Back in the Saddle

Dear Dialog,

Back in the saddle again, so to speak. The winter break was nice, got to recharge, see my family and visit my partner’s family, too. A separation from the academic life showed me where I tend to exist is, to some extent, a bubble. I faced different challenges than I was anticipating and did not have challenges where I thought they might arise. It also feels good to be back into a stride.

Getting back up on the horse that is research has been straight forward this year. With a semester under my belt, I have a decent understanding of what I should be doing: find a candidate site, download some images, analyze those images, repeat. I can put my blinders on and focus on the carrot being dangled in front of me. This year, I have already finished up the a couple of projects that I hadn’t gotten around to last semester (with the exception of a final branding of approval by Catherine). For example, check out Zumba crater and all that melt! Whee-doggie that looks good!

In situ map of Zumba. Orange refers to pitted pools, blue to smooth pools, and pink to possible pools. The line refers to the rim of the crater measured from a HiRISE-made DTM.

In situ map of Zumba. Orange refers to pitted pools, blue to smooth pools, and pink to possible pools. The line refers to the rim of the crater measured from a HiRISE-made DTM.

I have written down my process and will follow it for the next few projects. Sheepishly, I admit I have been avoiding completing my current favorite site, Mojave crater. As of today, I have 40 GB of images to work with and I want to be sure that I won’t waste my time doing a massive project that is incorrect. Rest assured, I am champing at the bit to complete that one.

Another fun tidbit for the current times is the US government is currently in its 3rd week of a shutdown and the USGS Astrogeology site has been been down when I try to access it. A minor inconvenience, but I will need it to be up an running to process images eventually. It’s feasible to code it but the site’s server is already pretty fast at doing it.

Part 2.

I recently came across Felice House, an artist who takes a critical eye towards traditional imagery. In this gallery, she reimagines old western heroes as females. By combining techniques of computer science and painting with gender-bent ideas, she effectively challenges and shifts our preconception of what femininity and masculinity may look like. These examples show that our existing ideas or representations of professions could use a second hard look. As detailed here, the use of classic male body language and physically dominating size (the last image for a comparison) lend to the challenge of traditional gender roles. And I would argue that the heavy handedness of the color red throughout adds to the depiction of female empowerment. (More than) A few questions come to mind in this gallery. Why are cowboys thought of as ultra macho and the epitome of American masculinity? What influences have propagated that idea? Why have women not been depicted in a similar way? Why does this challenge us in the first place? Does this bias still exist today? There are of course lots of questions and answers that can be sparked by this gallery. Since this is an academic-focused blog, let’s try using that framework. Why are scientists often thought of as male? What power comes into play maintaining that status quo? Why are women underrepresented in STEM fields? Would we be challenged if similar artwork was created about our field today?

And to drive home the point of unequal treatment of genders, a twitter post about an astrophysicist:

With these questions in mind, taking a critical eye towards visual entertainment such as movies, tv or even social media, can be a beneficial exercise towards conscientiously choosing the kind of content we surround ourselves with in the first place, including in the STEM fields.


November Review and Feminist Lexicon

Dear Dialog,

    Firstly, my research has progressed steadily over the last couple of weeks. Had a meeting with Livio about how my identification of melt pools stacked up and he mentioned they generally looked pretty good. I can even expand the search to ponded and pitted, smooth, and possible melt pools. 

    Secondly, homework for the CPSX seminar was to create a video of ourselves saying an elevator pitch of our thesis. This exercise was useful for showing just how many idiosyncrasies come across when I speak or think about what I need to say. Check it out below!

    For our main discussion today, I would like to draw attention to the language we use within our communities and how it can affect those around us. It has been well studied that women and minorities in STEM fields have been woefully under-represented, especially as they go further along in their studies and careers, a phenomenon also known as the "Leaky Pipeline". (Here are a few great examples of blogs about women in planetary science, astronomy, and space! Thanks to Dr. Catherine Neish for the recommendations.)

    While this systematic forcing out of women is an entire thesis at the very least, a casual but large facet of it is everyday language. Examples can include referring to occupations where a male is typically referenced in the position like policeman fireman, congressman. Languages such as German or Spanish where nouns are given masculine, feminine, or neuter can also influence the way we think about them. More gender-fair language (GFL) these terms could be police officer, fire fighter, congressperson. GFL has the specific intention of being more inclusive. This can even extend to folks who gender non-conforming. We need to change our lexicon to be more equitable and less male-centric, like not using 'he' or 'man' to refer to humans on the whole. Here are some examples about how to make the shift, it can often just need a conscientious decision. We can not afford to stand on the sidelines choosing not to engage and in this era, there is no reason for us to not be familiar with how these issues propagate through our society.

    To further this point, we need to acknowledge and reconsider how we describe those around us, especially in context of their gender identity. Just a few days ago, a blogger criticized the wardrobe U.S. Representative-elect Alexandria Ocasio-Cortez trying to undermine her platform. While this may be a little removed from STEM fields, the idea is the very much the same: women are often not judged on their aptitude. Other common descriptors towards women, such as their morality and sociability, in a professional setting are often biased and limiting.  This definitely includes dress codes for conferences (and they are oppressive towards minorities, too)! These differences in descriptions go hand in hand with the double standards that many women have to constantly face. We need to think about where these descriptions come from and what implications they have in the larger picture. 

    And finally, using blatantly sexist language such as the b-word or c-word to put others down, especially if you are a male, is reprehensible. Even though it is becoming rarer in professional settings, it can be more common in casual ones. The words have gone through a sort reclamation and its definitions can vary. The onus of a person who uses the word should to understand its origins, history, and modern day contexts and identify their privilege in being able to say them. 

    With all of this said, it is my belief that we are able to make small changes steadily building towards larger goals, such as paying attention to what we say and how we say it in order to make a more equitable society. Understanding the context society has formulated for us to live in can reveal hidden, and not so hidden, ideas that we cannot afford to turn a blind eye towards, especially since we shape what comes next.  


Short and Sweet Nov 7, 2018

Dear Dialog,

This entry is give you a brief update on how things have been going on the research front. 

  1. Finished Tycho (tee-koh) Crater mapping. There were a few issues on pools vs veneer but Catherine and I cleared those up so we are on the same page

  2. New setup. Moved from the Mac Mini (which I updated to Mojave and updated isis data/ software) to the Windows 10 computer with ArcGIS (QGIS, I did not give you up without a fight. I am sorry to say it's not me, it's you. We are just too incompatible and perhaps I am just not ready to solve your projection issues with you. Maybe we will cross paths in another life. I don't regret what we had.). Seeing as my thesis heavily includes mapping, I requested a second monitor to work on. Catherine was generous and let me repurpose one of the extras from the lab. And now my set up is complete and my environment is mostly to way I like it so I can move on from so much installation and troubleshooting.

  3. Mars Mars Mars! Finally moving on to the Red Planet. I initially tried processing the HiRISE images through isis but, turns out, HiRISE is the one instrument that does not need additional processing. So the native JP2 files, along with LBL files, are fine to use. Project selection was primarily based on Livio's 2012 database detailing well-preserved craters, henceforth refered to as Craterbase. Here are some of the projects I have been working on:

    1. Zumba Crater

    2. Corinto Crater

    3. Mojave Crater

    4. Domoni Crater

    5. Northeast Ascraeus Mons 

  4. HiWish. On Nov 6, 2018 the Mars Group with Livio had a planning meeting and I submitted my first suggestions! Now, we wait to see if they get accepted and imaged. Check them out here and here!


Progress Report Oct 17, 2018

Dear Dialog,

This week, I will be updating you, for the first time, on how research has been going! My research will consist of relating melt pools, and their characteristics, on Mars to melt pools seen on other planetary bodies within the solar system, such as Venus, the Moon, and Mercury. The investigation will help elucidate whether there exists a correlation between melt distribution, topography, impactor size, amount of melt, and/or impactor angle. To do this, I am using isis photogrammetry software, QGIS, and ArcGIS to process surface images and map the pools proximal to the outer crater rims. 

I first needed to understand what melt pools looked like before I could map them. They are melt from the impact that has flowed over the rim and pooled in the low topography areas. Similar to lakes that form on mountains from snow/rain run-off. Lots of areas will have gotten wet at some point, but the water will tend to collect into lower potential areas. These melt pools have shown interesting features. On the moon, there is a strong inverse correlation to impactor angle and direction of flow. Whereas on Venus, there is not a significant correlation. So investigating the Martian flows will be the next step towards understanding the further out bodies of the solar system, including icy bodies. Part of what makes Mars unique in particular is the fact that it has an atmosphere. This facilitates aeolian processes. Dust is a large part of the Martian environment and covers most of the surface, at least to some extent. This dust can often lie on top of the melt pools, obscuring them making their identification difficult. More on this topic in future posts.

So far, my research has consisted of establishing my environment and troubleshooting different softwares. Let me walk you through them! The isis software, stumped me for a little while. I tried accessing it on a Windows machine, installing cygwin in order to run bash commands, which is a requirement for isis. But this led to a dead end after exhausting possibilities of broken scripts/pathways and subsequently reading that isis runs on Mac OS. Moving on to the Mac mini, I tried reading through the maual looking for a way to run isis. Initially, I had to add where the path of isis was to the .bash_profile file located locally on my account so I could run isis from Terminal fluidly. Then, I had it in my head that I would need to enter, so to speak, the program much like python within Terminal, where one executes the name and then the program is accessible. This was not the case. The proper way to access the software is simply by typing the command into Terminal along with any needed parameters. Hurdle crossed. 

Onto processing! The images need to be found on source websites. After attempting to create a project on Mars around Resen crater for practice, I was informed courteously by Catherine that the "melt" I had mapped was, in fact, very wrong. We took it step back and decided to map some pools on the Moon since they are easy to identify due to a lack of erosional processes. To do this here is the process:

Access Jmars or the Lunar Orbital Data Explorer website to find the images you would like. Investigation included looking at LRO NAC and LRO LOLA data(process still in progress). Download the .img and .lbl files. Run the following commands:

$ cd /homePaths/GISProjects/{projName}/Preprocessing/

$ lronac2isis

> Input: M103831840LE.IMG 

> Output: M103831840LE.cub

> Run

$ spiceinit from=M103831840LE.cub

$ lronaccal

> FROM: M103831840LE.cub

> TO: M103831840LE_cal.cub

> Uncheck all defaults for now

> Run

$ cam2map 

> FROM: M103831840LE_cal.cub

> MAP: $base/templates/maps/

> TO: M103831840LE_cal_cam.cub

> MATCHMAP: Don’t check “Match the map file”

> Output Map Resolution: Compute resolution from input cube (CAMERA)

> Output Map Ground Range: Minimize output image size

> Run

Ta-da! You should have a GIS-friendly .cub file now. Now we can open QGIS (or ArcMap if you move the files to a Windows computer) and create a new project. Define the Coordinate Reference System, CRS, to be "Moon 2000". Then Add Layer > Raster > {yourMoonImage}.cub. Check Properties to make sure the image is also in the Moon 2000 CRS. Next, verify the Draw Freehand tool is available. If not, Plug-Ins > Manage > Search for "Freehand" > Add > Close. Now we need to add LOLA data, but TBD. We also need to create a few shapefiles. Add Layer > New Shapefile > Polygon> Name it "meltPools". In the bottom left, where the loaded files are shown, Left Click meltPools > Toggle Editing. Now we can start drawing what we think are melt pools! Below are two examples of craters with melt pools drawn from LRO NAC images.

A very conservative mapping of Image M103831840LE:

The melt/flows are shown in blue. A large portion of this image could be melt, including venier. Only the most blatant flows/melt have been marked.

The melt/flows are shown in blue. A large portion of this image could be melt, including venier. Only the most blatant flows/melt have been marked.

From the eastern rim of Tycho Crater Left and Right:

Here we see the melt denoted in mauve. There is also strong indicators of melt, including colling cracks and albedo changes where the pools are located.

Here we see the melt denoted in mauve. There is also strong indicators of melt, including colling cracks and albedo changes where the pools are located.

#TODO next will be to nail down how to process the LOLA data and incorporate it into GIS projects. From there, I can start working on Martian melt.


Visualization of Data

Dear Dialog,

This week I would like to discuss the visual representation of data. This entry is directly and heavily influenced by Edward R. Tufte's 1983 book tilted "The Variable Display of Quantitative Information". You can check it out here! Data represented in graphical form is of the utmost importance, particularly when it comes to science and relaying your results to others. We will be discussing what makes a good and poor representation. Just like words, images can convey complex meaning and further our understanding of a topic. Tufte suggests the following criteria to be meet for a suitable representation.

- Show the data, with clarity and integrity

- Make large datasets understandable

- Encourage the reader to mostly think about the substance (not methodology, production, techniques, etc.)

- Reveal data at multiple levels (from big picture to the minutiae)

Within these parameters we can gain a foundation for what can make or break a graphical display. Let's dive into a few examples of each and see what went right or wrong.

Example 1: Death Map


In this visualization, the US is broken into counties and death tolls from cancer are given by rates of 100,000 people per county. Generally, the darker the hue, the higher the death toll is in that county. The representation does an excellent job at showing where there are curious groupings of counties that would seem to be a relative hotspot of deaths. Our eye is immediately drawn to the Kentucky/West Virginia border. From there, we can gleen a general idea that the cancer death tolls are higher in the south than the west coast. This a good example of showing big picture trends along with the finer details. It also demonstrates keeping the readers attention on the data rather than methodology. A modern aspect of this map, if you click through on the link, is the time variability that can be played with. So not only does it show the counts over a year, but does so over many years. What this image does not represent accurately is the population distribution. The geographical area of the counties may lead us to think the county lines show population too, but that is not the case. Additionally, death tolls can be hard to accurately survey, since coroners/doctors may not always put the correct cause of death, but rather the easiest or most obvious one. 

Example 2: Napoleon's Retreat Minard


Here, in the bottom panel, we have a display drawn up in by Charles Joseph Minard detailing the defeat of Napoleon's army in 1812. Tufte explains, "It may well be the best statistical graphic ever drawn." This map shows the path and size of Napoleon's army from the western edge of Russia to Moscow. On the left side, in red, is the start of the army's movement. The width of the line represents how large the army is at that point in time, starting at 4000,000+ soldiers. The offshoots show small groups of soldiers breaking off to prevent a flank attack. The direction of the army was generally east until they arrived in Moscow. They ended up retreating and their path to return home is denoted with the black line, ending with 10,000 soldiers. The bottom graph also indicates the temperatures during the retreat. There are six variables shown here: army size, direction, location in 2D space, dates, and temperature during the retreat. The amount of information contained here could've been read through a table but the integration into map made it incredibly more meaningful and interesting.

Example 3: Marey_Paris_Train_Schedule


This graphic, made in 1885, is from E.J. Marey, Le Methode Graphique, page 20. This shows the train schedule from Lyon to Paris, France in the 1880. The horizontal lines across the plot show the relative physical distance between each stop. The vertical lines describe time. Lines at an angle, broken up with horizontal lines which indicate waiting time, indicate the train speed. The closer to vertical the line is, the faster it travels. Lines are from Lyon to Paris and visa versa. So, with this display we can figure out how long it might take to get from Lyon to Paris depending on what time we left. This graph clearly has lots of information and can be overwhelming. But the depiction is creative and illustrative of train scheduling. 

Discussion: Data-Ink Ratio

In the theory of data graphics the montra is "Above all else show the data". So with that, we want to ideally show only and exactly what is necessary for us to print. Data-ink is defined by the non-redundant core drawn data. This is the data that you can't erase without losing important information. According to Tufte, the data-ink ratio is

Data-Ink-Ratio = Data-Ink / Total Ink In Graphic

The ideal ratio, of course, would be 1 where only the necessary information is drawn and there is no excess. This isn't the case for most graphs. But there is a balance that needs to be struck. As long as a justifiable reason can be made to include the ink, then it can be fine. Simplifying your graphs and plots can be a huge step forward into making your data easier to read. There are tips and tricks like range plots and dot dot dash plots that can reduce the amount of ink needed to create your figure.


Take the Marey Schedule with it's Data-Ink-Ratio improved. It certainly looks more readable!


Low Down on HiRISE

Dear Dialog,

Today, I will give an overview on some interesting tidbits and an insider look about the HiRISE camera onboard the MRO.

For quick reference:

MRO: Mars Reconnaissance Orbiter

HiRISE: High Resolution Imaging Science Experiment

In 2006, MRO settled into orbit around Mars. It has been running for about 12 years now! Meaning the lifespan has exceeded the primary science goal by approximately 10 years. This is among the longest running space exploration projects to date. Although HiRISE/MRO sometimes runs into troubles, like defaulting into safe mode, it largely has been been an enormous success. Our understanding of the surface of Mars has been greatly increased by it's presence. A few other instruments aboard the spacecraft are The Context Camera (CTX), Compact Reconnaissance Imaging Spectrometer for Mars (CHRISM), and Shallow Radar (SHARAD). These have contributed to many discoveries including Residual Slope Lineae (RSL) and dune movement measurements.  In short, the HiRISE camera is essentially a telescope that points towards the ground. Its resolution has been compared to that of conventional Earth based satellite imagery, sometimes even better (although military satellites are another story). The camera is set up as a pushbroom, meaning, in a sense, it scans the surface as the instrument moves along its orbit. This is in contrast to frame cameras, which is similar to a photographers camera where an aperature is opened to accept light from the entire field of view all at once. The pushbroom style has a couple of advantages to it, including varying the length of images. The ability to toggle the length of the image is particularly helpful when scientists or citizens want to observe a really small or really long patch of the surface. The average HiRISE image is ~1-2 GB so being able to save memory space is crucial for smooth transmission back to Earth. Another useful aspect of the HiRISE camera is its color receiving CCDs. initially at the mission proposal, the scientists wanted full images in Red, Infrared, and Blue-Green bands. Due to weight and size constraints, the IR and BG bands had to be reduced in size from 10 CCDs to 2 each, placed in the middle. Since Mars emits most of its visible light in the Red band, it was kept at 10 CCDs. In 2011, the RED9 CCD died and so it no longer can process the light it receives. However the upshot is, of all the CCDs to kick the bucket, RED9 was probably the least problematic, tied with RED0, since it is on the very edge of the array. Below is an example how the CCDs are arranged.


Image Credit: HiRISE

HiRISE has been focused on geologic science for most of its life, but sometimes it takes a break to monitor other goings-on around it!  In 2007, shortly after MRO entered its science orbit, the spacecraft rolled enough so that it could capture the Earth and Moon in this picture. There was also a fair amount of post processing to make it look as nice as it does.


Image Credit: HiRISE

In 2008, before the Phoenix Lander arrived at Mars, the mission planners of HiRISE knew where Phoenix would land and figured out what time the lander would be entering the Martian atmosphere. With careful calculation and planning, they where able to orient the spacecraft to point in the direction of the approaching lander and captured this incredible image!


Image Credit: HiRISE

And in 2014, Comet Siding Spring made a fairly close approach to the red planet and MRO was able to point toward the comet long enough to snap a picture, and then afterwards mission operators tried to keep the craft on the opposite side of the planet as much as they could, so the dust particles wouldn't damage the craft. 


Image Credit: HiRISE

In 2015, while I worked as a student validator for HiRISE, a few images came through looking for the lost Beagle 2 mission that the UK launched in 2003. Scientists overlaid multiple images of the area in order to increase the resolution and eventually they were able to find it! The lander was lost soon after getting to the surface, and scientists now think it was because some of the solar panels were not fully deployed. Although I was among the first people to view the image, I was not able to identify where Beagle 2 was until the scientists overlaid the images.


Image Credit: HiRISE

All in all, HiRISE has been an amazing instrument for Mars and for us. The notion that I get to keep working with it fills me with happiness! Soon I may be applying this data to actual requesting of images so I can be on both sides of the equation for HiRISE!


First Entry!

Dear Dialog (Diary + Blog),

This week has been more action-packed than most. I finished up the Planetary Short Course, visited with my parents, then traveled from Detroit, US to Toronto, CA to Reykjavíc, Iceland to Paris, France to now home here in London! Compound this with the hunt for a new apartment and I've hardly had time to take a breath. 


In these pictures, you can see some of Iceland's natural beauty. Wonderful outcrops of land being eroded by the sea, black sand beaches, oodles of lava flows, and an abundance of clouds and mist. Unlike most of Europe, where it's been uncharacteristically hot, Iceland is being lambasted with an unusually cold summer. Icelanders have shown a tenacity for resiliency. Every year they look forward to their summer season but since this year's summer weather fell way below expectations, they've shown a remarkable positive attitude for "perhaps next year will be better" and "we'll just keep on doing what we do".

The recent facilitation of tourism to Iceland has also brought numerous tourists. This has helped the recent economy a bit (the industry accounts for about 10% of their GDP) but for decades Iceland has struggled with their economy and inflation, in part due to their unique currency and small size, which has made them susceptible to volatility and in a addition to dissuading possible trading partners.  

In the above picture, I have located a very small (and free!) hot pool located to the Northwest of Reykjavíc. It was a welcome relief from the cold breezy morning that day! What can't be beat, is the unique geology that Iceland has to offer. An island that is famous for its geothermal energy sources and preserved nature. It is one of a kind and a bucket list item for many geologists. I am glad to say I was able to go and get a very brief taste of it. I hope to go back soon to fully enjoy everything about the island.