vicinity of actual buildings (most of the
time)

Enthusiastic contributors expend an awful lot of effort in flooding the
map with low-quality buildings. I have seen ruins, building parts,
walls, vague shadows on the ground, rubbish heaps, market stalls, cars
and trucks all tagged as buildings - and I'll charitably keep from
commenting on the geometric quality of those that attempt to map actual
buildings (and I'll leave aside the issue of HOT leads requiring the use
of outdated imagery such as Bing instead of ESRI World in Bamako). Is it
the most useful way to channel the energy of inexperienced contributors
?

I often find myself wishing that HOT leads introduce them to
Openstreetmap through Osmose quality control rather than by churning out
buildings like demented stonemasons trying to reach their weekly quota
of gamified task-managing !

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Re: Why the HOT obsession with low quality buildings in Africa ?

Phil Wyatt
Hi Jean-Marc

I reckon a good place to start is to look at the project in the Hot Tasking Manager and find out who created the project, and for which organisation. A quick contact with them can probably answer your questions. I suspect the answer will be very different between projects.

The project in Bamako look to have been initiated for OSM Mali by user AKE Amazan

https://tasks.hotosm.org/project/3724 
https://www.openstreetmap.org/user/AKE%20Amazan 

Cheers - Phil

-----Original Message-----
From: Jean-Marc Liotier [mailto:[hidden email]]
Sent: Monday, 2 July 2018 6:25 PM
To: [hidden email]
Cc: [hidden email]
Subject: [HOT] Why the HOT obsession with low quality buildings in Africa ?

Active in Senegal and Mali, I have noticed that changesets tagged with
tasking-manager HOT projects produce very large numbers of buildings.
Those buildings appear to be of very low quality. I wonder: who uses
this data ?

If it is only necessary to assess that people live there, then a
landuse=residential is sufficient

If it is necessary to count the number of dwelling units to infer
population, then a node is sufficient (maybe along with an attribute to
discriminate single or multi-tenancy)

If the geometry is actually necessary, then I wonder if anyone is
satisfied with those semi-random shapes that, with some optimism, may be
identified as being in the vicinity of actual buildings (most of the
time)

Enthusiastic contributors expend an awful lot of effort in flooding the
map with low-quality buildings. I have seen ruins, building parts,
walls, vague shadows on the ground, rubbish heaps, market stalls, cars
and trucks all tagged as buildings - and I'll charitably keep from
commenting on the geometric quality of those that attempt to map actual
buildings (and I'll leave aside the issue of HOT leads requiring the use
of outdated imagery such as Bing instead of ESRI World in Bamako). Is it
the most useful way to channel the energy of inexperienced contributors
?

I often find myself wishing that HOT leads introduce them to
Openstreetmap through Osmose quality control rather than by churning out
buildings like demented stonemasons trying to reach their weekly quota
of gamified task-managing !

_______________________________________________
HOT mailing list
[hidden email]
https://lists.openstreetmap.org/listinfo/hot


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Re: Why the HOT obsession with low quality buildings in Africa ?

AMEGAYIBO Kokou ELolo
Hi Jean-Marc, 
The majority of these tasks were created in training workshops on OpenStreetMap in Bamako, quality control work is done afterwards by the local community normally. I share your points of view, but for training workshops it is our best method to channel, control the work of the newbies and also familiarize them with the use of the Tasking Manager. I am open to any contribution who can help us  improving our approach.
Best regard,
Le lun. 2 juil. 2018 à 08:51, Phil Wyatt <[hidden email]> a écrit :
Hi Jean-Marc

I reckon a good place to start is to look at the project in the Hot Tasking Manager and find out who created the project, and for which organisation. A quick contact with them can probably answer your questions. I suspect the answer will be very different between projects.

The project in Bamako look to have been initiated for OSM Mali by user AKE Amazan

https://tasks.hotosm.org/project/3724
https://www.openstreetmap.org/user/AKE%20Amazan

Cheers - Phil

-----Original Message-----
From: Jean-Marc Liotier [mailto:[hidden email]]
Sent: Monday, 2 July 2018 6:25 PM
To: [hidden email]
Cc: [hidden email]
Subject: [HOT] Why the HOT obsession with low quality buildings in Africa ?

Active in Senegal and Mali, I have noticed that changesets tagged with
tasking-manager HOT projects produce very large numbers of buildings.
Those buildings appear to be of very low quality. I wonder: who uses
this data ?

If it is only necessary to assess that people live there, then a
landuse=residential is sufficient

If it is necessary to count the number of dwelling units to infer
population, then a node is sufficient (maybe along with an attribute to
discriminate single or multi-tenancy)

If the geometry is actually necessary, then I wonder if anyone is
satisfied with those semi-random shapes that, with some optimism, may be
identified as being in the vicinity of actual buildings (most of the
time)

Enthusiastic contributors expend an awful lot of effort in flooding the
map with low-quality buildings. I have seen ruins, building parts,
walls, vague shadows on the ground, rubbish heaps, market stalls, cars
and trucks all tagged as buildings - and I'll charitably keep from
commenting on the geometric quality of those that attempt to map actual
buildings (and I'll leave aside the issue of HOT leads requiring the use
of outdated imagery such as Bing instead of ESRI World in Bamako). Is it
the most useful way to channel the energy of inexperienced contributors
?

I often find myself wishing that HOT leads introduce them to
Openstreetmap through Osmose quality control rather than by churning out
buildings like demented stonemasons trying to reach their weekly quota
of gamified task-managing !

_______________________________________________
HOT mailing list
[hidden email]
https://lists.openstreetmap.org/listinfo/hot


_______________________________________________
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[hidden email]
https://lists.openstreetmap.org/listinfo/hot

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Re: Why the HOT obsession with low quality buildings in Africa ?

Palolo
In reply to this post by Jean-Marc Liotier
When you say "low quality" buildings, do you mean the quality of the polygon data or are you judging someone's home to be of low value?

On Mon, Jul 2, 2018 at 1:24 AM, Jean-Marc Liotier <[hidden email]> wrote:
Active in Senegal and Mali, I have noticed that changesets tagged with
tasking-manager HOT projects produce very large numbers of buildings.
Those buildings appear to be of very low quality. I wonder: who uses
this data ?

If it is only necessary to assess that people live there, then a
landuse=residential is sufficient

If it is necessary to count the number of dwelling units to infer
population, then a node is sufficient (maybe along with an attribute to
discriminate single or multi-tenancy)

If the geometry is actually necessary, then I wonder if anyone is
satisfied with those semi-random shapes that, with some optimism, may be
identified as being in the vicinity of actual buildings (most of the
time)

Enthusiastic contributors expend an awful lot of effort in flooding the
map with low-quality buildings. I have seen ruins, building parts,
walls, vague shadows on the ground, rubbish heaps, market stalls, cars
and trucks all tagged as buildings - and I'll charitably keep from
commenting on the geometric quality of those that attempt to map actual
buildings (and I'll leave aside the issue of HOT leads requiring the use
of outdated imagery such as Bing instead of ESRI World in Bamako). Is it
the most useful way to channel the energy of inexperienced contributors
?

I often find myself wishing that HOT leads introduce them to
Openstreetmap through Osmose quality control rather than by churning out
buildings like demented stonemasons trying to reach their weekly quota
of gamified task-managing !

_______________________________________________
HOT mailing list
[hidden email]
https://lists.openstreetmap.org/listinfo/hot


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Re: Why the HOT obsession with low quality buildings in Africa ?

Ralph Aytoun-2
In reply to this post by Jean-Marc Liotier

To help those highly experienced and very accurate OSM mappers understand better what is happening.

 

I have been a cartographer all my life, but I retired before being retrained and integrated into the world of GIS programmes so I am not as tech savvy as modern day mappers. When I started out mapping with OSM I used Potlach, sitting at home by myself, self teaching as I progressed and, while knowing that the building corners should be squared I did not know that there was a special way of doing this so tried to get as accurate as I could by eye. Until I got a polite message from sev_osm telling me about the squaring facility on Potlach. I was very grateful for that help which made a big difference to my speed and accuracy.

 

These local people and new mappers that are learning to add detail to OSM do not have the advantage of having a mapping background so have an even steeper learning curve than I did. They are eager, they are keen AND they are willing to learn. So if there are inconsistencies while we are expanding the OSM community into more remote areas then I for one am able to live with that. The fact that the people who are using the data being input (Medicins sans Frontieres, Red Cross, The Clinton Foundation’s Eliminate Malaria Campaign, to name a few) seem to cope with those inconsistencies, makes it reasonable to continue.

 

Our track record shows that we are gradually increasing the retention rate of new mappers from the original low of 10% and these new mappers are teaching new mappers as well bears good for the growth of the OSM community in those countries.

 

As has happened in the past and will continue to happen in the future, once those communities, roads and buildings are on the map they DO get added to and improved as local communities grow and take charge of mapping their own countries. If they were not there then there is nothing to improve on or add to, so simply having imperfect mapping is the start to getting accurate maps.

 

As to using ESRI I am sorry to have to point out that it is not the HOLY GRAIL of mapping and in many parts it is non-existent or low resolution. We do try to map to the latest high resolution mapping available. And switching between imageries is not the best answer because they do not align easily with each other and the rescaling adjustments vary quite a lot so that a building on one set of imagery may be much smaller than that same building on other imagery at the same zoom level. There are also major hiccups where imagery tiles join with offsets of 30+ metres.

 

So please be patient and allow these communities to grow and adjust to the accuracy of our high tech worlds. Their mud buildings do get pulled down and rebuilt, their unsurfaced roads get rerouted when the rainy season turns the existing road into a quagmire. But inaccurate buildings and roads do help aid agencies get a rough estimate of the population size and how to get there, something they could not do if there was nothing there. These communities are still trying to find out what they have got and where it is.

 

OpenStreetMap is growing and we have to be patient as other parts of the world try to catch up with us.

 

Ralph Aytoun

Associate Member of OpenStreetMap Foundation

Voting Member of Humanitarian OpenStreetMap Team

Tutor/Validator Supervisor for Missing Maps London

Member of the HOT Training Working Group

Advisor to West African Motorbike Mappers in Sierra Leone

Validator for Crowd2Map in Tanzania

 

Date: Mon, 2 Jul 2018 10:24:52 +0200

From: Jean-Marc Liotier <[hidden email]>

Subject: [HOT] Why the HOT obsession with low quality buildings in

                Africa ?

Active in Senegal and Mali, I have noticed that changesets tagged with

tasking-manager HOT projects produce very large numbers of buildings.

Those buildings appear to be of very low quality. I wonder: who uses

this data ?

 

If it is only necessary to assess that people live there, then a

landuse=residential is sufficient

 

If it is necessary to count the number of dwelling units to infer

population, then a node is sufficient (maybe along with an attribute to

discriminate single or multi-tenancy)

 

If the geometry is actually necessary, then I wonder if anyone is

satisfied with those semi-random shapes that, with some optimism, may be

identified as being in the vicinity of actual buildings (most of the

time)

 

Enthusiastic contributors expend an awful lot of effort in flooding the

map with low-quality buildings. I have seen ruins, building parts,

walls, vague shadows on the ground, rubbish heaps, market stalls, cars

and trucks all tagged as buildings - and I'll charitably keep from

commenting on the geometric quality of those that attempt to map actual

buildings (and I'll leave aside the issue of HOT leads requiring the use

of outdated imagery such as Bing instead of ESRI World in Bamako). Is it

the most useful way to channel the energy of inexperienced contributors

?

 

I often find myself wishing that HOT leads introduce them to

Openstreetmap through Osmose quality control rather than by churning out

buildings like demented stonemasons trying to reach their weekly quota

of gamified task-managing !

 


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Re: Why the HOT obsession with low quality buildings in Africa ?

Jean-Marc Liotier
In reply to this post by Palolo
On Mon, July 2, 2018 2:59 pm, Vao Matua wrote:
> When you say "low quality" buildings, do you mean the quality of the
> polygon data or are you judging someone's home to be of low value?

The tracing of course - mud shacks and posh villas are all equal before
Openstreetmap contributors !


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Re: Why the HOT obsession with low quality buildings in Africa ?

Jean-Marc Liotier
In reply to this post by AMEGAYIBO Kokou ELolo
On Mon, July 2, 2018 11:55 am, AMEGAYIBO Kokou ELolo wrote:
>
> The majority of these tasks were created in training workshops on
> OpenStreetMap in Bamako, quality control work is done afterwards by the
> local community normally. I share your points of view, but for training
> workshops it is our best method to channel, control the work of the
> newbies and also familiarize them with the use of the Tasking Manager.
> I am open to any contribution who can help us improving our approach.

I understand the difficulty of getting large numbers of new contributors
started with Openstreetmap - mistakes are normal and must be accepted as a
cost of growing the project. Nevertheless, I think that there are ways to
keep that cost lower.

First, and most important, I believe that quality control should not be
relegated to "done afterwards" - especially with less proficient
contributors who are most likely to make mistakes, and especially if they
are enthusiastic (it pains me to see incredible dedication in go to
waste). Quality control must be an integral part of the contribution and
that must be drilled into new contributors as early as possible. Insist on
using the JOSM Validator, have the users look at their own contributions
on Osmose... Show them how to be more responsible of their own work ! Or
course, having experienced users supervise is valuable but they are a
scarce resource and most importantly they risk infantilizing less
experienced contributors. Most of my own contributions start with looking
at Osmose, seeing a bunch of errors and I start editing there... Quality
control is a core skill for everyone, at every level of proficiency.

Second, have users. Creating data costs, maintaining it costs... Why are
we doing it ? We are doing it for users. How do we judge quality ? I am as
fond of the map as an aesthetic object as anyone here but we all agree
that we want to put our efforts to good uses - so we judge quality by the
fitness of the product for a particular use. If the data has no users, it
is dead data.  For example, as a user, I am a walker and a cyclist - I
enjoy buildings on the map as landmarks to help me navigate... That is my
personal way of judging quality - but other users may have other ways: to
some users the purpose of having buildings in Openstreetmap may just be
"there is a building here and its shape is not that important" - and maybe
those users are the majority, who knows ? So, as a producer of data, be
aware of how the data is used - that is the key to rational quality
control. That remains true if you just chose the buildings as a new
contributor training object.

Third, make sure that the most recent imagery of decent quality is used.
For the specific case of Bamako and at the current time, ESRI World is
better than Bing: https://i.imgur.com/w6YBG70.jpg - of course, this is
subject to change over time. In understand that, for lack of available
properly surveyed geodesic reference points, large numbers of users
working with multiple sources of imagery generates its own challenges (I
found that particularly frustrating in Dakar's suburbs).

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Re: Why the HOT obsession with low quality buildings in Africa ?

verdy_p
In reply to this post by Jean-Marc Liotier
I don't understand why the title speaks about an "obsession" when in fact it just defines the minimum goal expected fo manage emergencies; OSM is incremental can then continue building up on this base, including during emergencies to requalify and add precision where needed by the emergency teams. Locally they actively enhance the crowdsourced data, and even then the local groups and world contributors can add their own work.
HOT is all about creating oppotunities to start with a solid base from which we can develop new targets (not just for the recovery, but for longer term development or conservation, or for planning, or new commercial initiatives or to help better define new needs and help coordinate the actions of different actors (with a faster response and more savings on exploitation costs, human resources, or fine tuning and monitoring the budgets and avoid wasting precious ressources that will be more useful elsewhere instead of profiting only to small selected communities).

2018-07-02 16:25 GMT+02:00 Jean-Marc Liotier <[hidden email]>:
On Mon, July 2, 2018 2:59 pm, Vao Matua wrote:
> When you say "low quality" buildings, do you mean the quality of the
> polygon data or are you judging someone's home to be of low value?

The tracing of course - mud shacks and posh villas are all equal before
Openstreetmap contributors !


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Re: Why the HOT obsession with low quality buildings in Africa ?

Lists-3
In reply to this post by Jean-Marc Liotier
I concur with the points made by Jean-Marc Liotier. As Deming said in the 50's, it is important to build quality into the process, not depend on checks after the fact.

Along those lines, I still think that we could have an AI program do a big part of the initial mapping.


Bryan Sayer 


-------- Original message --------
From: Jean-Marc Liotier <[hidden email]>
Date: 07/02/2018 10:58 AM (GMT-05:00)
To: AMEGAYIBO Kokou ELolo <[hidden email]>
Cc: [hidden email], [hidden email]
Subject: Re: [HOT] Why the HOT obsession with low quality buildings in Africa ?

On Mon, July 2, 2018 11:55 am, AMEGAYIBO Kokou ELolo wrote:
>
> The majority of these tasks were created in training workshops on
> OpenStreetMap in Bamako, quality control work is done afterwards by the
> local community normally. I share your points of view, but for training
> workshops it is our best method to channel, control the work of the
> newbies and also familiarize them with the use of the Tasking Manager.
> I am open to any contribution who can help us improving our approach.

I understand the difficulty of getting large numbers of new contributors
started with Openstreetmap - mistakes are normal and must be accepted as a
cost of growing the project. Nevertheless, I think that there are ways to
keep that cost lower.

First, and most important, I believe that quality control should not be
relegated to "done afterwards" - especially with less proficient
contributors who are most likely to make mistakes, and especially if they
are enthusiastic (it pains me to see incredible dedication in go to
waste). Quality control must be an integral part of the contribution and
that must be drilled into new contributors as early as possible. Insist on
using the JOSM Validator, have the users look at their own contributions
on Osmose... Show them how to be more responsible of their own work ! Or
course, having experienced users supervise is valuable but they are a
scarce resource and most importantly they risk infantilizing less
experienced contributors. Most of my own contributions start with looking
at Osmose, seeing a bunch of errors and I start editing there... Quality
control is a core skill for everyone, at every level of proficiency.

Second, have users. Creating data costs, maintaining it costs... Why are
we doing it ? We are doing it for users. How do we judge quality ? I am as
fond of the map as an aesthetic object as anyone here but we all agree
that we want to put our efforts to good uses - so we judge quality by the
fitness of the product for a particular use. If the data has no users, it
is dead data.  For example, as a user, I am a walker and a cyclist - I
enjoy buildings on the map as landmarks to help me navigate... That is my
personal way of judging quality - but other users may have other ways: to
some users the purpose of having buildings in Openstreetmap may just be
"there is a building here and its shape is not that important" - and maybe
those users are the majority, who knows ? So, as a producer of data, be
aware of how the data is used - that is the key to rational quality
control. That remains true if you just chose the buildings as a new
contributor training object.

Third, make sure that the most recent imagery of decent quality is used.
For the specific case of Bamako and at the current time, ESRI World is
better than Bing: https://i.imgur.com/w6YBG70.jpg - of course, this is
subject to change over time. In understand that, for lack of available
properly surveyed geodesic reference points, large numbers of users
working with multiple sources of imagery generates its own challenges (I
found that particularly frustrating in Dakar's suburbs).

_______________________________________________
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[hidden email]
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Re: Why the HOT obsession with low quality buildings in Africa ?

Rupert Allan-4
Two words: Disaster Response

Although OSM will break down without its hard-won reputation for accuracy, there is also the case for 'some data being better than no data'. It's the old argument, I think, but for us this data is vital, however incomplete. We work with aggregated data:

Building materials and standards are used to map: Cholera, Malaria, Earthquake risk, general poverty levels, flood risk, vulnerability to infection, TB outbreaks, population per building, whether structures are temporary (refugee) permanent (hosting community), fire risk (spreading). These are practical/technical elements not always at the forefront of the digital mind.
When we plan a $10million intervention with only $3million, we need to know the areas where there is most risk.

A simple look at OSM metrics of, say, thousands of grass rooves amongst tin rooves in a fire, or hundreds of mud walls instead of concrete in an immanent flood, really helps. At this point, this data directly impacts and/or saves thousands of lives.

That's my obsession.

Best,

Rupert
Rupert Allan
Country Manager - Uganda
E-Mail: [hidden email]
Uganda:+256777656999 (mtn) /+256792297795 (africell)
UK: +447970540647
Skype: Reuben Molotov
HOT Uganda  
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On Tue, Jul 3, 2018 at 7:12 AM Lists <[hidden email]> wrote:
I concur with the points made by Jean-Marc Liotier. As Deming said in the 50's, it is important to build quality into the process, not depend on checks after the fact.

Along those lines, I still think that we could have an AI program do a big part of the initial mapping.


Bryan Sayer 


-------- Original message --------
From: Jean-Marc Liotier <[hidden email]>
Date: 07/02/2018 10:58 AM (GMT-05:00)
To: AMEGAYIBO Kokou ELolo <[hidden email]>
Cc: [hidden email], [hidden email]
Subject: Re: [HOT] Why the HOT obsession with low quality buildings in Africa ?

On Mon, July 2, 2018 11:55 am, AMEGAYIBO Kokou ELolo wrote:
>
> The majority of these tasks were created in training workshops on
> OpenStreetMap in Bamako, quality control work is done afterwards by the
> local community normally. I share your points of view, but for training
> workshops it is our best method to channel, control the work of the
> newbies and also familiarize them with the use of the Tasking Manager.
> I am open to any contribution who can help us improving our approach.

I understand the difficulty of getting large numbers of new contributors
started with Openstreetmap - mistakes are normal and must be accepted as a
cost of growing the project. Nevertheless, I think that there are ways to
keep that cost lower.

First, and most important, I believe that quality control should not be
relegated to "done afterwards" - especially with less proficient
contributors who are most likely to make mistakes, and especially if they
are enthusiastic (it pains me to see incredible dedication in go to
waste). Quality control must be an integral part of the contribution and
that must be drilled into new contributors as early as possible. Insist on
using the JOSM Validator, have the users look at their own contributions
on Osmose... Show them how to be more responsible of their own work ! Or
course, having experienced users supervise is valuable but they are a
scarce resource and most importantly they risk infantilizing less
experienced contributors. Most of my own contributions start with looking
at Osmose, seeing a bunch of errors and I start editing there... Quality
control is a core skill for everyone, at every level of proficiency.

Second, have users. Creating data costs, maintaining it costs... Why are
we doing it ? We are doing it for users. How do we judge quality ? I am as
fond of the map as an aesthetic object as anyone here but we all agree
that we want to put our efforts to good uses - so we judge quality by the
fitness of the product for a particular use. If the data has no users, it
is dead data.  For example, as a user, I am a walker and a cyclist - I
enjoy buildings on the map as landmarks to help me navigate... That is my
personal way of judging quality - but other users may have other ways: to
some users the purpose of having buildings in Openstreetmap may just be
"there is a building here and its shape is not that important" - and maybe
those users are the majority, who knows ? So, as a producer of data, be
aware of how the data is used - that is the key to rational quality
control. That remains true if you just chose the buildings as a new
contributor training object.

Third, make sure that the most recent imagery of decent quality is used.
For the specific case of Bamako and at the current time, ESRI World is
better than Bing: https://i.imgur.com/w6YBG70.jpg - of course, this is
subject to change over time. In understand that, for lack of available
properly surveyed geodesic reference points, large numbers of users
working with multiple sources of imagery generates its own challenges (I
found that particularly frustrating in Dakar's suburbs).

_______________________________________________
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Re: Why the HOT obsession with low quality buildings in Africa ?

mohamet lamine Ndiaye
Hello everyone,
I am Mohamet Lamine Ndiaye, a founding member of the Openstreetmap Senegal community and the main contributor on the mapping of the Bâtit at the level of the suburbs of Dakar.
Thank you Jean Marc for your comments and I think this is the umpteenth time we talk about it and during your last visit to Dakar you could hold a training on advanced editing techniques JOSM and quality control with OSMOSE and this has been a great contribution to the quality of the work.
However, it should be noted that in terms of the quality of the images and the density of the mapping areas, the contributors find it difficult to distinguish the actual boundaries of the Buildings from the actual impact on the quality of the building. Nevertheless, this does not preclude the use of these data in large-scale and highly resilient projects for the populations.
The Sunugox project at the level of the Dakar Suburbs in five communes financed by the European Union is done on the basis of this mapping and the results were conclusive. Another example, as part of the World Bank's Open Cities project, the basic data are those that have been mapped by the community at Saint Louis since 2014. And a work of updates will be done by the people. speakers at the project level. This is basically what motivates this work of mapping buildings.
Today, if we have drones imgeries we could make updates but also the fact that projects use this basic data.
Today, the availability of drone imgeries or the fact that projects use this basic data could help update the data and also meet the aesthetic needs.
Other things, you should know that there are neighborhoods that do not benefit from subdivision and non-harmonized architecture of some lots do not promote aesthetics.
Having contributed to several activations, the quality of the images and the level of resolution found in these areas is greater than that of our countries and this affects the level of detail. So many parameters to take into account.
What is important for me is that we have to start with something and although these data are of inferior quality, they respond to operational needs on the ground in case of disaster or flood for the organizations that intervene on the zone.Also if we have data released by the cadastre we will be able to make updates based on the subdivision and this will answer the aesthetic concerns. For that, an important advocacy work will have to be done at the level of the public authorities.


2018-07-03 8:46 GMT+00:00 Rupert Allan <[hidden email]>:
Two words: Disaster Response

Although OSM will break down without its hard-won reputation for accuracy, there is also the case for 'some data being better than no data'. It's the old argument, I think, but for us this data is vital, however incomplete. We work with aggregated data:

Building materials and standards are used to map: Cholera, Malaria, Earthquake risk, general poverty levels, flood risk, vulnerability to infection, TB outbreaks, population per building, whether structures are temporary (refugee) permanent (hosting community), fire risk (spreading). These are practical/technical elements not always at the forefront of the digital mind.
When we plan a $10million intervention with only $3million, we need to know the areas where there is most risk.

A simple look at OSM metrics of, say, thousands of grass rooves amongst tin rooves in a fire, or hundreds of mud walls instead of concrete in an immanent flood, really helps. At this point, this data directly impacts and/or saves thousands of lives.

That's my obsession.

Best,

Rupert
Rupert Allan
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On Tue, Jul 3, 2018 at 7:12 AM Lists <[hidden email]> wrote:
I concur with the points made by Jean-Marc Liotier. As Deming said in the 50's, it is important to build quality into the process, not depend on checks after the fact.

Along those lines, I still think that we could have an AI program do a big part of the initial mapping.


Bryan Sayer 


-------- Original message --------
From: Jean-Marc Liotier <[hidden email]>
Date: 07/02/2018 10:58 AM (GMT-05:00)
To: AMEGAYIBO Kokou ELolo <[hidden email]>
Cc: [hidden email], [hidden email]
Subject: Re: [HOT] Why the HOT obsession with low quality buildings in Africa ?

On Mon, July 2, 2018 11:55 am, AMEGAYIBO Kokou ELolo wrote:
>
> The majority of these tasks were created in training workshops on
> OpenStreetMap in Bamako, quality control work is done afterwards by the
> local community normally. I share your points of view, but for training
> workshops it is our best method to channel, control the work of the
> newbies and also familiarize them with the use of the Tasking Manager.
> I am open to any contribution who can help us improving our approach.

I understand the difficulty of getting large numbers of new contributors
started with Openstreetmap - mistakes are normal and must be accepted as a
cost of growing the project. Nevertheless, I think that there are ways to
keep that cost lower.

First, and most important, I believe that quality control should not be
relegated to "done afterwards" - especially with less proficient
contributors who are most likely to make mistakes, and especially if they
are enthusiastic (it pains me to see incredible dedication in go to
waste). Quality control must be an integral part of the contribution and
that must be drilled into new contributors as early as possible. Insist on
using the JOSM Validator, have the users look at their own contributions
on Osmose... Show them how to be more responsible of their own work ! Or
course, having experienced users supervise is valuable but they are a
scarce resource and most importantly they risk infantilizing less
experienced contributors. Most of my own contributions start with looking
at Osmose, seeing a bunch of errors and I start editing there... Quality
control is a core skill for everyone, at every level of proficiency.

Second, have users. Creating data costs, maintaining it costs... Why are
we doing it ? We are doing it for users. How do we judge quality ? I am as
fond of the map as an aesthetic object as anyone here but we all agree
that we want to put our efforts to good uses - so we judge quality by the
fitness of the product for a particular use. If the data has no users, it
is dead data.  For example, as a user, I am a walker and a cyclist - I
enjoy buildings on the map as landmarks to help me navigate... That is my
personal way of judging quality - but other users may have other ways: to
some users the purpose of having buildings in Openstreetmap may just be
"there is a building here and its shape is not that important" - and maybe
those users are the majority, who knows ? So, as a producer of data, be
aware of how the data is used - that is the key to rational quality
control. That remains true if you just chose the buildings as a new
contributor training object.

Third, make sure that the most recent imagery of decent quality is used.
For the specific case of Bamako and at the current time, ESRI World is
better than Bing: https://i.imgur.com/w6YBG70.jpg - of course, this is
subject to change over time. In understand that, for lack of available
properly surveyed geodesic reference points, large numbers of users
working with multiple sources of imagery generates its own challenges (I
found that particularly frustrating in Dakar's suburbs).

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Re: Why the HOT obsession with low quality buildings in Africa ?

Jean-Marc Liotier
In reply to this post by Rupert Allan-4
On Tue, July 3, 2018 10:46 am, Rupert Allan wrote:
>
> [..] 'some data being better than no data' [..]

Yes but, in that case, landuse combined with density and/or building type
attributes do the job more cheaply and with none of the low quality
stigma. But, of course, there may be other reasons for insisting on
building shapes.

> Building materials and standards are used to map [..]
> A simple look at OSM metrics of, say, thousands of
> grass rooves amongst tin rooves in a fire, or hundreds of mud
> walls instead of concrete in an immanent flood, really helps.
> At this point, this data directly impacts
> and/or saves thousands of lives.
>
> That's my obsession.
>
> *Rupert Allan*
> Country Manager - Uganda

While building=hut is a useful distinction that is widely recorded in
relevant locations
(https://taginfo.openstreetmap.org/tags/building=hut#map, the
building=material you seem to refer to is actually not very popular
outside of Europe
(https://taginfo.openstreetmap.org/keys/building%3Amaterial#map) - in your
country it only appears 693 times (http://overpass-turbo.eu/s/A2C)

Most of the buildings I seen in Senegal and Mali are building=yes with no
other attribute... So, for now at least, this is not a question of
building materials.


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Re: Why the HOT obsession with low quality buildings in Africa ?

Jean-Marc Liotier
In reply to this post by mohamet lamine Ndiaye
On Tue, July 3, 2018 3:56 pm, mohamet lamine Ndiaye wrote:
> I am Mohamet Lamine Ndiaye [..]

Nangadef, I'm happy to hear from you - it has been a long time !

> [..] I think this is the umpteenth time we talk about it

Yes, this is a pet issue of mine - I hope that one day I'll understand why
you all seem to put so much time and energy into those buildings that I'm
not happy about... But hopefully they make other people happy !

> [..] However, it should be noted that in terms of the quality of the
> images and the density of the mapping areas, the contributors find it
> difficult to distinguish the actual boundaries of the Buildings

Yes - and distinguishing between building parts and the whole buildings is
a challenge for even the keenest eye.

> [..] Nevertheless, this does not preclude the use of these data in
> large-scale and highly resilient projects for the populations.

Do you have examples of use of that data ? That would help me understand
the benefits of mapping buildings even if they are approximate.

> [..] Other things, you should know that there are neighborhoods that do
> not benefit from subdivision and non-harmonized architecture of some lots
> do not promote aesthetics.

Indeed, the less orthogonal parts of town are a great challenge. Odette
(who is currently doing an internship at my company) told me about her
experience updating the cadastre in Ngor - it was a nightmare and they had
excellent drone imagery... So for an Openstreetmap contributor with only
orbital imagery it is simply impossible to do right - which is why I
wonder: instead of that herculean effort, why not settle for a simpler
model that provides the same data at a granularity closer to what our
resources let us record with adequate quality ?

> [..] What is important for me is that we have to start with something
> and although these data are of inferior quality, they respond to
> operational needs on the ground in case of disaster

A landuse=residential with residential=* (currently values of
residential=* are mostly "rural" and "urban" but a finer-grained
nomenclature could be designed such as "sparse single family", "dense
single family", "sparse urban", "dense urban") would provide approximate
population impact calculations at a fraction of the effort and without the
side effect of producing low quality buildings. Of course, buildings offer
much better precision - but only if they are actually precise: if a
building is mapped as two rectangles and the two sheds in the courtyard
are also mapped as generic buildings, is the result less precise than the
surfacic approximation ?

Sure, quite a few contributors do excellent work - but there is currently
not enough of them available to perform the huge task with high precision
everywhere.

> if we have data released by the cadastre

If you ever get your hands on that, I will be mightily impressed by your
advocacy work... So far I failed at getting even a simple list of street
references so I find difficult to imagine the day when Senegalese and
Malian government agencies will release cadastre and geodesic network. I'm
glad that you remain optimist... And after all, before French contributors
got their hands on IGN orthophotography and vector cadastre, many of us
(including me) didn't think it was possible - and then it happened thanks
to the efforts of the optimists and stubborn among us !


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Re: Why the HOT obsession with low quality buildings in Africa ?

Jean-Marc Liotier
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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Re: Why the HOT obsession with low quality buildings in Africa ?

Paul Uithol
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/).
  • 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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Re: [OSM-talk] Why the HOT obsession with low quality buildings in Africa ?

Jean-Marc Liotier
In reply to this post by Jean-Marc Liotier
On Wed, July 4, 2018 1:47 pm, Oleksiy Muzalyev wrote:
> Sometimes I myself cannot recognize on a satellite image what kind of
> building it is, - a warehouse, a cowshed, a factory, etc., or how many
> levels it has got. I have to look at its shadow, surroundings, roof
> surface, to make a guess.

Imagery interpretation is artful indeed - it takes practice to train the
eye, but then recognizing features from elusive hints, such as a tall
structure from its shadow, becomes reflex.

This is an area where having travelled in the target area helps a lot -
with nothing but the imagery I can with near-certainty recognize most
Senegalese schools... But I'm entirely lost trying to do the same in
neighbouring Guinea !


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Re: Why the HOT obsession with low quality buildings in Africa ?

verdy_p
In reply to this post by Paul Uithol
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 <[hidden email]>:
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/).
  • 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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Re: Why the HOT obsession with low quality buildings in Africa ?

Jean-Marc Liotier
On Wed, July 4, 2018 3:00 pm, Philippe Verdy wrote:
> 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). [..]


From my open JOSM, a couple areas of Bamako, from both sides of the Djoliba:
https://i.imgur.com/P6TcYOM.png
https://i.imgur.com/jSAGGxg.png

Those don't feature duplicates, intersections with highways and other
gross errors that might distract you - they are just typical samples of
geometry quality.

From a quick glance I would say that, by your definition of acceptable
quality, about half of the building=yes there are usable... But a computer
won't know which half !

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