cmaidaartworkblog

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I have just now finished a video where I played some of the animated maps for this project on a globe in Blender, so here's that now too! Since the first published aspect of this project was a video, it's only fair that a video should be the *last* thing I share about it. Just the wonderful continuity of a bookend. Animated maps exported from Photopea, edited together in ClipChamp, used as textures for a sphere in Blender, from which I directly exported video elements, and, finally, spliced and narrated and captioned in ClipChamp once again. 2024

This video showcases my Blender model of the planet that the Scud aliens call home, the fourth and final world I've mapped out for @jayrockin's "Runaway to the Stars" project. A *lot* of maps were created in service of this final render, and also in service of presenting the special qualities of this planet. I intend to show you as many of these as I can under the cut, and also in subsequent posts focusing on some of the more interstitial, ancillary maps and figures that played a part in producing the primary maps you'll see in this main post.

Before I show the first maps I made for this project, what you see below are the satellite-style maps for the Equinoxes and Solstices, in order of (Northern) Spring, Summer, Fall, and Winter, the latter serving as the texture for the Blender object you saw in the video.

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With that matter covered, our next focus is this project's foundation: Geology. While I didn't spin as elaborate a tectonic history for this planet as I did for the Ayrum commission, I did work out as much detail as I could for the more recent geological activity, to set the stage for the elevation data - including a narrower focus on the coastal shallows that host the Scud populations.

__________

Once I could move on to climate, my first step was finding this planet's relative Insolation, which I managed thanks to @reversedumbrella's code and coaching. With an obliquity of only 16 degrees, this planet's yearly maximum Insolation levels stick close to the equator, compared to pole-to-pole oscillation we see on Earth

__________

Having a rough sense of where heat would concentrate seasonally and how the landmasses would deflect water in light of the planet's retrograde spin, I was able to set down the bi-annual ocean currents (Northern Summer above and Northern Winter below), then the monthly water temperatures pushed around by said currents, and finally -after factoring in many other considerations- the monthly land temperatures as well (combined in the second gif)

__________

Next came the seasonal air pressure maps and subsequent wind patterns (my first time creating those from scratch), which later factored into the precipitation maps. The incredible temperatures at the largest continent's interior make a desert of most of it, and the other interiors are fairly dry too, but all that heat on the equatorial ocean generates a *lot* of evaporation which ends up coming down elsewhere.

__________

With temperatures and precipitation mapped out for each month, I was able to find how the accumulation and melt of ice and snow played out, too. Given such a hot equator it's surprising to see freezing temperatures hold out in some places, but low obliquity and high elevation shield what areas they can, it seems.

__________

All this monthly data was then painstakingly combined and compared and plugged into equations to produce maps of discrete climate zones, using both the Köppen (left) and Trewartha (right) classification systems. The higher latitudes see some overlap with Earth's conditions, but the Tropics...

__________

I never really finished the map I wanted to make with my own loosely customized classification system, but I *did* get as far as this breakdown of the areas that sometimes surpass 56.7 degrees Celsius, Earth's record for highest surface temperature ever directly measured. And as you can see, that earthly record is broken by a *significant* fraction of this planet's surface, and far exceeded by the equatorial continent's deep interior

__________

The final phase of this project dealt with creating satellite maps of this planet's surface (which you saw at the top of this post), which started with a map of dry and submerged substrate, then a density map of the vegetation that sits atop it, then the colors of that vegetation under annual average conditions (demonstrating how they would appear in-person, rather than the area's appearance from orbit), and finally plant colors under seasonal conditions (same conceit as previous). In concert with the seasonal ice and snow maps, it was the four maps in the last sequence which were overlaid on the Substrate map, using the plant density map as raster masks, to produce the final Satellite-Style maps.

__________

This planet's sophonts being a marine species, it was then worth focusing on the conditions underwater, which included monthly seafloor temperatures (first gif), annual discharge of sediment from rivers (magenta in the 2nd gif), and seasonal upwelling of nutrients from deeper water (blue in the 2nd gif).

The creation of all my maps seen in this post was possible thanks to Photopea, which has been my go-to for several years now. The resolution kinda got crunched when I uploaded these here, so when I share them on Reddit later I'll add those links under this. These have also already been posted on Twitter, which you can see here if you like. Thanks for scrolling all the way down here!

[cmaidaartworkblog]

If any of you also follow me on Twitter and would like to keep seeing my posts in that site's format before I start gradually pulling away from it, you can now find me on:

[cmaidaartworkblog]

I finally got around to compiling some of the extraneous, in-service-of-the-main-feature maps for the "Runaway to the Stars" Scud-planet commission that I thought were also worth showing, some because they reveal something unique about this planet's qualities, others because they're pretty, and mostly both. There's a good handful of those and a *lot* of explanatory text, so that's all below the cut.

First we have the maps that bridge the gap between wind data and precipitation. This pair of animated maps demonstrates, first, the Orographic effect that would theoretically result from winds blowing in each of the eight cardinal directions across the planet's whole surface, and, second, the Orographic effects which are actually produced by the local prevailing winds for each season. For both of these, darker values mark where the topography prevents moist air from precipitating (a rain shadow, on the leeward side of a raised terrain feature) and lighter values show where the topography catches most of the airborne moisture before the wind blows over it (a rain-highlight, on the windward side of a raised feature).

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The first static map, looking like a meticulously customized Jawbreaker, roughly represents the inland distance over which air has to travel from various bodies of water (also accounting for vertical distance in the form of mountains and the sizes of the bodies of water providing the moist air), which is another factor in where rain is able to fall.

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Another static map, included entirely for aesthetic reasons, demonstrates (in white) where at least ten times as much rain falls in the wettest month of summer as in the driest month of winter. The cyan end of the gradient represents where only 3 times as much rain falls, in that comparison. This was a step in figuring out what areas would qualify as Dry Winter (climate type Cw) in the climate zone maps, which ended up being completely nonexistent once all the other requirements of that climate type were measured for. All of the areas marked in white (meeting that 10x ratio requirement for Dry Winter) ended up falling under Arid or Semiarid instead.

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For comparison, *this* map shows (in cyan through magenta) where there is at least three times as much precipitation in the wettest month of winter as in the driest month of summer, one of the requirements for Mediterranean climate (or Dry Summer, climate type Cs). Not all of the marked areas ended up meeting all requirements for the final climate zone map, either, but at least *some* did, falling just outside the Arid/Semiarid areas.

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Another precipitation-related map, this one instrumental in figuring out vegetation density, demonstrates the reliability of significant rainfall. Specifically, this represents how many months in a row a given area receives at least 60 millimeters of precipitation per month, with areas in white receiving this amount for every month of the year, areas in black experiencing no months with that much rainfall, and shades of grey showing where this much rainfall persists for anywhere from one to eleven months in a row. The second map attached here shows that data broken down for the exact number of months.

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Next, here is a map that helped me find where Upwelling would occur seasonally. Since material from deeper waters is brought to the surface by the general movement of water *away from* the coasts, and since water is moved in that direction by winds blowing *perpendicular to* the coasts (counterclockwise for the northern hemisphere on a retrograde-spin planet like this, and clockwise for its southern hemisphere), it was crucial that I first determine what directions the coasts themselves were facing, with red marking coasts that face north, yellow for coasts that face west, cyan for coasts facing south, and blue for those facing east. This particular map was produced by taking a blurred elevation map of the shallows, using it as the displacement texture for a flat Plane in Blender, and pointing different colored lights at it from the eight cardinal directions.

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One of the very last elements that I mapped out for this planet was the discharge of sediments from the rivers into seas and terminal lakes, which required a *lot* of steps. The first of these was to isolate the different major drainage basins that would deliver water to various sections of the coastal shallows, as seen in the first, multicolored map. In the second map, we see the surface areas of each of the drainage basins, in the third map we see the average density of vegetation within each basin, and in the final map I've combined this data to show the overall total amount of vegetation in each basin, which should roughly correlate with how much organic material ends up washing out to sea, since river discharge volume and vegetation density are both (largely) contingent on the same factor: precipitation.

All told this is only a tiny fraction of the maps that were part of the overall pipeline. On Reddit you should be able to see these images in higher resolution, so I'm including a link to the corresponding post here

[cmaidaartworkblog]

This video showcases my Blender model of the planet that the Scud aliens call home, the fourth and final world I've mapped out for @jayrockin's "Runaway to the Stars" project. A *lot* of maps were created in service of this final render, and also in service of presenting the special qualities of this planet. I intend to show you as many of these as I can under the cut, and also in subsequent posts focusing on some of the more interstitial, ancillary maps and figures that played a part in producing the primary maps you'll see in this main post.

Before I show the first maps I made for this project, what you see below are the satellite-style maps for the Equinoxes and Solstices, in order of (Northern) Spring, Summer, Fall, and Winter, the latter serving as the texture for the Blender object you saw in the video.

__________

With that matter covered, our next focus is this project's foundation: Geology. While I didn't spin as elaborate a tectonic history for this planet as I did for the Ayrum commission, I did work out as much detail as I could for the more recent geological activity, to set the stage for the elevation data - including a narrower focus on the coastal shallows that host the Scud populations.

__________

Once I could move on to climate, my first step was finding this planet's relative Insolation, which I managed thanks to @reversedumbrella's code and coaching. With an obliquity of only 16 degrees, this planet's yearly maximum Insolation levels stick close to the equator, compared to pole-to-pole oscillation we see on Earth

__________

Having a rough sense of where heat would concentrate seasonally and how the landmasses would deflect water in light of the planet's retrograde spin, I was able to set down the bi-annual ocean currents (Northern Summer above and Northern Winter below), then the monthly water temperatures pushed around by said currents, and finally -after factoring in many other considerations- the monthly land temperatures as well (combined in the second gif)

__________

Next came the seasonal air pressure maps and subsequent wind patterns (my first time creating those from scratch), which later factored into the precipitation maps. The incredible temperatures at the largest continent's interior make a desert of most of it, and the other interiors are fairly dry too, but all that heat on the equatorial ocean generates a *lot* of evaporation which ends up coming down elsewhere.

__________

With temperatures and precipitation mapped out for each month, I was able to find how the accumulation and melt of ice and snow played out, too. Given such a hot equator it's surprising to see freezing temperatures hold out in some places, but low obliquity and high elevation shield what areas they can, it seems.

__________

All this monthly data was then painstakingly combined and compared and plugged into equations to produce maps of discrete climate zones, using both the Köppen (left) and Trewartha (right) classification systems. The higher latitudes see some overlap with Earth's conditions, but the Tropics...

__________

I never really finished the map I wanted to make with my own loosely customized classification system, but I *did* get as far as this breakdown of the areas that sometimes surpass 56.7 degrees Celsius, Earth's record for highest surface temperature ever directly measured. And as you can see, that earthly record is broken by a *significant* fraction of this planet's surface, and far exceeded by the equatorial continent's deep interior

__________

The final phase of this project dealt with creating satellite maps of this planet's surface (which you saw at the top of this post), which started with a map of dry and submerged substrate, then a density map of the vegetation that sits atop it, then the colors of that vegetation under annual average conditions (demonstrating how they would appear in-person, rather than the area's appearance from orbit), and finally plant colors under seasonal conditions (same conceit as previous). In concert with the seasonal ice and snow maps, it was the four maps in the last sequence which were overlaid on the Substrate map, using the plant density map as raster masks, to produce the final Satellite-Style maps.

__________

This planet's sophonts being a marine species, it was then worth focusing on the conditions underwater, which included monthly seafloor temperatures (first gif), annual discharge of sediment from rivers (magenta in the 2nd gif), and seasonal upwelling of nutrients from deeper water (blue in the 2nd gif).

The creation of all my maps seen in this post was possible thanks to Photopea, which has been my go-to for several years now. The resolution kinda got crunched when I uploaded these here, so when I share them on Reddit later I'll add those links under this. These have also already been posted on Twitter, which you can see here if you like. Thanks for scrolling all the way down here!

[cmaidaartworkblog]

Turns out I never posted it here, but three years ago I rendered @jayrockin's character Talita's upper respiratory system just for kicks, and since the inner workings of her head are still knocking around in mine, she gets to be a Blender file now! The muscles and bones I've added to this new render aren't *necessarily* canon for this species' design, but speculation is fun : )

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Craniofacial reconstructions of four hominids, rendered and (awkwardly) showcased in Blender. These are mostly still in-progress, but should be close to finished soon.

Digital sculpture (Blender),

2024

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Here's *another* update to the Paranthropus/Australopithecus render, wherein I've made some adjustments to A. sediba's nose and to both of their scalps, ears, and necks, and rescaled them to reflect the comparative sizes of their skulls. I also made one gif where I fade between view modes and skin presence, and another where I peel back the layers by hiding soft tissue elements in reverse-alphabetical order except for the eyes, which I saved for last. Digital Sculpting (Blender) and .Gif-Making (Photopea), 2024

Some hominids-in-progress I've had on lately: a Neanderthal shifting her weight in preparation to throw a spear, some improvements I made to the meshes and textures for my A. sediba and P. boisei skins, and skins I still have to texture for H. naledi and H. heidelbergensis Digital painting (Photopea, first image), Digital sculpture (Blender, last three images), 2024

[cmaidaartworkblog]

Some hominids-in-progress I've had on lately: a Neanderthal shifting her weight in preparation to throw a spear, some improvements I made to the meshes and textures for my A. sediba and P. boisei skins, and skins I still have to texture for H. naledi and H. heidelbergensis Digital painting (Photopea, first image), Digital sculpture (Blender, last three images), 2024

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Returning to hominid facial anatomy once again, I was able to adapt my A. sediba muscle model onto the OH5 skull (P. boisei) too! I'm happy enough with it that I went ahead and rendered some skins for them as well. Selected all the right vertices and generated UV maps and everything. Hopefully the colors look as legible on your screens as they do on mine, these are still very much in progress.

My restoration of this individual was partly based on an earlier attempt at rendering Paranthropus, from back in 2019. There were a lot of elements that got tweaked or entirely changed up in the update, but the mouth got to stay the same between renderings. Having even a little understanding of the face muscles makes a visible difference from one model to another, and I'm sure there's still some parts I could improve on as I keep working in this vein. If anyone has more technical knowledge about this sort of thing than I do, feel entirely free to get at me : )

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Here's some hominid soft facial anatomy : )

The model on the right of frame, representing Australopithecus sediba, has been in sporadic progress for over a year now across a few programs, and I was able to create the model on the left of frame by conforming all the A. sediba elements to the Kabwe cranium (belonging to Homo heidelbergensis *or* H. bodoensis by some classifications). That latter process took place entirely in Blender over only a couple days, so I'm pretty happy with this method. While the skulls themselves aren't visible in these screenshots, they are part of the Blender file and were downloaded directly from MorphoSource, which was pretty helpful. Digital sculpture (SculptFab, SculptGL, 3D Builder, Blender), 2023-24

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Among many other questions on the various sites I posted my latest mapmaking project to, a couple people asked how I created the heightmaps for the Ayrum commission, and so I made a video going over some of my methods in a minor example project. Enjoy!

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Once I had enough high-resolution climate data to work with, the final part of the Climate phase was the creation of maps with discrete climate zones, which I produced in both the Trewartha classification scheme, left, and the Köppen classification scheme, right.

The final phase of the Ayrum mapmaking project was to create realistic satellite style maps, which began with mapping out soil colors and the ground cover of vegetation generally and tree-analogues specifically.

Once I knew where the plants belonged, I then determined what colors they'd be in the conditions they're adapted for, as seen in the maps, and under seasonal variation, with the chart showing how plants with certain adaptations react to seasonal changes in those conditions.

In these gifs we see the ground plants and tree canopies changing colors as the Solstices and Equinoxes expose them to greater or lesser rainfall and harsher or milder temperatures than what they're adapted for. Neither of these gifs provide a true image of what the surface looks like from space, but rather of the in-person appearance of whatever plants may be present.

Finally, using the vegetation density maps as raster masks for the seasonal plant color maps, and layering those with the snow-and-ice maps over the soil color map, we now have a much truer image of Ayrum's surface as of its (Northern) Winter, Spring, Summer, and Autumn months.

[cmaidaartworkblog]

Precipitation was the next dataset that I refined from the lower-resolution Panoply version, which started with applying the wind data (as seen above, I only combined and color-coded WBP's datasets and added a coastline overlay to produce this) to the elevation data in order to create detailed rain shadows.

Once I found the rain shadows and highlights (or the Orographic effect), I was able to apply those to the preexisting Precipitation dataset, and also make the continental interiors a little rainier and then apply a color gradient to the greyscale maps.

With the monthly precipitation established it was then possible to create an Annual Total precipitation map, revealing where the more consistently dry regions are.

Combining the monthly precipitation and temperature data (to wildly oversimplify) also allowed for monthly snow and ice depth maps, which were pretty consistent with Nikolai Lofving Hersfeldt's datasets. As you can see, Ayrum's high obliquity precludes year-round frozen poles.

The next phase of the Ayrum project was climate, which I'll introduce with the resource that made my work possible in the first place: these datasets created by Nikolai Lofving Hersfeldt, who runs WorldBuildingPasta and shared all of this with my client and me via Panoply. These were tremendously helpful and I wouldn't be able to achieve a fraction of the final detail without them.

My own adjustment to this data begins with Surface Temperature, which came down to correcting the coastlines (I mistakenly sent in a version of the elevation map that resulted in continental shelves appearing above sea level), refining the effects of elevation, and adding a color gradient.

I was then able to combine this data into Annual Minimum, Average, and Maximum temperature maps, seen below, which was pretty useful too.

One use for the Annual Average map, for example, was providing a baseline to compare each month's data against, seen in the sequence above.

And from the Annual Minimum and Maximum maps, I was able to create a map that presents the overall range of temperatures throughout the year, which does a good job of showing just how extreme the conditions are in higher latitudes and further inland.

[cmaidaartworkblog]

The next phase of the Ayrum project was climate, which I'll introduce with the resource that made my work possible in the first place: these datasets created by Nikolai Lofving Hersfeldt, who runs WorldBuildingPasta and shared all of this with my client and me via Panoply. These were tremendously helpful and I wouldn't be able to achieve a fraction of the final detail without them.

My own adjustment to this data begins with Surface Temperature, which came down to correcting the coastlines (I mistakenly sent in a version of the elevation map that resulted in continental shelves appearing above sea level), refining the effects of elevation, and adding a color gradient.

I was then able to combine this data into Annual Minimum, Average, and Maximum temperature maps, seen above, which was pretty useful too.

One use for the Annual Average map, for example, was providing a baseline to compare each month's data against, seen in the sequence above.

And from the Annual Minimum and Maximum maps, I was able to create a map that presents the overall range of temperatures throughout the year, which does a good job of showing just how extreme the conditions are in higher latitudes and further inland.

[cmaidaartworkblog]

These screenshots I took in Blender are the final product of a commission I worked on for over a year, of my client's planet Ayrum. These represent the planet as it appears at the Northern Spring Equinox, at various angles and different times of day. This project had multiple phases and produced many maps and figures, so I'll be making multiple posts about it over the course of multiple days, working from the earliest results up to the images used in these screenshots.

First, the tectonic history sequence, covering about 600 million years of activity. The colors of continental crust in the gif's top half represent which plate it will belong to in the end, and the colors used in the bottom half represent what plates they belong to at the time

With the tectonic history settled, it's easier to determine what the topography should look like. The two greyscale elevation maps start from the lowest trench depth and from sea level respectively, and the color-graded elevation map has dry land differentiated from bodies of water.

Dipping into Blender once again, with some screenshots where I used the color-graded elevation map as the image texture and the greyscale elevation map as the displacement texture, to emphasize the topography. This will be all for today, but there is much more to come. These maps were made for the user @umbrace-ramble, to whom I am very thankful for this commission and all the experience it inspired me to gain. Rendered in Photopea with the aid of Blender, screenshots taken in Blender, November 2022-January 2024

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Results from the Flocking #paleostream

Geosterbergia, Archocyrtus, Titanophoneus and Besanosaurus

In addition I fulfilled two more wishes for people who donated the Paleocene Kickstarter, Cotylorhynchus and Cervifurca.

[cmaidaartworkblog]

*Another* Archaeocete bust update that I posted to Twitter but forgot about sharing here, this time its my Georgiacetus render, redone this year to improve on the version I did in 2020. This one also got some additional mass packed on the bones and some new colors applied to it, compared to the original, and I hope someday to make a physical, life-size version of this piece, however long it takes to get to that point. Like B. cetoides, this ancient whale was also first found in the Southeastern U.S., but in Georgia instead, and its postcranial skeleton is rather disarticulated and incomplete. The earliest fossils of Georgiacetus vogtlensis are about 5 million years older than the first Basilosaurs, with a much more basal body plan: a larger and better developed pelvis, suggesting prominent legs (which would have been the main source of propulsion since it lacked flukes), a shorter torso and tail, and an altogether smaller body size (estimated to between 10 and 20 feet long). With the scarcity of postcranial material for this genus (such as limbs, certain vertebra, all but the tip of the tail, most of the ribs), our estimation of the animal is informed by fossil material from other, better represented Protocetids. Like the later appearing Basilosaurids, however, Georgiacetus's pelvis was not fused to its vertebrae, and their skulls are visually pretty similar. This mesh was rendered in Sculptfab and SculptGL, with these screenshots being taken in the latter program.