This image was acquired on June 27, 2015, by the Operational Land Imager on Landsat 8. Read more about the image here.
What was that brain-like pattern featured in our July puzzler and how did it form? The key insight—which none of the hundreds of readers who commented mentioned—was that the pattern was caused by a network of stream valleys and bands of vegetation that follow the contour of the hills. (Read our July 26 Image of the Day to find out why the vegetation grows in bands.) However, reader Stephanie Wurdinger did nail the location on both Facebook and our Earth Matter blog. “This is along the north coast of Somalia between Dayaha and Maydh, in Sanaag region. Mt Shimbiris is just off the upper right hand corner of this image. I believe it is part of the Maydh greenstone belt,” she wrote.
One of the more interesting things about the forests of the Cal Madow is that they are important sources of frankincense and myrrh, the fragrant resins made famous by the Biblical account of three kings bringing them to Bethlehem as gifts. For a more modern take on the frankincense and myrrh trade, check out the video put together by the the Institute for Environmental Diplomacy and Security at the University of Vermont. Skip ahead to mintute 2:30 to join the producers as they bump over rough mountain roads in Somaliland looking for frankincense. The same organization has posted a report about the frankincense industry in Somaliland with many more details.
Comments Off on July Puzzler Answer: Forests of the Cal Madow
Every month on Earth Matters, we offer a puzzling satellite image. The July 2015 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, what the image shows, 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 200 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, 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 about the geological, meteorological, or human processes that have played a role in molding the landscape. Please include your preferred name or alias with your comment. If you work for or attend 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 or work in geospatial imaging, please sit on your hands for at least a day to give others a chance to play.
Releasing Comments. Savvy readers have solved some of our puzzlers after only a few minutes or hours. To give more people a chance to play, we may wait between 24-48 hours before posting the answers we receive in the comment thread.
This is a cross-post from Laura Rocchio and our colleagues at NASA’s Landsat Science Team.
The European Space Agency’s Sentinel-2A successfully launched into orbit on June 22, 2015, from Europe’s Spaceport in Kourou, French Guiana, aboard a Vega rocket (10:52 p.m. local time; 01:52 GMT).
The Sentinel-2A satellite has spectral bands similar to Landsat 8’s (excluding the thermal bands of Landsat 8’s Thermal Infrared Sensor). The placement of the Sentinel-2A bands, as compared to Landsat 8 and Landsat 7 bands, can be seen in the graphic below.
The main visible and near-infrared Sentinel-2A bands have a spatial resolution of 10 meters, while its “red-edge” (red and near-infrared bands)—specifically designed to monitor vegetation—along with its two shortwave infrared bands have a 20-meter spatial resolution, and its coastal/aerosol, water vapor, and cirrus bands have a 60-meter spatial resolution.
During the development of Landsat 8 and Sentinel-2A, calibration scientists from both projects worked together to cross-calibrate the sensors. Many scientists and researchers are looking forward to collectively using data from Landsat 8 and Sentinel-2A.
Sentinel-2A alone provides 10-day repeat coverage of Earth’s land areas. In combination with the 8-day coverage from Landsat 7 and 8 combined, users can look forward to better-than-weekly coverage at moderate resolution. Repeat coverage capabilities will further increase with the planned launch of a second Sentinel-2 satellite (Sentinel-2B) in 2016.
According to ESA, “As well as monitoring plant growth, Sentinel-2 will be used to map changes in land cover and to monitor the world’s forests. It will also provide information on pollution in lakes and coastal waters. Images of floods, volcanic eruptions and landslides will contribute to disaster mapping and helping humanitarian relief efforts.”
After the successful Sentinel-2A launch, Dr. Garik Gutman, the NASA Land Use / Land Cover Change program manager, said, “We are looking forward to new exciting data to complement Landsat observations and to collaborative research—especially because ESA followed USGS in its open data policy.” This sentiment is echoed by many in the Landsat community.
Our July 16 Image of the Day—Changing Forest Cover Since the Soviet Era—features a Landsat-derived map showing how forests have changed in Eastern Europe since 1985. After exploring the three areas we highlighted, I highly recommend browsing the map at full resolution using either Google Earth or GigaPan. The amount of detail you will find is extraordinary. There are dozens of other interesting forest loss and gain hot spots that we could have highlighted. In fact, we may publish additional stories using these data, so please let us know if you are aware of local stories of forest change in eastern Europe that deserve more attention.
While the satellite maps offer invaluable “big picture” perspective, ground photographs really bring the changes to life. Peter Potapov, the University of Maryland scientist who led the mapping effort, passed along a few photographs taken during his field research in Russia. It is one thing to know that a brown pixel in the maps indicate forest loss and the a green pixel indicates gain. It becomes real when you can actually see charred trunks after a forest fire or stands of saplings springing up in abandoned Soviet farm fields.
Logging site in the Vladimir region of Russia. Photo Credit: Peter Potapov.
Spruce trees killed by bark beetle in the Vladimir region of Russia. Photo Credit: Peter Potapov.
Charred trunks caused by a forest fire in the Vladimer region of Russia. Photo credit: Peter Potapov
Pine forests in an abandoned pasture in the Vladimir region of Russia. The pine trees are about ten years old. Photo Credit: Peter Potapov.
Birch forest growing on abandoned farmland in the Nizhny Novgorod region of Russia. Photo Credit: Peter Potopov
Early stages of forest recovery in abandoned farmland in the Kirov region of Russia. Photo Credit: Peter Potapov
Many readers were convinced that our June Puzzler (image above) showed Nazca lines in southern Peru. There certainly were lines in the image, but they were located about 10,000 kilometers (6,000 miles) away from Peru on a plateau in southern Libya. While the Nazca lines were probably created for religious purposes, the grid lines in Libya had a very different raisond’être: oil exploration.
As Stefano correctly noted at 12:26 p.m. on June 23, the lines were tracks left over from a seismic survey. While a layer of rocks, gravel, and ancient stone tools carpet most of the plateau, lines of large “thumper” trucks that use a vibrating metal plate to press down against the ground likely created the grid pattern. When they drove around prospecting the area with seismic sensors, the trucks kicked up a very fine layer of dust that was lighter brown than the rest of the surface. Less than two hours after Stefano weighed in, Miles Saunders explained much of this.
Nazca lines in southern Peru. Read more about them here.
Twenty minutes later, Franco B. weighed in with some more key details. “This looks like geophysical prospection lines in some oil field in an arid zone, each line would be a succession of geophones placed in order to make seismic sections. The scattered dots are probably oil wells. The combination of lines at 90º allows to make very detailed 3D maps of the geological structures in depth, in order to improve the oil and gas exploration. All this overlays on what looks like an intermittent dendritic drainage pattern, evidence of the arid climate,” he said.
To get a sense of how the “thumper” trucks work, check out the video below from Maurin Media.
Here is a view of what the tracks look like on the ground.
Photograph courtesy of Marta Lahr, University of Cambridge.
Meanwhile, twelve minutes before Stefano mentioned seismic lines on our blog, Kaye Simonson noted on our Facebook page that the grid was related to seismographs. About ten minutes later, Chris Leonard posted the exact coordinates on Facebook. By that afternoon, Leonard had figured out that the image featured seismic grid lines related to oil exploration. He worked it out by locating an archaeological study published in PLOS One that included the telling figure shown below. As the authors of that paper explain, the top part of the figure (a) shows the location of the grid lines that were laid out for oil exploration. The middle part (b) shows where archaeologists discovered stone tools (lithics) during a sweep before the seismic survey. A white circle indicates the presence of tools; larger circles indicate a higher density of stone tools. The bottom part (c) shows a more detailed view of a small portion of the plateau.