Moon Zoo is a new addition to the Zoo-universe, a collection of citizen science project that started a few years ago with the highly successful Galaxy Zoo. The project invites everyone to explore the lunar surface in unprecedented detail, with the resolution of up to 0.5m., courtesy of NASA’s Lunar Reconnaissance Orbiter (LRO) and its two Narrow Angle Cameras.

Moon Zoo asks the participants to classify and measure the shape of features on lunar surface with the main focus on:

• counting the number of and measuring the size of impact craters
• categorizing locations of interest such as lava channels, crater chains, lava flooded impact craters,  volcanic eruptive centers, etc.
• assessing the degree of boulder hazard by comparing boulder density on two images
• identifying recent changes on lunar surface by comparing LRO and Apollo photographs
• determining the location of space mission hardware on the Moon (Apollo landers, Luna rovers, European and Chinese probes)

Besides delivering high quality data which will address many questions of lunar science, Moon Zoo is also an excellent tool to promote lunar and space exploration and engage the public in learning about processes involved in scientific discoveries.

Although the plugin is now available for download, the process to request the API key is not yet in place (so the plugin will not yet display any data for you). If you wish to participate in the beta testing, just sign up for Galaxy Zoo (and Galaxy Zoo Forums) and wait for an announcement (which should be coming in not distant future).

The Galaxy Zoo WordPress Plugin widgets sample preview

This plugin offers two WordPress widgets through which users can display data from their accounts on Galaxy Zoo.

The first widget, ‘Galaxy Zoo’, display general stats such as the username, the date the user joined Galaxy Zoo, the number of galaxy classifications  and the latest classified galaxy.

The Galaxy Zoo WordPress Plugin widgets sample preview (closeup)

The second widget, ‘Galaxy Zoo Favorites’, displays thumbnail images of galaxies the user selected as his/er favorites (using the Galaxy Zoo’s My Galaxies page)

Both widget are completely customizable via the widget’s control panel and style-able via a separate css file(s).

The Galaxy Zoo WordPress Plugin Admin Panel

Galaxy Zoo is an online astronomy project which invites members of the public to assist in classifying over a million galaxies. It is an example of Citizen science as it enlists the help of members of the public to help in scientific research.

The Galaxy Zoo files contain almost a quarter of a million galaxies which have been imaged with a camera attached to a robotic telescope the Sloan Digital Sky Survey.

It is not uncommon in science to make accidental discoveries. Alexander Fleming certainly did not intend to contaminate one of his research cultures with a Penicillium genus. Arno Penzias and Robert Woodrow Wilson discovered the cosmic microwave background radiation because of their “inability” to account for the 3.5 K excess temperature of their radiometer. Thomas Bopp (co)discovered the most observed comets of the 20th century when looking at the globular cluster M70 (and actually did not even own a telescope at the time).

Other times, data from a research project with a specific goal can be used to make discoveries never anticipated by the project team. Several Galaxy Zoo participants noticed interesting artifacts present in images of galaxies from the SDSS. The rainbow-like artifact in the image below is actually an asteroid.

Galaxy designated as SDSS J130941.81+063637.8 with an asteroid trail - Image Source: SDSS

The SDSS instruments use couple-charged device (CCD) cameras to collect light. A CCD chip can be thought of as a 2 dimensional array of light collectors that accumulate electric charge proportional to the intensity of incident light. The electric charge is then converted to voltage in a charge amplifier and digitized by a computer to create an image. CCD data in astronomy is used to create (only) gray-scale images. To make a color image, the camera takes exposures with different filters. The individual filter images can be later combined into a single color image (similar to combining the  R, G and B channels of a color picture).

The SDSS camera uses five different filters: u (ultraviolet), g (green), r (red), i and z (both infrared). Thus, five exposures are required to produce an image of any single region of the sky. The actual order in which the filters are used is r, i, u, z and g. Although SDSS takes images through five filters, only three are combined to produce colored pictures. The i filter makes the red picture, r filter makes the green picture, and the g filters makes the blue picture.

Because of the technique called “drift-scanning” employed by the SDSS, exposure through a single filter takes roughly 54 seconds. Since asteroids are relatively close to us, they move rather quickly across the sky. This motion is easily noticeable at the resolution of 0.396 arc second per pixel achieved by SDSS. Furthermore, because of the order in which different filters are used, the red and green streaks are closer together and for slower moving objects may even be combined into single yellow/orange/brown streak. The dark blue/violet streak, however, is always easily recognizable at a sufficient distance from the other two (because the g filter is used last) .

Galaxy designated as SDSS J105646.89+050055.3 with an asteroid trail beneath it - Image Source: SDSS

The animation below shows what happens when the SDSS’s filters scan a part of sky with a slow-moving asteroid. The asteroid is the brown dot moving across the animation. The animation shows the camera’s r, i, and g filters sweeping across the sky. (In reality, it works the opposite – the cameras stay still and the sky moves during the night.) The camera takes a picture of the asteroid through the r and i filters (which are next to one another), leaving a yellow dot (or red and green dots). When the g filter scans the asteroid, the asteroid has moved; it shows up as a blue dot in its new place. In the last frame of the animation, the asteroid is removed, leaving only the image that would be seen by the SDSS.

Although SDSS is focused on looking for distant galaxies and quasars, it also sees objects in our cosmic neighborhood. The first data release (SDSS DR1) alone contains more than 100,000 asteroids. Occasionally, it manages to photograph a wobbling satellite in low-earth orbit (below) and even a bright meteor (below).

A satellite in Low Earth Orbit captured by SDSS camera using the r filter. The discontinuity in the satellite's path is a result of the data for that particular area being taken at different time - Image Source: SDSS

Bright meteor captured in the act of burning up in the earth's atmosphere. The trail is colored green because the image of the meteor was captured in only one of the 5 SDSS filters - Image Source: SDSS

Moon Zoo will be another citizen science project, the latest incarnation of the highly successful Galaxy Zoo. The project will use high resolution images from the Lunar Reconnaissance Orbiter Camera (LROC) on NASA’s LRO spacecraft. Moon Zoo will ask the participants to classify and measure the shape of features on lunar surface with the main focus on:

• counting the number of and measuring the size of impact craters
• categorizing locations of interest such as lava channels, crater chains, lava flooded impact craters,  volcanic eruptive centers, etc.
• assessing the degree of boulder hazard by comparing boulder density on two images
• identifying recent changes on lunar surface by comparing LRO and Apollo photographs
• determining the location of space mission hardware on the Moon (Apollo landers, Luna rovers, European and Chinese probes)

Besides delivering high quality data which will (hopefully) address many questions of lunar science, Moon Zoo will also be an excellent tool to promote lunar and space exploration and engage the public in learning about processes involved in scientific discoveries. Moon Zoo is expected to be even more popular than Galaxy Zoo, exploiting the media exposure of the 40th anniversary of Apollo 11 and the recent NASA’s LRO/LCROSS mission.

Full resolution detail from one of the first LROC NAC images. At this scale and lighting, impact craters dominate the landscape. Two general types of impact craters are readily identifiable. Solitary craters which most likely represent a single impact event, and clusters or chains of small, fresh craters produced by the impact of lunar material excavated by a larger impact. Image width is 1400 meters, north is down - Photo Source: NASA/GSFC/Arizona State University

When the original Galaxy Zoo was launched in summer of 2007, hardly anyone could anticipate the enormous participation and the enthusiasm with which thousands of users meticulously classified millions of galaxies. Because of the immense success of the original project, Galaxy Zoo 2 was created to focus on a detailed classification of 245,609 galaxies selected from millions of classifications available. Galaxy Zoo 2 participants answer the kind of questions the creators of the original Galaxy Zoo project would have asked had they known how large the users base was going to be.

Earlier this month the Zoo project family was extended by Galaxy Zoo Supernovae (currently in a planned off-time to analyze preliminary data). The Supernovae project uses images from the Palomar Transient Factory (PTF) taken only hours earlier. The PTF data is fed through an automated pipeline which finds suitable candidates to display to users. Because time (the age of a supernova) is of the essence for this type of research, unlike in Galaxy Zoo 1 and 2, GalaxyZoo Supernovae implemented a priority queue to always display the most recent candidates before showing older data. This system presents a unique opportunity for anyone to discover a never-before-seen supernova.

A supernova found in on of the Galaxy Zoo Supernovae candidate assets - Photo Source: GalaxyZoo.org

Galaxy Zoo project was the first of its kind to use the exceptional power of human brain to recognize patterns and shapes (something that computers “learn” with great difficulties). More importantly, Galaxy Zoo proved that worldwide citizen science projects can provide data analysis comparable in quality to professional astronomers. The large number of independent results by amateurs or enthusiasts has an advantage over a significantly smaller number of results by experts because it allows to quantify uncertainties with ease.

1,000,000 classifications reached well ahead of time

The GalaxyZoo project is a bit similar to the world-known SETI@Home which opened to public almost 10 years ago (May 17, 1999). Since then millions of internet users joined the effort and donated their computer idle time to a variety of scientific research. GalaxyZoo is different in a way that it recruits members of public to carry out galaxy classfications. Unlike the @Home projects, which rely on computer analysis of their data, automated programs have been unable to produce reliable galaxy classification. Human brain is far more efficient at recognizing patterns. Without human volunteers it would take years to analyze and classify the collected data.

The Galaxy Zoo files contain almost a quarter of a million galaxies collected by the Sloan Digital Sky Survey. More than 150,000 people have taken part in Galaxy Zoo so far, producing a wealth of valuable data and sending telescopes on Earth and in space chasing after their discoveries. On April 2, Galaxy Zoo hit the 20 million classification mark!