And for a break from solar cars, here are some sulphur-crested cockatoos enjoying the Australian winter sun:
It’s solstice time in a few days, so here is an infographic on the seasons (click for hi-res image):
Infographic constructed using R (with DescTools::DrawCircle, rasterImage, layout, and the suncalc package for day length calculation). Images used are a diagram by “Colivine,” paintings by Arthur Streeton and Joseph Farquharson, and two photographs of my own.
Winter is here (in the Southern Hemisphere, at least), and the constellation Scorpius always heralds the southern winter’s icy sting. The image below is based on a vintage astronomical illustration, but I have corrected the star positions of the major stars and indicated their apparent magnitude (brightness) and approximate colour (based on spectral class). It is interesting to compare the image with this quality photograph.
Generations of astronomers have memorised the O–B–A–F–G–K–M stellar classification system developed by Annie Jump Cannon with the mnemonic “Oh, Be A Fine Girl/Guy/Gal/Gentleman, Kiss Me.” Scorpius does not contain any bright O-class stars, but it is easy to see stars ranging from the hot blue-white B class to the cooler orange-red M class (stars which are only “red hot”).
The most obvious star in Scorpius is the enormous red supergiant Antares, which has that name because it is easily confused with the planet Mars (Ares). It is also known as “Cor Scorpii” (the heart of the scorpion). It is easy to recognise the curved tail as well, with the stingers Shaula and Lesath at its tip. It is less obvious which stars are the scorpion’s claws – the artist here has drawn the left claw extended so as to reach the dim white star Psi Scorpii. Other artists draw the scorpion facing more to the right, with the line of blue-white stars being the claws.
Infographic constructed using R (with lm to map true sky coordinates to image coordinates, rasterImage for the background, and the showtext package for fonts).
Recently, somebody pointed me at phenology wheels, which are a popular tool for nature study among teachers and homeschoolers. Nature study is all about careful observation and finding patterns, and phenology wheels help with both. Every month, students draw a picture of what they see in the garden or on a nature walk, and the completed phenology wheel then shows an annual pattern. Other activities are possible – see this University of Wisconsin-Madison Arboretum document.
The picture below shows a pair of partially complete mother/daughter phenology wheels from the very useful Nature Study Australia website (they are using the central circle to show indigenous seasons). It is helpful to outline each month’s section in felt-tip pen:
Mother and daughter phenology wheels from naturestudyaustralia.com.au
Like nature journals, this is an activity both fun and educational!
Credits: lavender watercolour painting by Karen Arnold, sunflowers by Vincent van Gogh, butterfly from here, font is Jenna Sue, wheel constructed using R (with DescTools::DrawCircle, rasterImage, and the showtext package).
As a result of a discussion with a photographer friend of mine, I’ve been thinking (not for the first time) about visualising the colour palette of images. Consider this sunset, for example (a picture I took in Adelaide 8 years ago):
The photograph is rich in yellow and orange. However, the apparent blue in the sky is actually grey, and the apparent grey of the sea is actually brown. If we postulate a standard set of 35 plausible pencil colours, and map each pixel to the closest-matching pencil colour, we get this (I have done the comparison in RGB space):
Then we can visualise the colour palette of the image by showing the wear on the virtual pencils, if each virtual pencil has been used to colour the corresponding pixels. It can be seen that a lot of orange, brown, and grey was used (click to zoom):
Conversely, this beach scene (photographed in Vanuatu in 2016) is rich in blues:
The warm light greys of the beach don’t quite find an exact match among the pencils, but the other colours match fairly well:
And here is the pencil visualisation (click to zoom):
If, rather than using a standard set of colours, we extract the pencil colours from the image itself (image quantisation), fewer pencils will, of course, be required:
The fit to the original image will be much closer as well:
So this is a trick to remember for another day – pencil visualisations!