[HOT] Interim Report: Typhoon Haiyan (Yolanda) Damage Assessment

Dan S danstowell+osm at gmail.com
Sun Feb 16 21:47:51 UTC 2014

Hi Robert,

Thanks for pointing me to the raw data. I've run a crosstabulation
(matching up objects by their osm ID) and it seems to look like this:

                no    damaged    destroyed
no            85               82           63
partial    170             119          111
major     173             160         196
total         88               31           70

This is rather disappointing - there is some correlation between the
two types of annotation but a lot of noise. For example the osm 'no'
category seems to be more likely to be _any_ of the other categories
in your observations rather than 'no'!

I quantified the predictability of one from the other (using mutual
information) and it confirms this, comes out rather low. My analysis
code is at https://gist.github.com/danstowell/9040956 - just a quick
evening script, check it before relying on it...


2014-02-14 14:53 GMT+00:00 Banick, Robert <Robert.Banick at redcross.org>:
> Hi Dan,
> There's a "download raw data" button on the side of the website at
> americanredcross.github.io/OSM-Assessment. Feel free to download and play
> with the data further -- and do contribute back anything new you find.
> We're running more intensive stats analysis on the data now and will be
> working that into the final report.
> Cheers,
> Robert
> Robert Banick | Field GIS Coordinator | International Services | Ì
> American Red Cross <http://www.redcross.org/>
> 2025 E Street NW, Washington, DC 20006
> Tel 202-303-5017 | Cell 202-805-3679 | Skype robert.banick
> On 2/14/14 4:18 AM, "Dan S" <danstowell+osm at gmail.com> wrote:
>>Hi Robert,
>>Thanks for this. It's great to have some concrete analysis of what we
>>did, and the extent to which it's accurate.
>>Is there a full cross-tabulation available of the numbers for
>>building-osm-status vs building-true-status? In the report there's a
>>table of over/underrepresentation, and some other stats, but it
>>doesn't give me a complete summary of whether our errors were in the
>>form of "bias" (e.g. consistently labelling things worse or better
>>than they are) or "variance" (e.g. the labelling tends to be a bit
>>random). I'd be really grateful if you could provide the full
>>2014-02-12 14:22 GMT+00:00 Banick, Robert <Robert.Banick at redcross.org>:
>>> Dear HOT Communuity,
>>> The American Red Cross and the REACH Initiative are pleased to present
>>> interim assessment report on the validity of the building damages
>>> through OpenStreetMap in the weeks following Typhoon Haiyan. You can
>>>find a
>>> print copy attached and a more interactive website version at the above
>>> link.
>>> The results were unfortunately negative and underline real limitations
>>> OpenStreetMap's ability to capture these results in the present.
>>> Neverthless, this report identifies strong promise in the OSM model of
>>> crowdsourcing and highlights the investments needed to make that
>>> possible.  It's our sincere hope that funders, NGO partners and most
>>> especially the OpenStreetMap community will rally around these
>>> so that OSM can play an even stronger and more operationally useful
>>>role in
>>> future disaster responses.
>>> We are indebted to the US Agency for International Development's Office
>>> Foreign Disaster Assistance (OFDA) for funding this assessment and look
>>> forward to future partnerships to improve the utility of open data and
>>> OpenStreetMap in particular for disaster response.
>>> With all the best,
>>> Robert Banick, Dale Kunce and Clay Westrope
>>> American Red Cross & REACH Initiative
>>> Robert Banick | Field GIS Coordinator | International Services | Ì
>>> Red Cross
>>> 2025 E Street NW, Washington, DC 20006\
>>> _______________________________________________
>>> HOT mailing list
>>> HOT at openstreetmap.org
>>> https://lists.openstreetmap.org/listinfo/hot

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