On June 19, 2013, the U.S. Geological Survey officially decommissioned Landsat 5 after an astonishing 29 years of operation. The satellite’s longevity was recognized by the Guinness Book of World Records, which dubbed Landsat 5 as the longest-operating Earth observation satellite.
I recently listened to Dr. Steve Covington — the flight systems manager for Landsat 5 since 2001 — recount some of the lucky circumstances and creative engineering that kept the satellite operating for nearly three decades. (The talk will be posted on the Library of Congress web site in the near future.) Here are some of the highlights.
Lucky circumstance 1: Landsat 5 had a twin, Landsat 4, which showed problems with its power system once it was in orbit. Those problems let engineers adjust Landsat 5 before it launched on March 1, 1984.
Lucky circumstance 2: Landsat 5 was equipped with a large auxiliary fuel tank designed to let the satellite fly down from its orbit to a lower orbit where astronauts could retrieve and repair it. The polar-orbiting space shuttle program that would enable these on-orbit repairs never got off the ground, and this left Landsat 5 with a whole lot of extra fuel. Mission operators used the fuel to extend the mission across decades.
Creative Engineering 1: In January 2005, Landsat 5’s primary solar array drive failed, and months later, in November, the backup drive failed. This key component turned the solar array to face the Sun straight on whenever the satellite was on the sunlit side of the Earth. Without the drive, the solar array was stuck in a single position, limiting the amount of energy it generated to power the instruments and spacecraft.
The failure of the drives looked to be a mission-ending event, since the Landsat 5’s batteries couldn’t be recharged sufficiently to continue science operations. But mission operation engineers came up with a novel solution: If the solar array couldn’t move, they would move the entire spacecraft. Before the satellite came across Earth’s shadow into the sunlight, they pitched the satellite to face the Sun. The satellite faced down again to acquire data, and then, approaching the shadow again, pitched out to face the Sun. This dance gave the satellite just enough extra Sun exposure to keep the batteries charged and execute its imaging duties.
Creative Engineering 2: Landsat 5 had four pathways for sending data to the ground: two communication links with relay satellites, and two direct downlinks to ground stations. The last of these failed in 2012, preventing the satellite from sending data from its primary instrument (the Thematic Mapper) to the ground. The secondary instrument, the Multispectral Scanner (MSS) had been turned off in 1995. Mission operations engineers realized that the communication links used by MSS were still good, and the mission could continue if the MSS still worked. Seventeen years after turning the instrument off, engineers powered it back on, and amazingly, it worked. This allowed Landsat 5 to acquire one more year of data until Landsat 8 was ready to take its place in early 2013.
Each month, Earth Observatory offers up a puzzling satellite image here on Earth Matters. The seventeenth puzzler is above. Your challenge is to use the comments section to tell us what part of the world we are looking at, when the image was acquired, and why the scene is interesting.
How to answer. Your answer can be a few words or several paragraphs. (Try to keep it shorter than 300 words). You might simply tell us what part of the world an image shows. Or you can dig deeper and explain what satellite and instrument produced the image, what spectral bands were used to create it, or what is compelling about some obscure speck in the far corner of an image. If you think something is interesting or noteworthy, tell us about it.
The prize. We can’t offer prize money for being the first to respond or for digging up the most interesting kernels of information. But, we can promise you credit and glory (well, maybe just credit). Roughly one week after a puzzler image appears on this blog, we will post an annotated and captioned version as our Image of the Day. In the credits, we’ll acknowledge the person who was first to correctly ID the image. We’ll also recognize people who offer the most interesting tidbits of information. Please include your preferred name or alias with your comment. If you work for an institution that you want us to recognize, please mention that as well.
Recent winners. If you’ve won the puzzler in the last few months, please sit on your hands for at least a few days to give others a chance to play.
One of the wonderful things about working for the Earth Observatory is that we often get first crack at examining imagery from satellites new and old. It’s been especially exciting to look at data from Landsat 8, a joint U.S. Geological Survey and NASA mission launched in February 2013.
But with new things comes new challenges. We’ve had some odd problems with the very intense memory demands of Landsat 8 imagery, for example. And when I saw the image below, I thought for sure I had stumbled on a processing error.
Oh dear. Look at that ripple pattern along the river banks. Superficially, it looks a lot like a software processing error. New code I wrote: my error, right? In fact, at first glance, it looked a lot like Landsat data of a decade or so ago when the source files were being distributed with nearest-neighbor resampling–a technique used in remapping and resizing data which limits interactions between adjacent measures, something often useful in science measurements, but which causes jagged-looking edges. Since this was not the first time my code had done something unexpected, it was the obvious first place to look for the cause. The software failed me! Again!
However, a quick glance through the data files showed that, whatever was going on, it was coming from the source data: the same rippling showed up in all the bands. Ha! Someone else’s software had failed!
Because Landsat 8 is so new, it is easy to assume maybe I was not the only one having occasional processing problems with old software on new data. There was one more check I should have done before contacting customer service at USGS, but…
…I didn’t think of it. If you see something odd in imagery, it is always good to check reality. In this case, a quick zoomed-in view in Google Earth (as shown here) would have informed me that the jagged edges along the banks of the river in the imagery are real jagged edges along the banks of the river.
In hindsight, there were other clues. Notice that the jagged features are present in some places and not others. And notice that the rippled pattern along the banks bends and curves with the flow of the river. A processing artifact might only show up on very strongly contrasting features (the boundary between land and water here, for example), but would most likely be aligned consistently through the image. It wouldn’t appear and disappear like it does here, and it would probably be more regular. It would probably distort in the same direction every time it happened.
In the end, it turns out that all the new systems were working just fine and there really is a very oddly shaped series of features along the banks of the Elbe River near Wittenberg, presumably to stablize the banks of the river and control sediment flow.
But there’s not much they can do in the face of severe flooding.
Today’s guest post is from Kate Ramsayer of the NASA Earth Science News Team. Kate wrote the caption for today’s Image of the Day about El Paso and the mountains of data collected by Landsat over four decades.
When the first Landsat satellite — originally called the Earth Resources Technology Satellite (ERTS) — launched in 1972, it was no small feat to visualize the data it sent back and to conduct research with it.
“When ERTS was first launched, there was one cathode ray tube in the country that could take in the digital data and display an image,” said Jeff Masek, Landsat project scientist at NASA Goddard.
In the early years, satellite observations of the light reflected off of Earth were transmitted to receiving stations and mailed to processing centers. Computers translated the image data into photographic prints or transparencies that could be placed on light tables for interpretation. Alternatively, computers translated the numbers in each pixel into alpha-numeric symbols that were printed on large reams of paper. Analysts, often graduate students, could then color-in the symbols with crayon or magic markers. Standing on ladders over the colored-in data, they’d try to visualize the landscape represented by the maps.
“Things were pretty primitive in those days,” Masek said. “People say, ‘Why didn’t they produce a global land cover map in those first few years?’ They were lucky to be able to look at one image for a Ph.D. dissertation.”
The following is a guest post from Erin Jones (pictured above), the scientific outreach lead for the Global Modeling and Assimilation Office at Goddard Space Flight Center. As a graduate student at Purdue University, she used to chase tornadoes.
June 2, 2013, started as most Sundays do. My alarm went off; I got out of bed; I came downstairs, and I turned on my computer. I logged on to facebook. A quick look at my news feed told me that this Sunday would not be the same as most Sundays:
Getting lots of rumors that veteran chasers were killed by the El Reno tornado. I really hope this is not real.
… just received the news of the possible passing of Tim, Carl and Paul. We are in total shock… God rest their souls if this is true.
Hopes that messages about Tim Samaras are not true… Bad news if this is true…
I put my hand to my chest.
The rumors were true. Tim Samaras, his son Paul, and his chase partner Carl Young were gone. They had been killed while chasing a storm on May 31 near El Reno, Oklahoma, when a large tornado hit their car and reduced it to scrap metal.
I was in shock.
The storm that produced the El Reno tornado, as seen from the vantage point of mobile Doppler radar DOW8, near Mustang, OK. Photo courtesy of Paul Robinson.
The sad truth of the matter is that many in the community have thought for years that it was only a matter of time before a storm chaser was killed. Since the practice of storm chasing began over 50 years ago, not a single chaser had died in pursuit of a storm. Over the past several years, however, increased media coverage and TV shows like Storm Chasers have glamorized chasing and spurred the growth of an entire industry built around following storms.
The number of chasers has exploded, and it has made chasing for science more difficult and dangerous. I’ve seen it. I’ve felt what it’s like to be on a storm, just hoping that the circulation getting ready to pass over your head stays aloft because you’re stuck in chaser-induced gridlock and there’s no way you’d be able to escape if a tornado forms. I’ve known that fear. It’s like we have been on borrowed time.
As much as I dreaded the day when I would hear that a tornado had killed a storm chaser, I thought I was prepared for it. But nothing could have prepared me for what I heard on Sunday morning. Tim Samaras—a pillar of the chase community—was dead. He was a well-respected, veteran chaser. He wasn’t out for the thrill, and he wasn’t out to get the best picture or to take some extreme video. He was a serious scientist. And he was gone.
These questions have been at the forefront of the minds of many of my friends and colleagues over the past few days. As people begin to piece together accounts of what happened…as they process and analyze the data that were collected during the storm, a clearer picture is beginning to emerge. The tornado that hit near El Reno was more than 2.5 miles wide, making it the widest tornado ever recorded. It had a multiple vortex structure with wind speeds of up to 296 miles per hour. Toward the end of its life, it became occluded and turned northeast, deviating from its forecast path.
Tim Samaras and Carl Young. Photo courtesy of Ryan McGinnis.
Tim Samaras and his crew had always chased safely. They knew what they were doing but it didn’t matter. Had they been caught off guard? Had they ended up stuck in traffic? Were they driving on unpaved roads that were difficult to navigate in storm conditions? Was the tornadic circulation so large that it was impossible for them to get to safety? We still don’t know.
Many of my friends were out there that day. By chance or circumstance, they all stationed themselves out of harm’s way. Three of them–Paul Robinson, Eddie Smith, and Jon Lutz–were several kilometers away from the tornado, collecting mobile Doppler radar data on the storm when it hit Tim Samaras. I asked them if they had any thoughts or stories they’d like to share about what happened.
“I’m not sure what to contribute,” Eddie said. “At the same time Paul, Jon, and I were high-fiving each other over our great positioning and the phenomenal data set we were recording, we were watching, in real-time, this thing kill our friends. How do you reconcile that?”
Jon reflected that “that thing could have killed any of us, depending on which way it turned.”
And Paul told me how he was struck by a sense of eerie irony when they ended up in Moore, Oklahoma, after fleeing the storm, where they then witnessed an EF-0 tornado disturb the same landscape that an EF-5 tornado had devastated just two weeks before.
We still don’t have a great understanding of how tornadoes form, and we still don’t know much about what the wind fields are like near the ground. Tim Samaras spent his career trying to answer these questions so that the losses due to tornadic storms might be minimized. When Tim left this world, his work was not done. It would be a disgrace to his memory if we were to stop trying to collect scientific data on severe storms and to retard the progress on tornado research that he so diligently strove for.
During a chase on May 19, 2010, Jones’ team had to abort operations because heavy traffic made their attempts to collect data unsafe. Credit: Erin Jones.