[HOT] Nepal major road validation

kusala nine kusala9 at googlemail.com
Wed Apr 29 21:34:02 UTC 2015


hi - I'm still ploughing through the UN road distance map. It's good
because it's shown up some misclassifications but mostly placename
differences and incorrect locations. I've covered most of the high priority
area and the good news is that the distances largely agree with the OSRM
distances even in some of the remoter areas. I'm going to push on with some
of the other areas and try to correct placename locations and road
connectivity as I find them. the table below is the North/East section of
the UN diagram. I have some data from the west and will cover the higher
priority areas first. Generally though the road connectivity looks pretty
good :-)


Jon.


kathmandu dunche 118 (117)

kathmandu banepa 26 (30)

banepa panauti 9 (6.8)

dhulikhel nepalthok 50 ?

banepa lamidanda 19 (20) -  lamidanda = lamidadha

lamidanda dolalghat 12 (11)

dolalghat chautara 25 (26)

dolalghat lamosangu 19 (24)

lamosangu kodari 37 (34)

lamosangu charikot 18 (56) - are we missing a more direct road here?

charikot tamakosi 18 (19) tamakosi?(duplicate placename - 27.6188, 86.0788)

charikot ramechhap (airport) - 71 (57)

[issues with places marked in wrong places. kirnetar, tamakosi, ramechhap]

naubise galchhi 22 (23) - galchhi = gardo khola

galchhi malekhu 20 (22)
malekhu mugling 40 (37)

On Tue, Apr 28, 2015 at 1:22 PM, kusala nine <kusala9 at googlemail.com> wrote:

> Hi - just a bit more info on the validation on roads. I concentrated on
> Task 6 and got the following results from OSRM vs the UN document. OSRM are
> in (brackets). All distances in km.
>
> Kathmandu - Naubise 25 (30)
> Naubise - Palung 37 (43)
> Palung - Simbhanjyang 15 (18)
> Simbhanjyang - Bhainse 41 (41) note: Bhainse = Bhaise Dovan on geonames...
> Bhainse - Hetauda 11 (12)
> Hetauda - Bharatpur 77 (76)
> Palung - Kulekhani 21 (35) I think Kulekhani not yet fully captured and
> actual location looks vague to me.
>
> I'm using this to focus on digitising some of the Task 6 squares to get
> the main road distances working. The area around Naubise may be dubious as
> two of the distances are greater in OSRM. Please note that, as I said
> before Kathmandu-Hetauda = 129 on the network map and 221 on the triangle
> map (unless I'm suffering from lack of sleep??). Anyway, I'm moving on to
> task 3 (most of task 5 is outside the area of the network map)... Hope this
> helps. I will also keep digitising roads in task 6 according to these
> results.
>
> Jon.
>
>
> On Tue, Apr 28, 2015 at 11:11 AM, kusala nine <kusala9 at googlemail.com>
> wrote:
>
>> I agree -  a good methodology is to use the smaller tree diagram to
>> validate in dividual distances and look at where they differ significantly.
>> The UN doc itself is inconsistent. If you look at Kathmandu to Hetauda
>> the tree diagram distances don't add up to the distance in the triangular
>> table (89km vs 211km!). The tree distances are much closer to the OSRM
>> distances and you can work on smaller ones. I managed to validate the
>> distances within task 6 last night fairly quickly. I'll write the results
>> up and post them on later today.
>>
>> Jon.
>>
>> On Tue, Apr 28, 2015 at 11:02 AM, Pierre Béland <pierzenh at yahoo.fr>
>> wrote:
>>
>>> Great
>>>
>>> From your table, I see many significative differences. Taking shorter
>>> segments would help to validate further I think.
>>>
>>> cheers
>>>
>>>
>>> Pierre
>>>
>>>   ------------------------------
>>>  *De :* kusala nine <kusala9 at googlemail.com>
>>> *À :* hot <hot at openstreetmap.org>
>>> *Envoyé le :* Mardi 28 avril 2015 1h47
>>> *Objet :* Re: [HOT] Nepal major road validation
>>>
>>> I did quick comparison just using names from the distance calculator
>>> from kathmandu (results below) but now moved onto checking using the
>>> smaller network diagram. this lets you concentrate on areas which are in
>>> the current task manager tasks. Just finishd Task 6 last night and they
>>> look pretty good covering Kathmandu, Hetauda, Bharatpur, Palung and
>>> Bhampali. I've since digitised roads in a couple of key tiles based on km
>>> distance discrepancies and when I've finished those I'll move on to task 3.
>>> The triangular distance table is good but points to a lot of discrepancies
>>> in the longer distances which are out of the target zones.  I'm happy to
>>> digitise the triangular table though if anyone wants to try the URL method
>>> to identify areas of difference. I'm using NGAs geonames service to
>>> identify differences in place naming - what should we do when there's a
>>> difference? e.g "Bhainsie = Bhaise Dovan". Can I attribute a synonym?
>>>
>>>
>>> *place**OSM**UN**difference**Comments…*baitadi8421168-326biratnagar396
>>> 549-153chandragadhi473624-151terhathum505654-149ilam538685-147dharan403
>>> 545-142birganj135276-141hetauda82221-139rajbiraj317456-139gaighat314452
>>> -138dhankuta467595-128janakpur295378-83tulsipur401441-40narayanghat133
>>> 144-11bhairahawa274279-5dhunche115117-2dhulikhel3132-1lumbini300301-1trishuli
>>> bazar6970-1salyan5045031kodari1161133pokhara2021984chautara87825jiri188
>>> 17612butwal27225715tansen31129615Birendranagar59557520dipayal83681620
>>> mahendranagar70668422dhangadhi67665026nepalgunj52549926taplejung88783552
>>> gorkha19714057dailekh66460559krishnagar831334497baglungno route271Baglung
>>> not connected - closest major place is pokharaBarhabiseno place111no
>>> such place. Closest OSM place is Mangalsen by wikipedia's coordinates.
>>> kakarbhittano place618not inOSM. Closest is charali = 1036km
>>> (charali-kakarbhitta=11km)sindhullmadhino place387still looking….
>>>
>>>
>>>
>>> On Tue, Apr 28, 2015 at 12:53 AM, Andy Anderson <aanderson at amherst.edu>
>>> wrote:
>>>
>>> Hi, Andrew,
>>>
>>> The documentation says “The results are network distance, i.e.
>>> travel-time, in 10th of seconds.” It’s hard to translate that into
>>> distances without the speeds assigned to road segments. If one knows the
>>> type of road and what the “common” speed is for that type of road one can
>>> make an estimate, but it could still be quite far off. Do you have any
>>> guidance on how to get road segment information? If one needs to download
>>> the road data itself, then the length of the segments should be there, too.
>>>
>>> — Andy
>>>
>>> On Apr 27, 2015, at 6:44 PM, Andrew Buck <andrew.r.buck at gmail.com>
>>> wrote:
>>>
>>> > -----BEGIN PGP SIGNED MESSAGE-----
>>> > Hash: SHA1
>>> >
>>> > The OSRM distance table calculator is documented here...
>>> >
>>> >
>>> https://github.com/Project-OSRM/osrm-backend/wiki/Server-api#distance-ta
>>> > bles
>>> >
>>> > Basically you feed it a url with a bunch of lat/lon pairs are
>>> > parameters (say for the 10 largest cities in the area) and then it
>>> > creates a 10x10 table of the distances from every city to every other
>>> > city.  So we can duplicate the table in the top right corner of the
>>> > PDF, we just need someone to get the lat/lon of each of those cities
>>> > and feed them into the api call documented above.  If our distances
>>> > are signifigantly greater than the PDF distances listed for any
>>> > entries then that probably indicates a problem in our data on the road
>>> > between those cities.
>>> >
>>> > - -AndrewBuck
>>> >
>>> >
>>> > On 04/27/2015 07:57 AM, Pierre Béland wrote:
>>> >> http://un.org.np/node/10028, shows road distance of major cities
>>> >> from kathmandu. Look at the pdf files that shows distance of
>>> >> various road segments. Any volunteer to use this data and compare
>>> >> with OSRM's distance matrix tool? If distances are significantly
>>> >> different, this would indicate missing connecting roads or wrong
>>> >> tag like path.
>>> >>
>>> >> Pierre
>>> >>
>>> >>
>>> >>
>>> >>
>>> >>
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>>> >>
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>>> >
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