Popular Posts

Showing posts with label Satellite Imagery. Show all posts
Showing posts with label Satellite Imagery. Show all posts

The Future of Earth - Global Warming




Video - The Future of Earth with Global Warming

Abbreviated version of the visualization 'Heating Up,' which depicts climate model projection of 21st century global temperatures. Credit: NASA Scientific Visualization Studio.


“Do we think about the aerosol propellant in our underarm deodorant every day?” Gavin Schmidt, climatologist and director of The Goddard Institute for Space Studies (GISS), asked me. “I don’t think we even have aerosols anymore,” I answered, wondering where he was going with this.

“That’s the point,” he continued, “and nobody cares. Nobody cares where your energy comes from; nobody cares whether your car is electric or petrol. People confuse energy supply with where the energy is supplied from.” He was trying to make the point that as long as people have the things they want, it doesn’t matter, to the vast majority of us, how we get them. This means that as long as the light switch still turns on the lights, most people would barely notice if we were to shift from burning fossil fuels to energy sources with less impact on Earth’s climate (just as people don’t notice that ozone-depleting propellants aren’t used in aerosol cans any more).

I was eager to speak with Dr. Schmidt because of his passion for communicating climate science to public audiences on top of his work as a climatologist. Schmidt is a co-founder and active blogger at Real Climate and was also awarded the inaugural Climate Communications Prize, by the American Geophysical Union (AGU) in 2011. “My goal in communicating,” he explained, “is a totally futile effort to raise the level of the conversation so that we actually discuss the things that matter.”

Since the mere mention of a computer model can cause an otherwise normal person’s face to glaze over, I thought Schmidt, a leader in climate simulations and Earth system modeling, would be the ideal candidate to explain one of the most important, yet probably one of the most misunderstood, instruments scientists have for studying Earth’s climate. See, people commonly confuse climate and weather, and this confusion is perhaps most pronounced when it comes to understanding the difference between a weather forecast and a climate simulation.
Numerical laboratory

Schmidt’s work routine is much like that of any other scientist. He spends a few months preparing experiments, then a few more months conducting the experiments, then a few more months refining and improving the experiments, then a few more months going back and looking at fine details, then a few more months … you get the idea. Climate scientists use complex computer simulations as numerical laboratories to conduct experiments because we don’t have a bunch of spare Earths just lying around. These simulations model Earth’s conditions as precisely as possible. “A single run can take three months on up on super computers,” Schmidt said. “For really long runs, it can take a year.” NASA scientists can reserve time at the NASA Supercomputer Center with High-End Computing Capability to run simulations. Like an astronomer who reserves time on a large telescope to run her experiments, Schmidt books time on these computers to run his.

Schmidt asks the computer to calculate the weather in 20-minute time steps and see how it changes. Every 20 minutes it updates its calculation over hundred-year or even thousand-year periods in the past or the future. “The models that we run process about three to four years of simulation, going through every 20 minute time step, every real day.”

A typical climate simulation code is large, as in 700,000 lines of computer code large. For comparison, the Curiosity Rover required about 500,000 lines of code to autonomously descend safely on Mars, a planet 140 million miles away with a signal time delay of about 14 minutes. The size of a typical app, such as our Earth Now mobile app, is just over 6,000 lines of code. Climate simulations require such a large quantity of code because Earth’s climate is so extraordinarily complex. And, according to Schmidt, “Complexity is quite complex.”

Like a scientist who runs an experiment in a science lab, climate modelers want code that’s consistent from one experiment to another. So they spend most of their time developing that code, looking at code, improving code and fixing bugs.

The model output is compared to data and observations from the real world to build in credibility. “We rate the predictions on whether or not they’re skillful; on whether we can demonstrate they are robust.” When models are tested against the real world, we get a measure of how skillful the model is at reproducing things that have already happened. Then we can be more confident about the accuracy in predicting what’s going to happen. Schmidt wants to find out where the models have skill and where they provide useful information. For example, they’re not very useful for tornado statistics, but they're extremely useful on global mean temperature. According to Schmidt, the credible and consistently reliable predictions include ones that involve adding carbon dioxide to the atmosphere. “You consistently get increases in temperature and those increases are almost always greater over land than they are in the ocean. They’re always larger in the Arctic than in the mid-latitudes and always more in the northern hemisphere than the southern, particularly Antarctica. Those are very, very robust results.”

Lately, his team has been working on improving the code for sea ice dynamics to include the effects of brine pockets (very salty fluid within the ice matrix) as well as the wind moving the ice around. For example, to understand the timeline for Arctic sea ice loss, his team has to work on the different bits of code for the wind, the temperature, the ocean and the water vapor and include the way all these pieces intersect in the real world. After you improve the code, you can see the impact of those improvements.

I asked Schmidt what people’s behavior would look like “if they understood that burning fossil fuels produces carbon dioxide, which causes global warming.” He replied, “People would start focusing on policies and processes that would reduce the amount of fossil fuels without ruining the economy or wrecking society.” Then he added, “I think, I hope! that people will get it before it’s too late.”

I hope so, too...


Gavin Schmidt

Communications Specialist                                           NASA Climate - Earth Right Now
Laura Faye Tenenbaum is a science communicator at NASA's Jet Propulsion Laboratory and teaches oceanography at Glendale Community College.           Contact Laura


Spectacular Drone Video Footage - Maasai Mara Wildebeest Migration

Last year, I embarked on an unforgettable 19 000km adventure that will stay with me for a very long time. I crossed the African continent alone on a motorcycle. The journey took about 6 months, as I took my time to learn more about the 15 African countries I was travelling through .


_MG_4581_S


I tried to help where I could, particularly with charities for children and wildlife conservation. I also captured many images, many of which are on the Facebook page of Two Wheels Across and documented the entire journey in videos for my Youtube channel.






_MG_4421_S


One of the exciting parts of my adventure was Casper the friendly drone, a Quadcopter that I used as often as I could to capture the beauty of Africa from the air.


quadcopter


I am excited to share one of the videos I filmed with you. I was fortunate to be in Kenya’s Maasai Mara during the migration and I captured the river crossing from the air. I also danced with an elephant, ran with wildebeests and kept three lions company for a few minutes. I hope you will enjoy the film!




 Guest Blogger in Animal Encounters                             Africa Geographic

Satellite Image - The Nile Illuminated at Night

Nile River Delta at Night
acquired October 28, 2010 download large image (606 KB, JPEG, 1440x960)
                           
One of the fascinating aspects of viewing Earth at night is how well the lights show the distribution of people. In this view of Egypt, we see a population almost completely concentrated along the Nile Valley, just a small percentage of the country’s land area.

The Nile River and its delta look like a brilliant, long-stemmed flower in this astronaut photograph of the southeastern Mediterranean Sea, as seen from the International Space Station. The Cairo metropolitan area forms a particularly bright base of the flower. The smaller cities and towns within the Nile Delta tend to be hard to see amidst the dense agricultural vegetation during the day. However, these settled areas and the connecting roads between them become clearly visible at night. Likewise, urbanized regions and infrastructure along the Nile River becomes apparent (see also The Great Bend of Nile, Day & Night.)

Another brightly lit region is visible along the eastern coastline of the Mediterranean—the Tel-Aviv metropolitan area in Israel (image right). To the east of Tel-Aviv lies Amman, Jordan. The two major water bodies that define the western and eastern coastlines of the Sinai Peninsula—the Gulf of Suez and the Gulf of Aqaba—are outlined by lights along their coastlines (image lower right). The city lights of Paphos, Limassol, Larnaca, and Nicosia are visible on the island of Cyprus (image top).
Scattered blue-grey clouds cover the Mediterranean Sea and the Sinai, while much of northeastern Africa is cloud-free. A thin yellow-brown band tracing the Earth’s curvature at image top is airglow, a faint band of light emission that results from the interaction of atmospheric atoms and molecules with solar radiation at approximately 100 kilometers (60 miles) altitude.

Astronaut photograph ISS025-E-9858 was acquired on October 28, 2010, with a Nikon D3S digital camera using a 16 mm lens, and is provided by the ISS Crew Earth Observations experiment and Image Science & Analysis Laboratory, Johnson Space Center. The image was taken by the Expedition 25 crew. The image in this article has been cropped and enhanced to improve contrast. Lens artifacts have been removed. The International Space Station Program supports the laboratory as part of the ISS National Lab to help astronauts take pictures of Earth that will be of the greatest value to scientists and the public, and to make those images freely available on the Internet. Additional images taken by astronauts and cosmonauts can be viewed at the NASA/JSC Gateway to Astronaut Photography of Earth. Caption by William L. Stefanov, NASA-JSC.
Instrument(s): 
ISS - Digital Camera

City Lights Illuminate the Nile
acquired October 13, 2012 download large image (2 MB, JPEG, 3000x3000)
acquired October 13, 2012 download GeoTIFF file (5 MB, TIFF)
acquired October 13, 2012 download Google Earth file (KML)
                           
The Nile River Valley and Delta comprise less than 5 percent of Egypt’s land area, but provide a home to roughly 97 percent of the country’s population. Nothing makes the location of human population clearer than the lights illuminating the valley and delta at night.

On October 13, 2012, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite captured this nighttime view of the Nile River Valley and Delta. This image is from the VIIRS “day-night band,” which detects light in a range of wavelengths from green to near-infrared and uses filtering techniques to observe signals such as gas flares, auroras, wildfires, city lights, and reflected moonlight.

The city lights resemble a giant calla lily, just one with a kink in its stem near the city of Luxor. Some of the brightest lights occur around Cairo, but lights are abundant along the length of the river. Bright city lights also occur along the Suez Canal and around Tel Aviv.

Away from the lights, however, land and water appear uniformly black. This image was acquired near the time of the new Moon, and little moonlight was available to brighten land and water surfaces.

Learn more about the VIIRS day-night band and nighttime imaging of Earth in our new feature story: Out of the Blue and Into the Black.
  1. References

  2. United Nations Environment Programme. (2008). Africa: Atlas of Our Changing Environment. Division of Early Warning and Assessment, United Nations Environment Programme, Nairobi, Kenya.
NASA Earth Observatory image by Jesse Allen and Robert Simmon, using VIIRS Day-Night Band data from the Suomi National Polar-orbiting Partnership. Suomi NPP is the result of a partnership between NASA, the National Oceanic and Atmospheric Administration, and the Department of Defense. Caption by Michon Scott.
Instrument(s): 
Suomi NPP - VIIRS
NASA Earth Observatory





2014 - Satellite Imagery - Arabian Ramadan and Eid at Night

The Lights of Ramadan and Eid al-Fitr
Color bar for The Lights of Ramadan and Eid al-Fitr
acquired 2012 - 2014 download large image (1 MB, JPEG, 3099x3323)
                           
In December 2014, scientists using a NASA-NOAA satellite announced that they had detected significant changes in the amount and distribution of nighttime lighting during holiday seasons in the Middle East and North America. For instance, nighttime lights in some Middle East cities were 50 to 100 percent brighter during the holy month of Ramadan.


The maps on this page show changes in lighting intensity and location on the Arabian Peninsula and in the countries along the eastern Mediterranean coast. They are based on data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite. The maps compare the night light signals from the months of Ramadan in 2012–2014 (parts of July and August in these years) to the average light output for the rest of 2012 to 2014.


Green shading marks areas where light usage increased during the holy days; yellow marks areas with little change; and red marks areas where less light was used.


The VIIRS instrument on Suomi NPP can observe faint light signals on the night side of our planet, including reflected moonlight, airglow, auroras, and manmade light sources. In 2012, scientists assembled a new composite map of Earth at night created from averaged data from 22 nights of VIIRS data. The new 2014 analysis of holiday lights uses a new algorithm that filters out moonlight, clouds, and airborne particles to show city lights on a nightly basis.


The idea to examine holiday lights arose in 2012 out of an issue with some nighttime images of Cairo, Egypt. A science team led by Miguel Román of NASA’s Goddard Space Flight Center noticed a discrepancy in city light signals while performing quality checks on early mission data. The science team realized that there was either an error in the data or an unknown signal that they should study further.


After digging deeper, the team found that the large increase in light output around the Egyptian capital corresponded with the holy month of Ramadan. The change made sense because Muslims fast during daylight in Ramadan, pushing meals, social gatherings, commerce and other activities into nighttime hours. To confirm that the nighttime signal was not merely an instrument artifact, the team examined all of the nighttime data from spring 2012 through autumn 2014.


They found that the peaks in light use closely tracked the Islamic calendar, as Ramadan shifted earlier in the summer each year.


Light use in Saudi Arabian cities, such as Riyadh and Jeddah, increased by 60 to 100 percent throughout the month of Ramadan. Light use in Turkish cities, however, increased far less. Some regions in Syria, Iraq, and Lebanon did not have an increase in light output—and some even demonstrated a moderate decrease, possibly due to unstable electrical grids and conflict in the region. Click on the large, downloadable map for a closer view of the differences.


acquired 2012 - 2014


“Even within majority Muslim populations, there are a lot of variations,” said Eleanor Stokes, a Yale researcher and collaborator with Román. “What we have seen is that these lighting patterns track cultural variation within the Middle East.”


These variations appear even at the neighborhood level. Román and Stokes compared night lights data from Cairo with socioeconomic data, voting patterns, access to public sanitation, and literacy rates. Some of the poorest and most devout areas observed Ramadan without significant increases in light use throughout the month, choosing—whether for cultural or financial reasons—to leave their lights off at night. But during the Eid al-Fitr celebration that marks of the end of Ramadan, light use soared across all study groups, as all the neighborhoods appeared to join in the festivities.


“Whether you are rich or poor, or religious or not, everybody in Egypt is celebrating Eid al-Fitr,” Román said. This is telling Stokes and Román that energy use patterns are reflecting social and cultural identities, as well as the habits of city dwellers, and not just price or other commercial factors.


NASA Earth Observatory





A History of the Landsat Science Satellite

Landsat 1 • Landsat 2 • Landsat 3 • Landsat 4 • Landsat 5 • Landsat 6 • Landsat 7 • Landsat 8

From the Beginning

“The Landsat program was created in the United States in the heady scientific and exploratory times associated with taming the atom and going to the Moon,” explains Dr. John Barker. In fact, it was the Apollo Moon-bound missions that inspired the Landsat program. During the early test bed missions for Apollo, photographs of Earth’s land surface from space were taken for the first time.






“This photography has been documented as the stimulus for Landsat,” explains Dr. Paul Lowman, who proposed the terrain photography experiment for the last two Mercury missions, the Gemini missions, and the Apollo 7 and 9 missions.


Thor-Delta rocket prepared to launch Landsat 1, 1972.
Thor-Delta rocket prepared to launch Landsat 1, 1972.

In 1965, director of the U.S. Geological Survey (USGS), William Pecora, proposed the idea of a remote sensing satellite program to gather facts about the natural resources of our planet. Pecora stated that the program was “conceived in 1966 largely as a direct result of the demonstrated utility of the Mercury and Gemini orbital photography to Earth resource studies.”


While weather satellites had been monitoring Earth’s atmosphere since 1960 and were largely considered useful, there was no appreciation of terrain data from space until the mid-1960s.
So, when Landsat 1 was proposed, it met with intense opposition from the Bureau of Budget and those who argued high-altitude aircraft would be the fiscally responsible choice for Earth remote sensing.


Concurrently, the Department of Defense feared that a civilian program such as Landsat would compromise the secrecy of their reconnaissance missions.
Additionally, there were also geopolitical concerns about photographing foreign countries without permission.


In 1965, NASA began methodical investigations of Earth remote sensing using instruments mounted on planes. In 1966, the USGS convinced the Secretary of the Interior, Stewart L. Udall, to announce that the Department of the Interior (DOI) was going to proceed with its own Earth-observing satellite program.


This savvy political stunt coerced NASA to expedite the building of Landsat. But, budgetary constraints and sensor disagreements between application agencies (notably the Department of Agriculture and DOI) again stymied the satellite construction process.
Finally, by 1970 NASA had a green light to build a satellite. Remarkably, within only two years, Landsat 1 was launched, heralding a new age of remote sensing of land from space.


The Landsat satellite record stretches from 1972 to the present. This gallery includes all Landsat images published on the Earth Observatory, Visible Earth, and Landsat Science web sites from all seven Landsat satellites (Landsats 1-8, Landsat 6 failed to achieve orbit). All of the images are in the public domain and may be used with attribution. The correct attribution for imagery obtained from this site is:


“Landsat imagery courtesy of NASA Goddard Space Flight Center and U.S. Geological Survey” or “USGS/NASA Landsat”





More History

 












Learn about the Landsat Legacy project        Landsat Science



Curiosity Mars Rover moves On - Alexander Hills

Within Rover's Reach at Mars Target Area 'Alexander Hills'





This view from the Mast Camera (Mastcam) on NASA's Curiosity Mars rover shows a swath of bedrock called "Alexander Hills," which the rover approached for close-up inspection of selected targets.

The mosaic of six Mastcam frames covers an area about 6 feet (2 meters) across. It shows details within the workspace accessible using the rover's robotic arm from the rover's location when the view was acquired. The component exposures were taken on Nov. 23, 2014, during the 817th Martian day, or sol, of Curiosity's work on Mars. The color has been approximately white-balanced to resemble how the scene would appear under daytime lighting conditions on Earth.

Figure A is an annotated version showing the location of three targets selected for study -- "Aztec," "Agate Hill" and "Cajon" -- and a 50-centimeter (20-inch) scale bar.

The location of Alexander Hills within the "Pahrump Hills" outcrop at the base of Mount Sharp is indicated on an earlier Mastcam view at http://photojournal.jpl.nasa.gov/catalog/PIA19039. NASA's Jet Propulsion Laboratory, a division of the California Institute of Technology, Pasadena, manages the Mars Science Laboratory Project for NASA's Science Mission Directorate, Washington. JPL designed and built the project's Curiosity rover. Malin Space Science Systems, San Diego, built and operates the rover's Mastcam.

Image Credit: NASA/JPL-Caltech/MSSS

Erosion Resistance at 'Pink Cliffs' at Base of Martian Mount Sharp
Erosion Resistance at 'Pink Cliffs' at Base of Martian Mount Sharp
Full Resolution


Ripples Beside 'Pahrump Hills' Outcrop at Base of Mount Sharp
Ripples Beside 'Pahrump Hills' Outcrop at Base of Mount Sharp
Full Resolution


Erosion Resistance at 'Pink Cliffs' at Base of Martian Mount Sharp
Erosion Resistance at 'Pink Cliffs' at Base of Martian Mount Sharp (Labeled)
Full Resolution


Fine-Grained Rock at Base of Martian Mount Sharp
Fine-Grained, Finely Layered Rock at Base of Martian Mount Sharp
Full Resolution


Fine-Grained Rock at Base of Martian Mount Sharp
Fine-Grained, Finely Layered Rock at Base of Martian Mount Sharp (Labeled)
Full Resolution

<< RETURN TO IMAGES




NASA - MARS




The Florida Peninsula at Night from Space

                         
                           
Astronauts aboard the International Space Station took this photograph of Florida in October 2014. The peninsula is highly recognizable even at night, especially when looking roughly north, as our map-trained brains expect.



Astronaut photograph ISS041-E-74232 was acquired on October 13, 2014, with a Nikon D3S digital camera using a 24 millimeter lens, and is provided by the ISS Crew Earth Observations Facility and the Earth Science and Remote Sensing Unit, Johnson Space Center. The image was taken by the Expedition 41 crew. It has been cropped and enhanced to improve contrast, and lens artifacts have been removed. The International Space Station Program supports the laboratory as part of the ISS National Lab to help astronauts take pictures of Earth that will be of the greatest value to scientists and the public, and to make those images freely available on the Internet. Additional images taken by astronauts and cosmonauts can be viewed at the NASA/JSC Gateway to Astronaut Photography of Earth. Caption by M. Justin Wilkinson, Jacobs at NASA-JSC.



Florida at Night


acquired October 13, 2014 download large image (2 MB, JPEG, 2128x1416)



Illuminated areas give a strong sense of the size of cities. The brightest continuous patch of lights is the Miami-Fort Lauderdale metropolitan area, the largest urban area in the southeastern U.S. and home to 5.6 million people. The next largest area is the Tampa Bay region (2.8 million people) on the Gulf Coast of the peninsula. Orlando, located in the middle, has a somewhat smaller footprint (2.3 million). A nearly straight line of cities runs nearly 560 kilometers (350 miles) along the Atlantic coast from Jacksonville, Florida, to Wilmington, North Carolina.

South of Orlando, the center and southern portions of the peninsula are as dark as the Atlantic Ocean, vividly illustrating the almost population-free Everglades wetland. The lights of Cocoa Beach trace the curved lines of Cape Canaveral and the Kennedy Space Center, an area well known to astronauts. Dim lights of the Florida Keys extend the arc of the Atlantic coast to the corner of the image. The small cluster of lights far offshore is Freeport on Grand Bahama Island (image right). The faint blue areas throughout the image are clouds lit by moonlight.
Instrument(s): 
ISS - Digital Camera
NASA Earth Observatory

Digital Town Planning by Night




“Here!” exclaimed Jebediah as he nosed his schooner onto a fan of fertile loam. Come sundown, a makeshift corral encircled his livestock, and by Sabbath eve, the crown of a crude barn rose above the neighboring hummock.


Next spring, a steady procession of ships yielded a healthy crop of farmhouses. Wagon wheels burned a double track to the river landing, where itinerant capitalists soon repurposed a cluster of spartan shacks:


Dispell ill humours at Rodger’s Saloon!

 Satisfy your homestead needs with Trusty Mercantile!

 Every fifth horseshoe free at The Irony!


Forthwith straightened and graded, Main Street ran east to west, land astride platted into tidy rectangles. Soon, Washington and Jefferson joined in parallel, crossed at even intervals by perpendicular First, Second, and Third Streets.


A crystal in saturated solution, this grid grew: shooting southeast into open country along Telegraph Road, doglegging left around Miller’s Swamp, and crossing the river at Monroe Street Bridge, which lensed the opposite shore into a different orientation…


And so on, until some time ’round the Depression, when town planners discovered:
Oh my golly, curves! By George, a city block doesn’t necessarily need to be a rectangle, right? And, three way intersections, yeah, they’re pretty darn tootin’ okay…


Thereafter, new streets came, but in more pear-shaped and less grid-like arrangements than before.
Now, to Yours Truly, nirvana is a sunny day, strolling well-worn sidewalks past the wide-windowed storefronts of an old downtown. Some people might call me a Main Streetaholic – I’ve been known to scour maps for quaintness, and on a road trip, I’ll happily choose the Byzantine route just to experience the charms of a bygone Broadway.

And I thought I knew about every one between Ukiah and Scotts Valley.


Until, out of the blue, a friend informed me: “I’m moving to Graton!
Graton…? California? Uh… Why? Up came the Street View, and there, west of Santa Rosa, it was: a pocket-sized downtown decorated by a handful of adorable “Old West”-style buildings. OMFG.


What other treasures had I missed?!


I made these maps to help me find out.


Above is San Francisco, and below, New York, Washington DC, Los Angeles, Tokyo, and five other interesting metros:


Tokyo
Tokyo
New York
New York
Paris
Paris
Los Angeles
Los Angeles
Washington DC
Washington DC
Chicago
Chicago
Berlin
Berlin
Boston
Boston
London
London
That’s every public street, colored by the predominant orientation of itself and its neighbors, thickened where the layout is most “grid-like” – to use an old-school woodworking metaphor, it’s as if we brushed some digital lacquer over the raw geographic transportation network data to make the grain pop.


For the detail-oriented, these are 100%-algorithmic images generated from MapZen’s Migurski-inspired October 2014 OpenStreetMap Metro Extracts as follows. First, we assign each linear street segment a compass-heading-based tone from a modified sinebow, where a 90 degree directional difference corresponds to a full color revolution, so that roads at right angles to each other have the same hue. Then, to render each point on the map, we use Proximatic, my custom high-performance k-NN engine, to calculate the length-weighted average of the colors assigned to the nearest 500 meters of street, keying render weight to the local degree of parallelism/orthogonality (derived in a similar mod-90° vector space), with rolloffs for outlying roads and territory.
Pan and zoom via Vladimir Agafonkin’s excellent Leaflet viewer, and click the “Acme” button for a more conventional map of the current view, kudos to Poskanzer.


Lots of stories in there: of cities waxed, towns waned, territory absorbed, and terrain negotiated (or, ala San Francisco, ignored completely).


Enjoy, and I’ll see you in the grids!       Data Pointed