Can FT3 generate population maps? Hmmmmmm
Terraformer_Author
Newcomer
After looking for information lately for a poster - I learned a few things and discovered that the very units that FT uses for mapping - Temperature, Rainfal, and Elevation, are exactly the three major variables that contribute to population density distributions. In lue of this - I went about looking for climatological extremes for human habitation to act as models for establishing some sort of initial CLIMATE based parameters, but have not yet found any dealing with altitude YET. :
Hottest Populated Area : Dallot, Ethiopia,
MEAN TEMP = 106 F (41 C)
Coldest Populated Area: Omyakon, Russia,
Mean Temp = -51 F (-46 C)
Driest Populated Area: Arica, Chile,
Mean Annual Rainfall: 0.03 Inches (0.08 mm)
Wettest Populated Area: Wai`ale`ale, located on the island of Kauai in the Hawaiian island chain,
Mean Annual Rainfall: 460 inches (11,684.000 mm)
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Basic Units : People Per Sqaure Mile.
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Optimal Conditions (?)
Average minimum daily temperature in the coldest month: at least 15 ? (59 F)
Average maximum daily temperature in the warmest month: at most 30 ? (86 F)
Average yearly temp range: 59 F to 86 F
Mean Of Range: 72.5 F
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Average precipitation in the dryest month: no less than 20mm (0.79 in)
Average precipitation in the wettest month: no more than 100mm (3.83 in)
AVERAGE YEARLY PRECIP RANGE: 9.48 to 45.96 inches
Mean Of Range: 27.72 Inches
Greater Mean: 72.5 F, 27.72 Inches, 0 feet altitude (sea level ???).
I'm wondering how to get elevation stats. In an earlier conversation with Ralf - I relayed the following:
Using North American / United States statistical data seems reasonable since the maps indicate that this location IS a perfect model to "reverse engineer" geographically, demographically, and climatologically to get a population density solution - since it perfectly demonstrates the interrelatedness of these three variables probably a lot more obviously than a European or Asian model, especially considering the relative youth of the country - and how historical migration and settlement patterns are still vaguely recognizable - and how the dichotomy of altitude and climate is so obviously displayed.
This was the first time that I noticed these connections - when I was looking up info for this poster. If you can find maximums and minimums that you can graph - (using three variables?) - then you could make a case for this probably. I can see that closeness to sea level is proportional to increasing population density quite clearly - perhaps as to establish an upper limit - as is, temperature, and rainfall also being factors. I can smell an expression somewhere to describe this - so I know that this probably would involve somehow simply using some kind of combination referencing of the altitude and climate plot data generated for a specific FT World to generate a new type of map projecting population densities.
It's like saying "If for a specific map point : A = (X,Y [climate point value]), and B = (Altitude value point at +/- sea level), then C = (Population Density value at that point). The remaining problem would be to find maximum and minimum population values correlating with a combination of altitude and climate extremes logically - to set the parameters.
As a side consideration - it would not be unheard of to imagine an additional function within a future version of FT where geopolitical borders are generated using the "population density map" - based upon the "shape" of each of the population distributions.
I'm basically brainstorming here - but if you can get past my lousy syntax in this post - then I hope that you can see what I'm stabbing at here.
To get a population value point - you have THREE VARIABLES -> x= Mean Annual Temperature (People don't like places that are either too hot, or too cold - but they do love moderate to tropical climates), y= Mean Annual Rainfall (People LOVE water - even if they have to live where it floods occassionally), and z=Altitude (People will live at high altitudes - but population tends to decrease with increasing altitude, there seems to be no set limiting trend for folks living in areas BELOW sea level, but you could "mirror" the trends for increasing altitudes for decreasing altitudes theoretically for all values below "0" altitude).
Actually I'm not just rambling on incoherently here (although it would seem that way, lol).
I suspect that setting absolutely accurate upper and lower parameters for generating a population density map in three variables would be pretty darn difficult - since a lot of those upper and lower limits { - | 0 | + }, would be contradictive to each other? I don't know if a script could be devised to allow FT3 to do this - but maybe FT4?
Hottest Populated Area : Dallot, Ethiopia,
MEAN TEMP = 106 F (41 C)
Coldest Populated Area: Omyakon, Russia,
Mean Temp = -51 F (-46 C)
Driest Populated Area: Arica, Chile,
Mean Annual Rainfall: 0.03 Inches (0.08 mm)
Wettest Populated Area: Wai`ale`ale, located on the island of Kauai in the Hawaiian island chain,
Mean Annual Rainfall: 460 inches (11,684.000 mm)
---------------------------------------------------------------------------------------
Basic Units : People Per Sqaure Mile.
---------------------------------------------------------------------------------------
Optimal Conditions (?)
Average minimum daily temperature in the coldest month: at least 15 ? (59 F)
Average maximum daily temperature in the warmest month: at most 30 ? (86 F)
Average yearly temp range: 59 F to 86 F
Mean Of Range: 72.5 F
----------------------------------------------------------------------------------------
Average precipitation in the dryest month: no less than 20mm (0.79 in)
Average precipitation in the wettest month: no more than 100mm (3.83 in)
AVERAGE YEARLY PRECIP RANGE: 9.48 to 45.96 inches
Mean Of Range: 27.72 Inches
Greater Mean: 72.5 F, 27.72 Inches, 0 feet altitude (sea level ???).
I'm wondering how to get elevation stats. In an earlier conversation with Ralf - I relayed the following:
Using North American / United States statistical data seems reasonable since the maps indicate that this location IS a perfect model to "reverse engineer" geographically, demographically, and climatologically to get a population density solution - since it perfectly demonstrates the interrelatedness of these three variables probably a lot more obviously than a European or Asian model, especially considering the relative youth of the country - and how historical migration and settlement patterns are still vaguely recognizable - and how the dichotomy of altitude and climate is so obviously displayed.
This was the first time that I noticed these connections - when I was looking up info for this poster. If you can find maximums and minimums that you can graph - (using three variables?) - then you could make a case for this probably. I can see that closeness to sea level is proportional to increasing population density quite clearly - perhaps as to establish an upper limit - as is, temperature, and rainfall also being factors. I can smell an expression somewhere to describe this - so I know that this probably would involve somehow simply using some kind of combination referencing of the altitude and climate plot data generated for a specific FT World to generate a new type of map projecting population densities.
It's like saying "If for a specific map point : A = (X,Y [climate point value]), and B = (Altitude value point at +/- sea level), then C = (Population Density value at that point). The remaining problem would be to find maximum and minimum population values correlating with a combination of altitude and climate extremes logically - to set the parameters.
As a side consideration - it would not be unheard of to imagine an additional function within a future version of FT where geopolitical borders are generated using the "population density map" - based upon the "shape" of each of the population distributions.
I'm basically brainstorming here - but if you can get past my lousy syntax in this post - then I hope that you can see what I'm stabbing at here.
To get a population value point - you have THREE VARIABLES -> x= Mean Annual Temperature (People don't like places that are either too hot, or too cold - but they do love moderate to tropical climates), y= Mean Annual Rainfall (People LOVE water - even if they have to live where it floods occassionally), and z=Altitude (People will live at high altitudes - but population tends to decrease with increasing altitude, there seems to be no set limiting trend for folks living in areas BELOW sea level, but you could "mirror" the trends for increasing altitudes for decreasing altitudes theoretically for all values below "0" altitude).
Actually I'm not just rambling on incoherently here (although it would seem that way, lol).
I suspect that setting absolutely accurate upper and lower parameters for generating a population density map in three variables would be pretty darn difficult - since a lot of those upper and lower limits { - | 0 | + }, would be contradictive to each other? I don't know if a script could be devised to allow FT3 to do this - but maybe FT4?
Comments
Human habitation is very dependent on distance to water resources, which is only broadly indicated by rainfall. You may find cities on the coast in horrible deserts due to inland rainfall that's some distance away. FT has a way to compute distances from features, but the results are quantized to a 0-255 number (that's Select>>Modify>>Distance after selecting something). You'd want the full distance transform, which isn't directly exposed in FT anywhere because it's a floating-point pixel distance rather than a useful number such as meters (to get meters would require an equal-distance projection being used before selecting the base information).
Note that FT's computations of rainfall and temperature are totally inadequate to do good computations for habitation. The lack of air currents and water currents severely limits their usefulness. I had intended them only as a starting point that users would edit to get their desired results (note that FT's landforms are also very unnatural and you've got a recipe for very bad worlds).
http://forum.profantasy.com/comments.php?DiscussionID=3277
So I'm familiar with what your talking about. As far as the climate calculations, they might be just "guesstimates" like your saying - but they seem to work rather well considering FT3's intended scope. I do think that perhaps in future versions of the software creating a population density projection based on the three variables that I mentioned would definately be doable.
No one is disputing that FT3 is NOT designed to work like the logistics department at NASA - but as far as useful "ballpark guesstimates" are concerned, I'm guessing that it shouldn't be an insurmountable thing to rig software wise. I'm thinking along the lines of finding some way to "mimic" a solution to the point pixel versus real distance discrepancy - some kind of really sneaky work around somewhere. I'm not a programmer - and I really have only mediocre algebra skills, but I have a nagging gut feeling that there should be a "trick" somewhere to pulling it off.
Most of what FT3 does anyway is more or a less a "guesstimate" ballpark generalization. It would take one heck of a developement team with a budget burden to match, to turn FT into anything else, and that would be beyond the scope of practicality anyway, but finding a map that produces limited "guesstimates" as to where one might be "more likely" to see people living "seems" to be reasonable.
Somehow I just intuitively sense that it can be done. Whether or not that's an illusory viewpoint or wishful thinking on my part remains to be seen really.
You and I both know that trying to get an pin point accurate climate picture using FT3 is impossible - if for no other reason than the fact that the NOAA - using complex modelling systems computing literally hundreds of variables - ultimately can't produce a 100% climate prediction either. Whenever they do a forecast prog - they have to either make a decision based upon trends that appear in model ensembles across the board - or hang the process until the models converge into solutions that fall within a reliable tolerance range to rate a "reasonably" predictable outcome. The climate picture that FT produces - however - IS a very sufficient "ballpark estimate", even though that's one hell of a BIG ballpark, and what I'm saying is that - just as you used workarounds to get beyond the deficiencies of the climate routine - then isn't there someway that one might do the same for a map that tags a heirarchy of livability values for map point locations based upon temp, rain, and elevation?...
Food for thought.
At least that's what I'm getting at here.
You could perhaps express habitability in units that were fractions of an Eden
Whatever the habitability of an area, its actual human population level at any point in time
is a function of technology mediated by politics and chance. Without any technology at all,
so the diggers of bones tell us, the human or pre-human population everywhere was either
infinitesimally small or non-existant. A sobering thought.
People generally prefer grasslands and light forest. It has been suggested that one of the reasons that we like to have our surroundings appear to be wooded grassland is because that's the most natural environment for us.
The template might somewhat resemble the random, multicolored, speckley snow on an old color t.v. with really crappy reception. Ouch, lol. At least that's what I'm imagining - but maybe I'm just spooking myself.
I'de also like to point out that human beings also prefer lower elevations because your going to find a richer biomass there - i.e. - more food, more water, more air. Also one cannot forget that the higher that you go - not only the colder it gets - but also the air gets thinner, which complicates effective calorie use by inhibiting aerobic processes. Carrieing a 40 lbs. load might feel like carrieing a 70 lbs. load at greater elevations above the 800 mb cloud deck / surface weather layer. There's an actual altitude limit for complex plant life - but I'de have to look it up, and I'm kinda tired from chores today, lol.