The JPEG2000 image file format is pretty darn cool, however, there are a dearth of good bits of Open Source software for dealing with them. The HiRISE team distributes the IAS Viewer to allow you to browse the HiRISE JP2 files on their JPIP server, or you can also use it to view JP2 files that you have downloaded. A colleague of mine let me know about the JHelioviewer software that is an Open source JPEG2000 viewer capable of loading local JP2s and reading from JPIP servers. It is developed by the solar physics community (they have big pictures of the Sun), and many of its user aide features are geared towards the solar physics community (and their need for time-domain movie-like data). However, it works just fine for HiRISE images, and provides an Open Source alternative to the IAS Viewer.
The Web page for Detexify2 really says it all, but it is essentially a handwriting classifier that turns your mouse-drawn scribble into the appropriate LaTeX symbol code. I appreciate that this is for LaTeX-nerds only, but wow, is it ever awesome.
Help us put scientific papers on the map—of Mars!
Here at NASA Ames, we're working with Google, Inc., and the SAO/NASA Astrophysics Data System to get scientific papers geo-located on Mars. Although we'll start with explicitly geo-locating a few, we want to enable a system so that the scientific community itself can add geo-location information to already-published works, and encourage future publications to include easier to parse geo-location information.
Lots of blogs (here and here) and news outlets have covered some of the great new Mars features in Google Earth. I will assume that you have read those blogs, watched various demonstration videos, or even watched some of the Guided Tours available in the Google Earth client itself. I will most certainly assume that you have at least taken a cursory spin around the Mars in Google Earth (we refer to it as Google Mars internally—at Ames and Google—but since that has meant the 2D Google Maps API Mars maps for so long, I don't want to confuse people).
For the discerning visitor I present a number of little perks that you might not notice. Mars in Google Earth is primarily targeted at a general public audience, but we've also slipped in some pretty cool extras (if I do say so myself) for scientists and advanced explorers alike.
HiRISE images are huge, frequently 1.5 GB, and they are in JPEG 2000 format, which many image software programs don't (yet) handle. So what do you do if you need to work with just a small area of that image at high resolution? This post explains how to get that subframe.
Tired of not having a proper LaTeX template for writing LPSC abstracts and abstracts for other LPI meetings? Still limping along on the old LPSC LaTeX template from 1996? Moses and I hacked together an LPSC LaTeX Template that conforms to the format requirements for LPI meetings. Enjoy!
All of the data in the Planetary Data System (PDS) have a detailed set of labels (meta-data). Sometimes these labels are in separate files (detached labels) or are embedded in the data file itself (usually as a header). The data of these labels are encoded in a text-based framework known as a parameter value language (PVL). There are several approaches to programmatically parsing and reading these PDS data in PVL format. This article discusses several of the libraries that exist in C, C++, and Java that can help you with your PDS PVL needs (reading and writing).
For those of you interested in a generic tool for viewing stereo pairs and manually editing match points, I developed some freeware (if you have IDL) to do that, and it can be downloaded at http://www.gi.alaska.edu/~rherrick/smt/index.html. It works under IDL and there is a users manual and installation guide on the web site. I had an abstract about it at the 2005 LPSC (abs. #1984). The download includes sample image pairs from Magellan,
Jumping off from this discussion, I'd like to hear more about what ISIS is all about, and whether I should consider using it. I work primarily with Cassini ISS data, and my main issue is that, since I work with rings, I'm interested in a cylindrical coordinate system rather than a spherical one. My other issue is that I'm accustomed to using IDL rather than C++, but I could consider changing if other issues came together.
Not all images are the same. Frequently, to do science you might want to compare two different images at the same resolution, or map them to the same grid, different from the original. To map to lower resolution you should co-add pixels, but to map at a higher resolution you might need to interpolate. This article discusses four interpolations schemes, how to use them, and which might be best for you.