In many instances, images can speak for themselves. However, one often wants to put arrows or indicators on an image mentioned in the caption or the text. This article explains a few ways to do that with the GIMP.
Not quite sure where to start with data from the Mars Global Surveyor spacecraft? This article contains links to the raw data, and also links to the various software tools that members of the community have created to analyze the data itself.
Some images are worth 1000 words. Similarly, some movies, or animations, are worth 1000 images, even if they are made up of fewer. What I'm trying to say is that there are some concepts which are better illustrated using animations rather than just graphs or images. Hal Levison, for example, shows movies of orbits changing as a function of time that give a better impression of orbital evolution, and in less time, than a succession of plots. Strategic use of animations really increases the amount of understanding that you can transmit to your audience in a 7-minute talk. Generating simple animations is easy using the command-line-driven ImageMagick software.
Oftentimes when faced with a data-rich environment, a good way to begin the process of analyzing and organizing the data in order to get a look at the big picture is to use a classification scheme. Here I describe some ways to classify data, practical uses, an in-progress application of the data to Visual and Infrared Mapping Spectrometer (VIMS) spectra of Titan, and some links to other places to obtain further information.
Not too many authors think critically about their selection of color for their data graphics, I know I have been guilty of that. This article by Light and Bartlein (2004) is a good discussion of the issues, and they also have a nice color scheme resource.
If you use the Generic Mapping Tools (GMT), I've attached some color tables below that can be used by GMT's
makecpt program. If they aren't the ones that you want, they should serve as a guide for how to make them.
I describe here principal components analysis, a method for condensing the information present in images with many colors into fewer channels. This section is heavy on linear algebra—just a warning.
I am presently using this to try to map Titan into spectral classification units using the Visual and Infrared Mapping Spectrometer (VIMS). VIMS takes simultaneous 64×64 images in 256 different infrared channels at wavelengths between 0.9 and 5.2 microns. However, VIMS can only see through Titan's atmosphere and down to the surface in a handful of spectral windows, totalling maybe 20–30 channels. The remaining channels probe different levels in the atmospheric haze, but most are redundant.
I am using principal components analysis (PCA) to bring out subtle variations by reprojecting the VIMS 256-color maps into a different set of orthonormal basis vectors that span the same space, but have most of the data's information in only 9 or 10 channels instead of 256. Woah.
Generating posters for scientific conferences is best done using a vector-based graphics system. Although it can be done using Photoshop or the GIMP and a 10,000 by 10,000 canvas, vector-based approaches use less RAM and therefore run faster on most machines; they also offer more flexibility in the alteration and rearranging of both text and images. Similarly, you should use a vector-based graphics system to generate figures for scientific papers—being arbitrarily scalable, they'll keep your figures looking good even after the journal editors have manhandled them.
Tired of not having a proper LaTeX template for writing papers for submission to the Journal Icarus? Frustrated by having to then re-format to Elsevier style guidelines once the paper gets accepted? So were we, so we hacked together an Icarus LaTeX Template that conforms (mostly) to the format requirements for the Icarus Editorial Office, and also allows for a straightforward transition to the Elsevier style (although with a fair amount of cutting and pasting).