Land Patents in Nebraska.

Historical Land Patent Data

This is Nebraska, colorized by population density in 1890. This is the basic narrative frame for the larger project I’m working on.

{
   "year": 1890,
   "drawing": [ "ModernCounties", "StateLines", "ExternalLines"],
   "getters.annotation.ModernCounties": "d => d.ID",
   "duration": 3000,
   "changeOffset": 20,
   "getters.fill.ModernCounties": "density",
   "scales.fill.ModernCounties": "better"
   , "zoom.States":["NE"]
   , "getters.annotation.PLSS": "d => return `${d.properties.names} acquired under ${d.properties.entry_class} (${d.properties.meta_class}) on ${d.properties.signature_date}`"
  }

Edwards, Wingo, and Fairfield (EWF) use several townships in Custer County, Nebraska as one of their study areas.

{
   "zoom.ModernCounties": ["Custer, Nebraska"]
   ,"rendering.strokeStyle.ModernCounties":"black"
   , "rendering.lineWidth.ModernCounties":"3"
   , "drawing": ["ModernCounties", "StateLines", "ExternalLines"]
  }

I’ve got most of original claims. Here they’re colorized by township number. You can see a few features.

  1. Nebraska BLM maps only go down to section resolution (AFAICT), so I’ve had to piece the aliquots together based on subdividing the original land. So a term like “N1/2SE” gets the top half of the lower-left corner. This means that the data is inexact and occasionally wrong.
    • For instance, the course of the Middle Loup river is clear as a swatch of missing data. That’s because these were numbered aliquots, not standard ones, that can’t be programatically for the whole country. Most likely there’s some Nebraska-specific data out that that could correct this that isn’t in the global BLM data I have.
  2. Some claims span multiple townships. Those show up in funny colors here. That’s correct.
  3. Two sections are missing in each township. This is because the BLM data doesn’t include the school section, 16, and section 36, which I guess had some special use in Nebraska or at least Custer County.
  4. The missing checkerboard in the lower left is a railroad claim that either isn’t in the BLM data, or that failed catastrophically in parsing the GLO records. I think it’s more likely the former. Such railroad claims are so distinctive that it would be possible to identify them simply based on the missing data (as being certainly a railroad/canal grant.)
{
     "zoom": "undefined"
     , "drawing": ["ModernCounties", "PLSS/31041", "StateLines", "ExternalLines"]
     , "getters.fill.PLSS": "d => 'T' + d.properties.township_nr+ ' R' + d.properties.range_nr"
     , "scales.fill.PLSS": "scheme2"
     , "filters.PLSS": "undefined"
     }
  

One of the EWF sections is T17 R24W.

{
       "zoom.PLSS": ["NE2050__.170-31041","NE1930__.364-31041"]
     , "drawing": ["PLSS/31041", "StateLines", "ExternalLines"]
     , "getters.fill.PLSS": "d => 'T' + d.properties.township_nr+ ' R' + d.properties.range_nr"
     , "scales.fill.PLSS": "scheme2"
     , "filters.PLSS": "d => (d.properties.township_nr=='17.0' && d.properties.range_nr=='24.0')"
     }
  

Here’s a map of that township colorized by the claim type. (If the legend is screwed up, you might need to refresh the page here by pressing control-R: there’s still work to be done on the underlying visualization engine).

{
       "zoom.PLSS": ["NE2050__.170-31041","NE1930__.364-31041"]
     , "drawing": ["PLSS/31041", "StateLines", "ExternalLines"]
     , "getters.fill.PLSS": "d => d.properties.entry_class"
     , "annotate.PLSS": ["NE1930__.364-31041", "0197-242","NE3000__.001-31041"]
     , "scales.fill.PLSS": "<cat>"
     , "filters.PLSS": "d => (d.properties.township_nr=='17.0' && d.properties.range_nr=='24.0')"
     }
  

One of the notable features of this part of Nebraska is that homestead claims and land sales occur out of sync with each other. Here are claims made between 1884 and 1889: scattered claims have been made under the Homestead acts. (I backdate any completed homestead claims by 5 years to reflect the original date of the claim. This doesn’t capture failed claims.)

{
       "zoom.PLSS": ["NE2050__.170-31041","NE1930__.364-31041"]
     , "year": 1889
     , "filters.PLSS": "d => (d.properties.township_nr=='17.0' && d.properties.range_nr=='24.0') && (d.properties.date < $year && d.properties.date > $year - 5)"
  }

Between 1889 and 1894, most transfers are land sales in the speculative bubble. As an economic history question, the early 1890s bubble is extremely well attested by the files in ways that might give interesting new ways to study it. For example: I’ve noticed that on the Kansas-Colorado border, sales in Kansas counties happen well before in Colorado counties. I think this is naive speculators from out of state simply assuming a Kansas address is better than a Colorado one, although there could be other regions.

{ "year": 1894 }

While between 1894 and 1899, every claim is under the Homestead or Timber Culture acts. I haven’t linked these to previous homesteaders, but presumably many are already captured earlier. Timber-Homestead linkage is possible and maybe useful.

{
  "year": 1899
  }

Let’s now zoom back out to the full county. You can see claims made in the 4 year period ending in 1889. Click the button below to animate the progression of claims. At a scale larger than a few counties, it become impractical to do this kind of thing in-browser, so some kind of resolution-binning becomes necessary. Which is too bad–these things look good in their full resolution, if you’re willing to abide by missing data.

{
  "year": 1889
  , "annotate": "undefined"
  , "zoom.ModernCounties":["Custer, Nebraska"]
  , "filters.PLSS": "d => (d.properties.date < $year && d.properties.date > $year - 4)"
  }

This interactive works for more or less the entire West. (It’s not great on the Mexican claims in California and certain other areas, or parts of the old Northwest.) Here, for instane, is the year for the other Nebraska county in the EWF set.

It’s also possible to overlay more abstracted features–the contour line of 1890 homesteading, for example, or visualizations that treat counties or townships as the primary unit. Some form of zooming, filtering, and annotation seems as though it could add a lot of value, especially for people who know about their county and not others.

{
  "year": 1889
  , "annotate": "undefined"
  , "zoom.States":["NE"]
  , "drawing": ["PLSS/31041", "PLSS/31045","StateLines", "ExternalLines"]
  , "getters.fill.PLSS": "d => d.properties.date"
  , "scales.fill.PLSS": "homesteadYear2"
  , "filters.PLSS": "none"
  , "duration": 1000
  }

Some of these things, though, are so specific that they’d require the full resolution. This map limited the map to only homeclaims by people with the last name “PIERCE”. That quickly leads to one family set of claims.

It wouldn’t be too hard to look into names most statistically concentrated in each township or county and get some mildly interesting local history angles worth poking around at more.


  {
    "year": 1889
    , "annotate": "undefined"
    , "duration": 5000
    , "drawing": ["PLSS/31041", "PLSS/31045","StateLines", "ExternalLines"]
    , "getters.fill.PLSS": "d => d.properties.date"
    , "scales.fill.PLSS": "homesteadYear2"
    , "filters.PLSS": "d=>d.properties.names.endsWith('PIERCE')"
    , "zoom.ModernCounties": ["Custer, Nebraska"]  
  }
  

Here’s a closeup of one of those original Pierce claims.

{  "zoom.PLSS":["NE0820__.002-31041","NE0820__.475-31041"]
    }

Some random other notes: you can edit some of the code to generate visualizations here by pressing the gear icon. The API isn’t documented yet, but you might be able to figure some of it out.

I have made a few haphazard efforts at linking last name to gender and nationality. It seems to work reasonably well. A more sensible overall approach might be match names directly against the federal census.

As part of the digital publication, I’ll be putting out geojson files for the full country once they seem reasonably useful. If you can see uses for any of these, such as in a classroom setting, let me know.