I need a list of extreme latitudes and longitudes for each US state. That is, max / min latitude, max / min longitude.

The purpose is to exactly center each state map when initially shown.

I found some lists with the "center" of each state, but these are based on center-of-mass (COM), or average of zip code centers (ZIP), not NS / EW "center". For an irregularly shaped state, for example Texas, the COM and ZIP "centers" do not exactly center the map. I know, I have tried it.

For example, the extreme longitudes for Texas are -93.508 and -106.646 (from Wikipedia) giving -100.077 EW center. That works perfectly. The websites with their COM and ZIP "centers" give values around -97.6475, so map is not centered, looks bad.

Wikipedia has some state extreme lat/long values, but not in a data table, and about half the values are missing.

One web site purported to show the extremes, but the values were somewhat off, for example W 105 039´ and W 93 030´ values for Texas, so I don't have a lot of faith in it, and they use degrees and minutes so I would have to convert.

Does anyone know a list with the extreme coordinates? I know I could somehow download all the census files or other dataset with coordinates and write a program to find the extremes. But I do not want to reinvent the wheel. It seems like such a list should already exist.

If there is no such list, I will probably just use the center-of-mass centers, and make the viewport larger so does not look bad, or adjust some of the centers by hand. But I would rather do it right, with the correct data.


If you're just looking for extreme values of x/y coordinates, you could use QGIS with this expression (e.g. in the field calculator): x_max( $geometry) - replace x with y and max with min for the according values.

  1. Download a vector file for US states, e.g. from OpenStreetMap. There are different ways to do than, one is using Overpass Turbo.

  2. Create a bounding box around each state.

  3. Calculate the centroid of the bounding box and you're done.

Screenshot: Vector shape of Texas with red bounding box. White dot: centroid of Texas polygon, red dot: centroid of bounding box. enter image description here

  • My thoughts exactly. – Erik Feb 9 at 8:23
  • Thanks for responding, but a centroid is the center of mass. I have already explained that the center of mass does not center the map for irregularly shaped areas, for example Texas. – Daniel Goldman Feb 9 at 8:33
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    Read the answer: it's the center of mass of the bounding box, thus it does exactely what you want, trust me. You create a rectangle with the extreme lat/lon values of your polygon shape - see here for an image of a bounding box: stackoverflow.com/questions/34834464/… - so you don't create the centroid of the polygon, but the middle value of extreme coordinates. – Babel Feb 9 at 8:44
  • You are right, the centroid of the bounding box centers the map. I was confused by your use of centroid (not center) for the box, and your helpful illustration was added later. However, doesn't your suggestion mean that I would have to create the bounding boxes and calculate the centroids by hand? I don't even have the software to do that, even if I wanted to do things by hand, which I don't. Could someone please answer my question, does a list with the extreme coordinates for each US state exist? Thank you – Daniel Goldman Feb 9 at 9:01
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    I need to go to sleep. I will be back tomorrow. Thanks – Daniel Goldman Feb 9 at 10:24

If you're looking for data, please try https://opendata.stackexchange.com/.

Two expressions in QGIS will give you exactly what you want:

( y_min( $geometry ) + y_max( $geometry ) ) / 2

( x_max( $geometry ) + x_min( $geometry ) ) / 2

I will post and expand upon the answer provided by JonasV in his comment to the original post. If JonasV wants to post an answer, I would be happy to mark that as the answer. Based on his answer, here are two web sites with the data I was looking for:

TONY - https://anthonylouisdagostino.com/bounding-boxes-for-all-us-states/ - has 56 states and territories – Texas extreme longitudes are -106.645646 and -93.508292

MISHARI - https://gist.github.com/mishari/5ecfccd219925c04ac32 – has 48 states (eg, missing AK) – Texas extreme longitudes are -106.645652770996 and -93.5078201293945

For comparison, Wikipedia Texas extreme longitudes are -106.645657 and -93.507969 - https://en.wikipedia.org/wiki/List_of_extreme_points_of_U.S._states_and_territories

I have no idea why the extreme longitudes (bounding boxes) are (very slightly) different in the three sources. The differences are evidently not rounding errors.

TONY has bounding boxes for basically all the states and territories, so that is the best choice. Here are the data exactly as posted on the TONY web site in CSV format for importing into a spreadsheet:

"3","60","AS","American Samoa",-171.089874,-14.548699,-168.1433,-11.046934
"8","69","MP","Commonwealth of the Northern Mariana Islands",144.886331,14.110472,146.064818,20.553802
"11","11","DC","District of Columbia",-77.119759,38.791645,-76.909395,38.99511
"33","33","NH","New Hampshire",-72.557247,42.69699,-70.610621,45.305476
"34","34","NJ","New Jersey",-75.559614,38.928519,-73.893979,41.357423
"35","35","NM","New Mexico",-109.050173,31.332301,-103.001964,37.000232
"36","36","NY","New York",-79.762152,40.496103,-71.856214,45.01585
"37","37","NC","North Carolina",-84.321869,33.842316,-75.460621,36.588117
"38","38","ND","North Dakota",-104.0489,45.935054,-96.554507,49.000574
"43","72","PR","Puerto Rico",-67.945404,17.88328,-65.220703,18.515683
"44","44","RI","Rhode Island",-71.862772,41.146339,-71.12057,42.018798
"45","45","SC","South Carolina",-83.35391,32.0346,-78.54203,35.215402
"46","46","SD","South Dakota",-104.057698,42.479635,-96.436589,45.94545
"49","78","VI","United States Virgin Islands",-65.085452,17.673976,-64.564907,18.412655
"54","54","WV","West Virginia",-82.644739,37.201483,-77.719519,40.638801

I have already incorporated the data into the software I write, in data arrays. It all works automatically / perfectly, all the state maps are exactly centered now.

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