Leaders in Lidar

This is a closeup view of the GEDI forest height data collected over Senegal. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This version has no on screen color bar. The Global Ecosystem Dynamics Investigation (GEDI) produces high resolution laser ranging observations of the 3D structure of the Earth. GEDI’s precise measurements of forest canopy height, canopy vertical structure, and surface elevation greatly advance our ability to characterize important carbon and water cycling processes, biodiversity, and habitat. GEDI’s data on surface structure are also of immense value for weather forecasting, forest management, glacier and snowpack monitoring, and the generation of more accurate digital elevation models. GEDI provides the missing piece – 3D structure – in NASA’s observational assets which enables us to better understand how the Earth behaves as a system, and guides the actions we can take to sustain critical resources. The GEDI instrument is a geodetic-class, light detection and ranging (lidar) laser system comprised of 3 lasers that produce 8 parallel tracks of observations. Each laser fires 242 times per second and illuminates a 25 m spot (a footprint) on the surface over which 3D structure is measured. Each footprint is separated by 60 m along track, with an across-track distance of about 600 m between each of the 8 tracks. GEDI expected to produce about 10 billion cloud-free observations during its nominal 24-month mission length.To learn more, visit the GEDI webpage Forest height color bar spanning 0m to 40m This is a closeup view of the GEDI forest height data collected over Senegal. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This is a closeup view of the GEDI forest height data collected over the Goddard Space Flight Center in Maryland. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This is a closeup view of the GEDI forest height data collected over the Laurentides region around Quebec Canada. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This version has no on screen color bar. This is a closeup view of the GEDI forest height data collected over the Laurentides region around Quebec Canada. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This is a closeup view of the GEDI forest height data collected over Florida. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This is a closeup view of the GEDI forest height data collected over Florida. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This version has no on screen color bar. This is a closeup view of the GEDI forest height data collected over the Goddard Space Flight Center in Maryland. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This version has no on screen color bar. Still image depicting GEDI forest height data being collected over time. Camera is zoomed in on the west coast of the United States. Still image depicting GEDI forest height data being collected over time. Camera is zoomed in on the west coast of the United States. Still image depicting a global view of GEDI forest height data. Still image depicting a global view of GEDI forest height data. Still image depicting a global view of GEDI forest height data. Still image depicting GEDI forest height data being collected over time. Camera is zoomed in on the west coast of the United States. Still image depicting GEDI forest height data being collected over time. Camera is zoomed in on the west coast of the United States. Forest height color bar spanning 0m to 75m This visualization depicts a global view of forest height data collected by the GEDI instrument aboard the International Space Station. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale.Coming soon to our YouTube channel. Still image depicting a global view of GEDI forest height data. This is a closeup view of the GEDI forest height data collected for the west coast of the United States. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale.Coming soon to our YouTube channel. This visualization depicts a global view of forest height data collected by the GEDI instrument aboard the International Space Station. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This version has no on screen color bar. This is a closeup view of the GEDI forest height data collected for the west coast of the United States. Data is drawn on the globe over time, depicting how data coverage increases with each satellite pass. Brown and dark green represent shorter vegetation. Bright green and white represent taller vegetation. This visualization uses data collected between April 2018 and April 2019. Height is exaggerated to depict variation at this scale. This version has no on screen color bar. Forest height color bar spanning 0m to 50m

This visualization depicts changes in Antarctic land ice thickness as measured by the ICESat (2003-2009) and ICESat-2 (2018-) satellites. The camera zooms into a region near the Kamb ice stream to compare ICESat and ICESat-2 beam tracks. The beam intersections are highlighted to explain how the data at these points are used to measure how land ice has changed over time. After exploring a few regions in detail, the camera moves out to a global view and an ocean temperature dataset is revealed. The future response of the Antarctic Ice Sheet to changes in climate is the single largest source of uncertainty in projections of sea level rise. If the ice sheet melted completely it would raise sea levels by 57 meters, a process that would unfold over millennia. One key to understanding how the ice sheet will respond in the future is to observe and analyze how the ice sheet has reacted to changes in climate over the past decades, where satellites observations are available. One key to understanding ice sheet change is to examine records of elevation change that show where the ice sheet is thinning and thickening due to changing environment. Recent analysis of incredibly precise surface elevations collected by NASA’s ICESat and ICESat-2 satellite laser altimeters reveals complex patters of ice sheet and ice shelf (floating extensions of the ice sheets) change that are the combined consequence of changes in melting by the ocean, changes in precipitation and, changes at the bed of the glacier where the ice sheet slides across the underlying bedrock. The researchers do this my finding locations where tracks of measured elevation intersect, measuring the change in elevation and correct for changes in the average density of the surface using models. Coherent regional patters of elevation change reveal the underlying mechanism responsible causing ice sheet change. One of the most striking features in the data is the Kamb Ice Stream that once flowed rapidly into the Ross Ice Shelf but that stopped flowing due to an increase friction (resistance to flow) likely caused by changes in the availability of liquid water at its base. Strong patters of thinning are visible all along the Amundsen Cost where ice shelves are rapidly thinning in response to increased melting by warm ocean waters. Melting of ice shelves do not directly contribute to changes in sea level, since they are already floating, but they do indirectly impact how fast the grounded ice is able to flow into the ocean. Ice shelves are located at the fronts of the glaciers and help to regulate how fast the ice flows into the ocean. As the ice shelves thin they become less able to hold back the inland ice, causing the grounded glaciers to accelerate and thin. In the East, broad patters of thickening reveal that the East Antarctic Ice Sheet is growing most likely in response to increases in precipitation relative to some unknown time in the past. The thickening is strongest along the coast of Dronning Maud Land where enhanced moisture transport has resulted in increased snowfall. Despite the diversity of gains and losses, losses in the West (208 cubic kilometers of water per year or Gt) greatly outpace Gains (90 Gt per year) in the east resulting in a total Antarctic mass change loss of 118 Gt per year. This visualization depicts changes in Greenland land ice thickness as measured by the ICESat (2003-2009) and ICESat-2 (2018-) satellites. The camera zooms into a region near the Zachariae Isstrom glacier to compare ICESat and ICESat-2 beam tracks. The beam intersections are highlighted to explain how the data at these points are used to measure how land ice has changed over time. As the Greenland Ice Sheet responds to warming oceans and atmosphere it has become one of the largest contributors to sea level rise and will continue to be for the foreseeable future. Scientists are working to determine more precisely how much more ice will be lost and when that loss will occur. One key approach to doing this is to analyze changes in the ice sheets elevation over the past decades where satellite observations are available. By finding the intersection of elevation track measurements collected by NASA’s ICESat (2003-2009) and ICESat-2 (2018-) satellite laser altimeters, researchers are able to make very precise measurements of elevation change that can be converted to estimates of mass change after correcting for changes snow density using models. The combination of long time-span between measurements and the high accuracy of NASA’s satellite laser altimeters allows the researchers to make highly detailed maps of mass change that provide insights into the mechanism behind the ice sheets rapid rate of loss. Thinning can be seen around the periphery of the ice sheet where elevations are closest to sea level and rates of surface melting are highest. This pattern is punctuated by localized areas of extreme thinning where large glaciers come into contact with warm ocean waters. Unlike the uniform pattern of low-elevation thinning that is being driven by increased melting due to warmer summer air temperatures, these concentrated areas of thinning occur where outlet glacier have sped up. These glaciers have sped up in response to some combination of retreating ice front position, changes in the slipperiness at the bed of the glacier due to changes in liquid water at the ice-rock interface and due to change in the rate frontal melting due to an increase in the heat content of the ocean waters that come into contact with the glacier front. Juxtaposed on the pattern of rapid thinning along the periphery of the ice sheet is a broad pattern of thickening in the high-elevation interior of the ice sheet. This pattern of thickening suggests that increases in snowfall, relative to sometime in the past, are partly compensating for increased losses due to enhanced melt and accelerated glacier flow. Overall low-elevation losses greatly outpace high-elevation gains resulting in 3200 cubic kilometers of water (Gt) being lost from the ice sheets and entering the oceans, raising global mean sea level by 8.9 mm. This high resolution still image depicts changes in Antarctic land ice thickness as measured by the ICESat (2003-2009) and ICESat-2 (2018-) satellites. This high resolution still image depicts changes in Greenland land ice thickness as measured by the ICESat (2003-2009) and ICESat-2 (2018-) satellites.

ICESat-2 tracks over the Arctic Ocean spanning from November 2018 to March 2019. One of the big challenges in polar science is measuring the thickness of the floating sea ice that blankets the Arctic and Southern Oceans. Newly formed sea ice might be only a few inches thick, whereas sea ice that survives several winter seasons can grow to several feet in thickness (over ten feet in some places). Sea ice thickness is typically estimated by first measuring sea ice freeboard - how much of the floating ice can be observed above sea level. Sea ice floats slightly above sea level because it is less dense than water. NASA’s ICESat-2 satellite measures the Earth’s surface height by firing green laser pulses towards Earth and timing how long it takes for those laser pulses to reflect back to the satellite. Ice freeboard is calculated by differencing the heights of the ice surface and areas of open water next to the ice. Additional information including the depth and density of the snow layer on top of the ice is needed to convert this freeboard measurement to sea ice thickness. New state-of-the-art snow accumulation models have been developed to provide this extra data in preparation for the launch of ICESat-2. The very high precision of the ICESat-2 laser has enabled us for to measure the thickness of very thin sea ice for the first time. As the Arctic warms rapidly it is becoming increasingly dominated by a younger and thinner ice cover, making these new measurements extremely invaluable for understanding our changing polar regions. A view of the Arctic Ocean with monthly average sea ice thickness spanning November 2018 to March 2019. Low values are depicted in light blue, and higher values (5 meters) are depicted in magenta. Close up view of a single ICESat-2 track. The light grey section of the track represented ice freeboard (height above sea level) and the darker grey represents sea ice below the ocean surface. A 10m orange line is shown for scale. This visualization depicts sea ice thickness in the Arctic Ocean as measured by ICESat-2 over the course of several months. The visualization begins with a global view of the north pole as individual tracks are drawn over time representing each time the satellite passes overhead and collects sea ice data. A closeup view of one track is revealed, showing how the ICESat-2 laser can measure ice freeboard (height above sea level), which can be used to calculate total ice thickness. The visualization concludes by showing monthly average of sea ice thickness from November 2018 to March 2019.

The Global Ecosystem Dynamics Investigation (GEDI) uses laser pulses to give a view of the 3D structure of the Earth. GEDI’s precise measurements of the height and vertical structure of forest canopy, along with the surface elevation, will greatly advance our ability to characterize important carbon and water cycling processes, biodiversity, and habitat. The mission is led by the University of Maryland, College Park, and the instrument was built and tested at NASA four power and four cover tracks. Footprints are separated by 60 m along-track and 600 m across track.

Animation showing how ICESat-2 will measure the height of sea ice freeboard (hf) – the portion of sea ice floating above the water – to estimate sea ice thickness (hi). ICESat-2 will measure heights or elevations. In order to derive sea ice thickness from those measurements, it will compare the height of the ice with the height of the adjacent open water. The difference is height is the portion of the ice that is above the sea level, called freeboard. Because roughly 1/10 of the ice floe is above water we can calculate its thickness. Very often the only open water nearby is from cracks in the ice (leads) that open and close quickly as the ice drifts about in the polar oceans pushed by ocean currents and winds.

ICESat-2 orbit with ground track (short version) ICESat-2 is a spacecraft designed to accurately measure land and ice elevations on Earth. By comparing observations from different times, scientists will be able to study changes in elevations. ICESat-2 will be in a polar orbit which will provide high coverage near the poles where ice elevations are changing relatively quickly. This visualization shows ICESat-2 s global coverage which repeats about once every 90 days.The ATLAS lidar on ICESat-2 uses 3 pairs of laser beams to measure the earth’s elevation and elevation change. As a global mission, ICESat-2 will collect data over the entire globe, however the ATLAS instrument is optimized to measure land ice and sea ice elevation in the polar regions.For more information on ICESat-2 click here. ICESat-2 orbiting Earth: starting with global view building up ground track, then riding the satellite view, then back to a global view with full ground track

ICESat-2 has 3 pairs of lasers that will measure the heights of ice and snow at very high resolution The ATLAS lidar on ICESat-2 uses 6 laser beams to measure the earth’s elevation and elevation change. As a global mission, ICESat-2 will collect data over the entire globe, however the ATLAS instrument is optimized to measure land ice and sea ice elevation in the polar regions. ICESat-2 reports elevations with respect to a reference surface, called an ellipsoid. In this measurement system, shared by GPS devices, an elevation of zero meters indicates the notional sea level, although tides, wind, and waves can make the actual sea level either greater than or less than zero. The Antarctic ice sheet, shown here, ranges up to 4000m above sea level. Over the course of 91 days, ATLAS will generate 1387 ground tracks across Antarctica for each of it’s 6 beams.

Mercury is colored in the image on the right to show the diverse array of minerals on its surface. The colors in this image represent different types of geologic material seen in one of Mercury s surface is heavily cratered like our moon. This elevation map shows high terrain in white, and low-lying areas in purple. After four years of exploring Mercury from orbit, NASA’s MESSENGER mission comes to an end.

A redux of entry #2455 using MGS/MOLA data for the Martian topography and MGS/MOC for the Martian surface color. The animation rolls Mars to show major features of the Martian topography. Major features depicted include: Olympus Mons, Valles Marineris, Hellas Basin, and the Martian North and South Poles. Print resolution nadir view of the Martian South Pole. Print resolution image of Mars. Hellas Basin can be seen in the lower right portion of the image. Print resolution nadir view of the Martian North Pole. Print resolution image of Mars showing a partly shadowed Olympus Mons toward the upper left of the image. The row of 3 volcanoes that form the base of a triangle in relationship to Olympus Mons are (from top to bottom): Ascraeus Mons, Pavonis Mons, and Arsia Mons. Valles Marineris can also be seen. It s the giant valley that slashes equatorially across the Martian landscape to the right of the volcanoes. Print resolution image of Mars slightly tilted to show the Martian North Pole. Animation that rolls Mars around to show all the major features of the Martian topography. This animation begins with a hemispherical view of Olympus Mons and Valles Marineris and then rolls around to reveal the Martian South Pole. While traversing Northward, we pass Hellas Basin and end up looking down up the Martian North Pole.

This animation flys around the moon s South Pole in 3D via LRO/LOLA First Light Data (#3633). Sample animation using the match-frame rendered crater annotations from animation #3633 as an overlay to annotate the craters in this flyover. Print resolution still of the moon. Print resolution still of our simulated approach to the lunar surface. Print resolution still over the lunar south pole. Craters depicted in this image are Laveran, Wiechert, Amundsen, Faustini, Shackleton, Shoemaker, Scott, and Haworth. Print resolution still of the lunar south pole. Top down view of the south pole region.

This animation shows some of the first results of the LRO/LOLA instrument with labels over several craters. As the virtual camera flies around the lunar south pole we not only get an indication of the moon s distance to the surface. This is why there is virtually no data of the lunar north pole, and much better coverage of the south pole. The topographic data shown here is currently processed to show at approximately 30 meters per pixel.The colors in this animation depict the relative heights of the lunar surface with respect to the surface mean. Warm colors (brown, red, magenta, and tan) indicate areas above the mean. Cooler colors (green, cyan, blue, and violet) are areas below the mean. This animation shows some of the first results of the LRO/LOLA instrument without any labels. Colorbar for lunar elevations. Print resolution still of the moon with some early swaths of LOLA data. Print resolution still of the LRO/LOLA data swaths as they are laid out on the lunar surface. Please note that for aesthetic purposes the swath widths are shown wider than actual. The actual width of a swath is approximately 65 meters across. Print resolution still over the lunar south pole. Craters depicted in this image are Scott, Amundsen, Faustini, Shoemaker, Haworth, Malapert, Shackleton, and Wiechert. Print resolution still of the lunar south pole. Top down view of the south pole region.

A view of Antarctica showing ice sheet elevation and cloud data from ICESat This still image was generated to be printed as a lithograph for public distribution. [from the litho:] This image illustrates ice sheet elevation and cloud data from ICESat s standard ellipsoid with 50x vertical exaggeration. Data collected across floating sea ice and open water of the adjacent Southern Ocean cannot be shown at this scale. Clouds of various thicknesses are indicated by colors changing progressively from light blue (thin clouds) to white (opaque layers). Note that the laser cannot penetrate the thickest clouds causing gaps in the elevation profile below. The RADARSAT (Canadian Space Agency) mosaic is used to illustrate the Antarctic continent.

This is the standard definition version MPEG of the ICESat Data Accumulation Animation. Accumulating Data: Glas Builds Its Facts One Point at a Time - The technology behind GLAS is called lidar. Lidar is a distance measuring system similar to radar, except that instead of radio waves it uses pulses of laser light for range finding. The name is a contraction based on the words light and radar: Light Detection And Ranging. A lidar system determines precise distances by measuring the amount of time necessary for a pulse of light to leave an emitter, hit a target, and return. In this case, distance measurements helped researchers determine changes in ice thickness, vegetation, cloud thickness, and much more.

Animation showing ICESat collecting elevation data In this visualization we ride along with the ICESat spacecraft as its laser measures detailed changes in surface topography. This was produced in support of the ICESat first light release. ICESat collecting elevation data Video slate image reads .

A rotating view of the Martian south pole using MOLA topography data This is one of a series of visualizations showing false-colored renderings of the Martian topography measured by MOLA in the vicinity of the Mars Polar Lander landing site. Blue tones represent elevations of less than 2 kilometers, while reddish tones are greater than about 2.8 kilometers, relative to the mean equatorial height of Mars. The elevation of the landing site is about 2.4 km, midway into the polar layered terrain. The 400 meters (1/4 mile) resolution of the MOLA data gives a smoothed but vertically exaggerated view of the topography. At this scale it is impossible to ascertain the actual roughness at the lander s destination, forcing project directors to make their best guesses based on available data. The visible Martian south polar cap appears outlined in black, but the accompanying false color data shows the topographically inferred extent of the polar layered terrain. False color image of Mars from MOLA data. Here the color scale shows the darkest blues as roughly 8 km below the mean equatorial height, while reds indicate elevations up to 5 km above the mean equatorial height. MOLA data of Martian topography highlighting the differences in elevation between the Hellas Impact Basin and surrounding terrain. The deepest point in Hellas is roughly 8200 meters below the equatorial mean.

How the spacecraft made the gravity map. Animation by Studio 13. Evidence of global magnetic field on Mars collected by Mars Global Surveyor (MGS). Animation by Studio 13. Dramatic asymmetry in structure between north and south. North took longer to cool suggests that there may have once been a northernmartian ocean. Animation by Studio 13. How MGS made the gravity map. Animation by Studio 13. Animation of how MOLA takes elevation readings. Animation by Studio 13. How the spacecraft made the gravity map. Animation by Studio 13. Evidence of global magnetic field on Mars collected by Mars Global Surveyor (MGS). Animation by Studio 13. Dramatic asymmetry in structure between north and south. North took longer to cool suggests that there may have once been a northern martian ocean. Animation by Studio 13. How MGS made the gravity map. Animation by Studio 13. How Mars Orbiter uses its laser altimeter to collect elevation data. Animation by Studio 13.