![]() LRO imagery has even been used to re-examine previous data about the Moon, including data from the Apollo missions.Īstrobiologists supported by the Astrobiology Program have used data from LRO to better understand the history and formation of the Earth-Moon system. This data is relevant to understanding other similarly-sized worlds in the Solar System and beyond, such as the moons of other planets like Jupiter and Saturn. LRO data has informed scientific investigations that have expanded astrobiologists’ knowledge of the formation and evolution of small, rocky bodies. ![]() LRO observations have enabled numerous groundbreaking discoveries, creating a new picture of the Moon as a dynamic and complex body. After a year of exploration, the mission was extended with a unique set of science objectives.Īs our nearest neighbor, the Moon is a natural laboratory for investigating fundamental questions about the origin and evolution of the Earth and the Solar System. Today the full res frame will go up on the NLSI web server and we will provide the link to the 691 megabyte image.The Lunar Reconnaissance Orbiter ( LRO) is a robotic mission that set out to map the Moon’s surface in high resolution. The updates provide improved ease and accuracy when searching and. This is making me revise my estimation of the value of many of the LO images because it is extremely difficult for the LROC camera, if not impossible, to get images like this. LROC is thrilled to announce the Lunar QuickMap spring 2020 update release The update, which was officially released earlier today, includes many exciting new layers and features, as well as enhancements to previously released layers and tools that you may be familiar with. You can actually see how high a mountain is that just looks like a bump when looking down on it from a vertical perspective. One thing that is just so fascinating to me is how much more I get out of the oblique images when trying to get a sense of an area. The second image is from the Arizona State Quickmap looking straight down into the same area. The first image here is a zoom into the upper right quadrant of that image. It seriously looks like you are on a spacecraft about 50 km above the surface looking down. I loaded it on my computer this morning and was just simply blown away by it when zooming in. Last night Austin ran the framelets through our assembly and image processing program and left me the frame. We just had to get that image and so we found that we were missing a few framelets due to a tape change and thus we got the rest off of a Goldstone tape (G5-145). I started looking at the framelets and found the super cool oblique shots interesting when looking at them on the 30″ Apple high res monitor. I happened upon image LOV-041M from tapes W5-154, 155. Just by chance yesterday I was looking through some processed framelets because I had a discrepancy between what I was recording in my log book of the Lunar Orbiter sequence numbers and the framelets on the tapes as recorded by NASA. It is one of my little joys in doing the LOIRP project that I get to look at amazing images of the Moon that we get that look so incredible. ![]() Click on images to enlargeĭennis Wingo: I love looking at the Moon. Specifically frame 5151_H1.įYI at the native resolution of this restored image and the resolution of the individual monitors used in this hyper wall, we’d need 50 – yes fifty – hyperwall 2 set ups to show this LOIRP image at its full resolution. The image that was presented was a portion of the floor of crater Copernicus taken by Lunar Orbiter 5 on 11 August 1967. The hyperwall-2 helps researchers display, analyze, and study high-dimensional datasets in meaningful ways, allowing the use of different tools, viewpoints, and parameters to display the same data or datasets.” On Thursday one of the images retrieved by the Lunar Orbiter Image Recovery Project (LOIRP) was presented on the NASA Ames Hyperwall visualization system.Īccording to NASA Ames “Our in-house developed hyperwall-2 visualization system–one of the largest and most powerful in the world–provides a supercomputer-scale environment to visualize and explore the very large, high-dimensional datasets produced by NASA supercomputers and instruments.
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