Update: I met a lot of interesting people at the Science Online London 2009 conference last Saturday. One of them was Arfon Smith who is the technical lead on Galaxy Zoo. We was kind enough to demonstrate for me the first prototype of the Moon Zoo web interface and let me tell you – even though it is just the first prototype, it was sweet!
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.
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.
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.