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Mapping my hometown Rajahmundry

Posted by Jothirnadh on 10 November 2015 in English. Last updated on 14 September 2018.

Rajahmundry is one of the most populated cities in Andhra Pradesh, India. It is located on the banks of Godavari river and it is most known for its high cultures and traditions. Rajahmundry is also known as the ‘Cultural Capital’ of Andhra Pradesh.

Problems encountered while mapping

I started my OSM mapping journey recently and the first thing I wanted to map is my hometown (Rajahmundry). In the beginning, I was quite surprised to see that most of the roads and buildings of the city are already mapped by OSM mappers for which I’m always thankful. This made my work much simpler and thought of adding names to the streets which I’m familiar with, but soon I started to encounter errors in the data. The most common error is the misalignment of data, which I mentioned in the following context.

1. The difference in Satellite data

The city is having overall coverage of Bing imagery but the Satellite data is divided into three major blocks. The center block is from 2013 coverage, the upper block is from 2012 coverage and the lower right block is from 2011 coverage.

screen shot 2015-11-09 at 10 54 34 am

There is a significant shift at the intersection of these blocks

screen shot 2015-11-09 at 11 51 20 am

screen shot 2015-11-09 at 11 52 40 am

This is the major reason that caused data alignment problems in this city.

2. Misaligned roads

Due to the shift in the merging of satellite data the roads in this blocks are completely misaligned. Most of the roads are aligned to the older satellite imagery and the others are aligned with the newer satellite imagery. This brought a lot of mess in the data.

screen shot 2015-11-09 at 12 13 50 pm

3. Building digitization

Most of the buildings at the heart of the city are digitized by different contributors but are digitized in different time periods which caused data alignment problem. Also, the satellite image is not that clear to identify the building footprints, which made it hard for the contributors to identify the exact building dimensions I guess.

screen shot 2015-11-09 at 12 51 08 pm

4. Misplaced Hospitals and medical shop’s

The only thing one can identify by looking at the cities data is Medical symbols marked all around the city. I’m sure that there are many hospitals and medical stores in the city but not as many as marked on the map. I personally went to the marked locations of some medical stores but failed to find most of them. It seems like all the medical related shops and hospitals are imported by a single user whom I need to contact and know the details of the imported data.

screen shot 2015-11-09 at 1 17 19 pm

What I tried to contribute so-far

Cleaning up the data without a proper understanding of the background is pretty hard. In the beginning, I started to align the roads to the Bing imagery, but later I found the shift in the imagery itself which spoiled my previous work. I tried to delete all the duplicate roads and nodes. I did not touch the building alignment work as the imagery is not clear enough to mark the building footprint (hoping to get clear imagery soon). I also made some changes to the borders of the Rajahmundry Airport. I aligned the roads with the available imagery but I don’t think it’s the best process to follow.

All together my edits look as below, but there are a lot more to go

screen shot 2015-11-09 at 1 28 43 pm

What I intended to do in Future

  • Hoping for some suggestions from the community members to take further actions in such conditions.
  • Will try to contact the user who made huge import of data (mainly medical related) to know the details of the collected data to identify the data quality.
  • Try to contact local mappers to improve the data.
  • Will try my best to arrange a mapping party to grow the local mapping community.
Location: Rajamahendravaram, Rajahmundry (Urban), East Godavari, Andhra Pradesh, 533100, India


Comment from saikabhi on 10 November 2015 at 08:57

Great diary post @Jothirnadh. Happy mapping!

Comment from Chetan_Gowda on 10 November 2015 at 09:31

Oh man, this town should be cleaned first!! @Jothrinadh, Nice work. Keep on improving.

Comment from SimonPoole on 10 November 2015 at 09:38

@Jothirnadh (welcome to OSM) lots of us have been through the misaligned imagery valley of grief :-) Which includes major parts of Europe just a couple of years back.

The main problem seems to be that there is no reference information right now to adjust the imagery.

There are essentially not so many ways to generate/get such information:

  • make precision measurements with a GPS device of well defined features that have good visibility on the imagery (for example a corner of a 1 to 2 storey building on which you can access the roof)

  • generate (multiple) GPS tracks over crossings and turn offs (you will need multiple tracks on both sides of the road to get resonable information)

  • get official reference point information from the governement or similar (typically this is not so helpful because the points themselves tend not to be visible on imagery)


Comment from Warin61 on 10 November 2015 at 12:33

The imagery alignment … may be different within the same image — due to parallax and height changes for example.
Most people try to use GPX tracks to get the correct alignment. Preferably several over at least a few days .. I have had some that are displaced from the rest by upto 10 meters!

Given that the GPS may be out by up to 10 meters then discrepancies in the map may not be as easy for the user to resolve. As long as the map ‘looks’ like the visual world that the user sees, then user will probably be accepting of any offsets (they could be from their GPS and/or the map).

Comment from SK53 on 10 November 2015 at 13:43

@Warin61 is quite right, but the imagery alignment problems are very daunting for the mapper.

As @SimonPoole says getting some useful alignment traces really helps. In the past mappers in India without access to a smartphone capable of recording GPS traces have managed this by borrowing such a phone from a relative for an hour or two. Otherwise if you have a GPS-enabled phone an app such as GPS Tracker can be used.

Open spaces such as parks, temple precincts, wider highways are good places to try & capture decent GPS traces. Ideally you want a few as an individual trace will be affected by day to day vagaries.

There are a limited number of Strava tracks available in the area, but at least these can be used immediately:

You also may like to use an editor which uses the Imagery Offset database, which at least would allow the same offsets to be used consistently.

I would like to echo others comments that this is a nice write-up.

Comment from Jothirnadh on 13 November 2015 at 04:28

@all thanks for your suggestions and encouragement. Will follow your ideas and try to improve the map ASAP.

Comment from Govanus on 13 November 2015 at 19:36

Thank you for your contributions. Your dificulties sound familiar to mapping in the densely mapped parts I work in like central Oxford and here though it looks like someones started to move the buildings in Temple street off the road or vice versa. The building used to be on different offsets when try drawing the sidewalks so I took a set offset that seemed to be fairly accurate to a national import and standardised the area’s new sidewalks I added to it traceing arial photos both the basic in the editor and side views from bing’s bird view especially under trees and site visits to get a good line even through heavy shadow and low resultions (I’m fixing to distances of around about a dekameter (10cm) if I can.

Area maping the roads might be a way down on your to do, but they do have a fixing affect on offsets as long as the backgound image dosn’t warp much (see the recent diary note on japanese roads & here). They can be easy for mappers to adjust to. They can be present for long length through the map. and moden ones might have smooth lines either with markings at: the centre, kerbings or drains etc. that help with a site vist to help you deal with wrinkles.

Well you hope it may add to the help even if it feels a way into the future with so many other corrections to handle first.

At least youwon’t need to be dealing with bleeding edge tagging styles that others aguee for a bit about, for while too.

-Good luck

ps. If you everfind yourself puzzling over area highways and the like in the future let me know and I’ll try to help you out with were its reached by then…

Comment from malenki on 19 November 2015 at 15:20

Have you tried using Mapbox Imagery?
Though its resolution isn’t as good highways should be easy to map. Contrary to Bing Imagery there are only two sets of imagery end the offset is nearly zero (at the places I looked at). After you are done wit the highway grid based on Mapbox you can align Bing to the highways.

In case you use JOSM it may be easier to draw highways on an empty layer, then download the OSM data and use “replace geometry” to move the existing tags and object IDs vom the misaligned to the newly made, enhanced ways. “replace geometry” gets provided by the utils_plugin.

Comment from Jothirnadh on 19 November 2015 at 15:31

Thanks for you comments and guidance @Govanus & @malenki. They are really helpful, and gave me new ideas to formulate the mapping work.

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