While the morphology category data (MORPHOLOGY_EJECTA_1 through 3) is interesting, this data is not available for most craters listed in the data set.Additionally, the available data on morphology may prove difficult to interpret based on my existing knowledge.I am currently in the first week of the first course, Data Management and Visualization.
Original image from NASA/JPL at: https://gov/mer/gallery/press/spirit/20040110a/2NN006EFF02CYP05A000M1-A8R1_Purpose This post is the first in a series related to my coursework in Wesleyan University’s Data Analysis and Interpretation Specialization on Coursera.
In this program, I will be applying data science tools to specific research questions of my choosing; including data management and visualization, modeling, and machine learning.
While there are several Python libraries that handle location data — examples include Geographic Lib, Geo Pandas, and Arc Py — these libraries may need some adjustment to handle the location coordinate system specific to Mars.
Existing Topic Research and Hypothesis A search in Google Scholar yielded some earlier research on the characteristics of Mars craters, based on data obtained from the Mars Orbital Laser Altimeter.
The data sets for the above and earlier studies are not readily available for comparison.
However, the Aharonson study does indicate that certain physical characteristics, such as diameter and rim slope have a correlation.
Alternately I can choose a public data set of my own.
I must then provide a topic of interest related to the specific data set.
Hiesinger (2013), Lunar sinuous rilles: Distribution, characteristics, and implications for their origin, Planet.
Mazarico (2010), Global distribution of large lunar craters: Implications for resurfacing and impactor populations, 1504-1507, doi:10.1126/science.1195050.