This past week, the Canadian actor William Shatner flew to space after getting invited by Jeff Bezos, the founder of Amazon. At the age of 90, he finally crossed the so-called final frontier. Shatner got famous for playing Captain James Tiberius Kirk from 1966 to 1969 in 79 episodes of the US TV series “Star Trek”. Later, he took over the role again in a couple of sequel cinema movies.
Although NASA investigated space travel and space exploration at that time, I assume, William Shatner never ever assumed to be once in space himself. He was an actor playing with other actors in a movie studio set-up like a (at that time) hyper-modern and futuristic command bridge of a star sheep. But, times are turning. “Being” the captain of a spaceship made him famous and can be considered as the foundation of his international career. Although there were a couple of further movies dedicated to space travel at that time, I’d consider this one as the archetype of space exploration movies. In my opinion, the egalitarian philosophy (gender and skin color are not important at all – for that time, these sets were extremely progressive although you can see from today’s point of view, that there is room for more) among crew members as well as between crew and aliens: observe but not interfere.
On Twitter, I saw a screenshot showing Shatner after having left the spaceship and quoting him, that would have been the dream of his life. Another commenter was quite upset about it. Why he could have done this at that age and it would have been better, a scientist or at least a younger person were shot to space.
I can understand Shatner and why he had not refused to accept the invitation. Since I’m a child I’m interested in space exploration. In my children’s room, I had a huge poster on one of the walls showing the Space Shuttle in all of its glory while riding on a cushion of fire and smoke up to the stars. I’m admiring the images taken from outside of our planet showing our planet, stars, or deep-sky objects. Over the years a couple of books found their way onto my bookshelf, starting from my childhood. Jesco von Puttkammer and Carl Sagan are among the authors and in the 1990s I started collecting digital images published by NASA on their quite new web page. One of the most impressive images I’ve ever seen is the rising earth about the moon surface taken by the Apollo 8 astronauts as they came from behind the Moon. You see the image on the NASA homepage. When I’d get such an opportunity, I’d try everything to be part of that special party. My perfect destination would be a stay at ISS for a couple of days. I’m so jealous of Alexander Gerst (Astro Alex) and the views he had during his spare time on ISS. You can see some of the images he took while on ISS on Twitter.
I know, I will never ever get such an invitation. Nor will I ever have enough money to pay for my own tourist’s flight. And, to be honest, currently, these tourist flights are only up to about 106 km above sea level and allow only a very short stay. The flight up and down lasts longer than the stay. So, it’s more like a “hey, I was there” than enjoying the experience.
On the other hand, it’s a huge amount of waste and pollution necessary for making such a trip possible.
I took that image above showing the Andromeda galaxy in February this year. I’m not totally happy with the result, but I guess, it’s quite ok. Photographing deep-sky objects from the earth is very challenging. They are not very bright, but very small and light pollution is a serious problem. OK, when knowing where and when to look, you can recognize Andromeda with your bare eyes as a tiny patch different in size, brightness, and color than the surrounding stars. But it’s still a challenge photographing it and for having a view, I’d definitely recommend using a binocular or better a stabilized telescope.
This is a follow-up post to last week. Go back, to read my post from the week before last, if you not already did.
This is a follow-up post to last week. Go back, to read my post from last week, if you not already did.
A few weeks ago, I was on the road quite early for capturing flowers right after sunrise. Unfortunately, they were not blooming when I arrived, because of the too cold temperature we had during the last couple of weeks.
On my way back, I stopped at this huge machine, standing in a vast hole in the ground. I’m standing at the edge of the hole. In the back, you can spot another of these machines right above the edge of the excavation. Also, compare it with the white car. This car is a pickup. So, it’s not that small. I’ve never before been so close to such a huge machine. It’s used as a stacker to put the unusable earth back in the hole because they only want to have the brown coal.
I already published images from that digging pit a couple of times. In this post, published about 10 years ago, you can get a bit of an overview. Or, here, you can see, how it looks at night. While you can here find an image of the hole taken with a fisheye lens.
Although I hate how they treat the earth so badly by grabbing brown coal from the ground for using it inefficiently to burn it for producing electricity power, I find these huge machines really fascinating. Nevertheless, I’m looking forward to the day they are not needed anymore.
Recently, I started analyzing my images a bit. You know, nearly all cameras are writing some metadata in the image files in addition to the image you’re capturing. I dug all this information out of my developed images but left the undeveloped raw data alone. In this analysis, I’ve included only landscape, macro, Astro, and wildlife images, but no people photography like portraits, models, weddings, or similar things.
I installed the open-source software DigiKam on my computer and configured an image directory. All of my developed images are stored in that directory, but in different folders for each trip. You can find out a bit more about my storage principles in one of my past articles.
DigiKam now read in all the metadata from the jpg files and stored them in an SQLite database. After terminating DigiKam, I was able to open the SQLite database with an SQLBrowser and select all the information I want. I first duplicated the database and started then normalizing the information. Over time, I used different software products for developing my images and not all of them used the exact same writing style for naming the different cameras and lenses.
I was very interested in getting to know my most favorite focal length over time. So, this was the first step: selecting the different camera bodies. Here they are listed with their sensor size and resolution in Mega-Pixel.
|sensor size||MP||used from .. to||shutter count|
|1||entry-level APS-C||10||2008 – 2009||3,700|
|2||adv. level APS-C||12||2009 – 2017||63,800|
|3||pro-level APS-C||24||2017 –||54,500|
|4||Full-Frame||24||2012 – 2014||35,000|
|5||Full-Frame||24||2015 – 2020||61,000|
Hint: body 2 was used a lot for wildlife in addition to the common jobs like landscape, portrait, model, event, and weddings until it was replaced by body 4. From that point in time, I used it only for wildlife until it was replaced by body 3, which is nearly solely used for wildlife. That’s the reason for the very high shutter count of body 3. Body 1 and 2 are already sold and body 4 was replaced because of a product recall. I still own body 5 but only using it for portraits or weddings because of the remote flash capabilities. The shutter has a proposed lifetime of 150,000 exposures (5 + 6) respectively 200,000 (3). So, no need to worry.
In the next table, we have the overall usage of a certain lens in combination with one of the camera bodies. The totals are as interesting as the number of images per camera body.
|10.5mm f2.8 fisheye||APS-C||106||28||134|
|16mm f2.8 fisheye||full frame||39||82||121|
|12-24mm f4.5-5.6||full frame||1||1|
|14-24mm f2.8||full frame||188||319||507|
|24-120mm f4||full frame||2||13||3647||6863||361||10886|
|70-200mm f2.8||full frame||4||1||5|
|70-300mm f4.5-5.6||full frame||4||860||438||142||1444|
|80-400mm f4.5-5.6||full frame||102||4073||239||1111||6||5531|
|150-500 f5-6.3||full frame||227||46||273|
|150-600mm f5-6.3||full frame||2564||38||2602|
|200-500mm f5.6||full frame||34||34|
|800mm f5.6||full frame||154||154|
|90mm f2.8 macro||full frame||15||15|
|100mm f2.8 macro||full frame||102||102|
|105mm f2.8 macro||full frame||53||117||60||556||73||859|
|20mm f1.8||full frame||165||17||182|
|12mm full manual lens||full frame||7||7|
Hint: I don’t own all of the used lenses. I owned some of them at a certain time and sold them already, while I got borrowed others. But, the cameras I got borrowed for testing purposes are not included in these statistics.
Hint 2: the totals per camera in table 2 don’t correspond to the number of shutter releases from table 1. In table 1 I have the total number of shutter releases from the counter inside the camera. The total per camera in table 2 is the number of developed images. Sometimes, I’m taking security shots and develop only one or doing HDR images, where 3 or more different exposed raw files are merged into one final image to benefit from the expanded dynamic range. Astro images are quite similar to HDRs, but here are tens up to hundreds of raw files merged. In wildlife, portrait, and wedding photography, you also take more images as you need for different purposes.
Hint 3: I left out all portrait, wedding, event, model, and engagement photos because I know the most favorite lens for this purpose: the 85mm prime, the 50mm prime as runner up, followed by the 35mm prime. These lenses are quite old. They were made for film cameras (pre-digital). They are perfectly sharp and don’t have distortions, as all modern lenses have (you usually don’t notice this fact, because of the firmware of the lens and the camera, where the distortion is automatically corrected more or less well. But the corrections have an influence on the sharpness. Therefore I’m preferring the prime lenses.
Next, I will see my most favorite focal lengths (shown as 35mm equivalent), aperture, and ISO values.
The last step will be a script, correcting the wrongly labeled images.