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map-population.html
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<!DOCTYPE html>
<html lang="en">
<head>
<script src="https://cdn.jsdelivr.net/npm/d3@7"></script>
<script src="https://cdn.plot.ly/plotly-2.27.1.min.js" charset="utf-8"></script>
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Open+Sans&display=swap">
<link rel="stylesheet" href="map-population-resources/map-style.css">
</head>
<body>
<div class="map-content">
<div class="map-main">
<h1 class="map-title">Populations Trends Across the US Southwest</h1>
<p class="map-description"> Explore humanity's evolving presence
in the US Southwest from 750 to 1600 CE. Hovering over a shape
will give you more details about that time and place. See
<a href="#details">How was this map made?</a> for more details.</p>
<div class="map-container">
<div id="map-object"></div>
</div>
<h2 id="#details">How was this map made?</h2>
<p>This map shows population estimates aggregated across
<a href="https://www.usgs.gov/national-hydrography/watershed-boundary-dataset">HUC10 watersheds</a>
watersheds (a level of definition of watersheds used by the US
Geological Survey) and 25-year intervals. To arrive at those
estimates, we counted up the rooms in each residential site in
each watershed, under the assumption that more rooms means more
people. This is a common strategy in archaeology, and it is also
the strategy used by demographers today to estimate population
in areas where governments lack the resources to conduct a census
(for example, in the European Union's
<a href="https://ghsl.jrc.ec.europa.eu/">Global Human Settlement Layer</a>).</p>
<p>Unfortunately, it is not reasonable to infer population size
directly from room counts. That would be like arguing that there
must be 100 people staying at a hotel because the hotel has 100
rooms. In reality, some number of rooms will typically be vacant
on a given day. The situation gets more complicated if we
imagine the hotel adding or removing rooms over time, which is
what happened at residential sites in the US Southwest during
the time period being modeled.</p>
<p>To account for vacancy and changes in the sizes of
settlements over time, we simply assumed that each room
represents one person and that persons were evenly
(or uniformly) distributed over the years each site was occupied,
based on the associated pottery. For instance, if people lived
at a residential site for 100 years, that's four 25-year
intervals, and there are four rooms at that residence, then it
is assumed that one person lived at the site in each 25-year
interval. This was done for each residential site in the cyberSW
database, then those estimates were added up for each watershed
and time interval.</p>
<p>There's a lot of variation in these estimates, with some
areas having huge populations, and others almost no human
presence at all. It's hard to visualize spatial and temporal
trends with information like this, so the map actually displays
the logarithm of occupied rooms (zero counts are listed as
log(1e-5)).</p>
</div>
</div>
</body>
<script src="map-population-resources/map-build.js"></script>
<script>
var features = "https://raw.githubusercontent.com/kbvernon/hndsr-watersheds/main/data/watersheds.geojson";
var attributes = "data/room-counts.csv";
var basemap = "https://server.arcgisonline.com/arcgis/rest/services/World_Terrain_Base/MapServer/tile/{z}/{y}/{x}";
var div = "map-object";
build_map(features, attributes, basemap, div);
</script>
</html>