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I'm looking for a list of all populated places(not just big cities/ports) on the world that reside on sea/ocean. The list should contain the place name, latitude and longitude. Does something like that exist somewhere?

A bit more details: The reason I'm asking for this is because of my project requirement. I need to build a web service which can let people select a place in a list of all possible places in the world(Listed for example in GeoNames DB) but which are on the sea or ocean. The user then gets meteorological data that is related only to places which are on the sea. Like tides, sea temperatures and other more specific info related to the project. Allowing the user to select a place which is not on the sea would simply make no sense.

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Regarding your update, that begs another question. Do you have a list of populated places which actually have the meteorological data you need? This would almost certainly be a better starting point than all populated places in the world. – blah238 Apr 14 '14 at 22:18
That would be an easy way out ;) ... but no, unfortunately the information is derived from satellite data like SST from NOAA and I need to correlate it with latitudes and longitudes of actual places. – Ivan Kovacevic Apr 14 '14 at 22:22
I'm not familiar with nautical navigation apps or dedicated devices, but I'm now wondering if they have some auto route plotting algorithms which let you choose your destination. Obviously they would have to reject places not reachable by sea. Hmm... but then again I kinda doubt that auto routing would make much sense in nautical navigation ... – Ivan Kovacevic Apr 14 '14 at 22:40
Another idea that I'm thinking about is, city/place populated area as a surface, does such data exist? Then I could maybe check if some place surface intersects with the coastline? – Ivan Kovacevic Apr 14 '14 at 22:54
I'm not sure where you're going with the routing idea, but it's all about the data and how it's prepared and for what purpose. Additionally, a surface is not going to be able to uniquely identify something as numerous as worldwide populated places, only aggregated or continuous data. – blah238 Apr 15 '14 at 0:42
up vote 6 down vote accepted

I think your best bet is going to be downloading GIS data for populated places and coastlines (Natural Earth is an oft-recommended source) and performing a proximity analysis using GIS software to exclude all places except those matching some criteria, e.g. within 10 miles of a coastline.

Bear in mind the world is a big place, and the coastlines are very complex geometries (depending on the level of generalization in the data you use). There are a LOT of populated places. Depending on the amount and detail of the data, it will probably take many hours if not days to crunch all of the data.

Perhaps if you explained what you plan to use the data for, a more tailored answer could be provided.


Here is the result of a quick and dirty selection of populated places within 10 miles of coastlines (using Natural Earth's 1:10m scale data):


CSV data dump:

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This could be a solution! Although, as you said, a lot of work has to be done. But definitely a nice answer. Thanks. I've updated my question with a more detailed explanation of my intentions. – Ivan Kovacevic Apr 14 '14 at 22:10
After a bit of thinking I believe this could be used but with an addition to somehow take the size of the populated places into the consideration. So that the distance from coastline is less for smaller cities/villages and bigger for big cities. Can I extract the rough estimate of size(for example radius, from center) of places from some source? – Ivan Kovacevic Apr 15 '14 at 12:41
The Natural Earth data has various fields that I did not include in the CSV output in my answer, such as population, bounding box, area and perimeter with varying levels of completion. Check it out for yourself. You can use a FOSS GIS like QGIS to view shapefiles, as well as the commercial ArcGIS. There is also an online viewer here: – blah238 Apr 15 '14 at 16:06
Thank you! Lot of useful info. – Ivan Kovacevic Apr 15 '14 at 18:57

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