Kyleigh Kowalski

Hwyr and Hwys are the sources of heterogeneity!

• Resampled all sites except for nc1_3_slb

  • • Drop nc1_3_slb?

    • Next step? Confused by Hester's Methods > https://docs.google.com/document/d/12lw_lvReOTolG-T03SNaV-QV6fAalwVKbiURmW3-Pzs/edit > points then to txt

• symposium slides: (in progress) > https://docs.google.com/presentation/d/1i2XcnejDClcO7t4CCRw5Sw5GGVf08xQwqxrJDr5RIpo/edit#slide=id.g2bf13b31a79_0_9 

  • • What time? 3:15-4:45 pm for 10 min presentation? Where/when to meet to hand-over presentation?  Minor conflict with Pop. Ecol. Lab from 2:30 - 5:20. Professor is cool with me leaving early, but I would ideally stay as long as possible to get started on the lab

    • Download more ortho photos for the presentation? I only have photos for a hummocky and slabby site, neither of which are currently represented in the freq. distr. plots > screenshot areas in google earth

    • Which freq. distr. plot would be best to include / most easily interpretable by the audience?

      • • use python to aggregate all data into one place

Solved issue with 7x7_2m: https://drive.google.com/drive/folders/1WX5ZKO0u1vI9aQAjZmqF9IWc6GppE5yK

Clustering & data questions: https://docs.google.com/spreadsheets/d/17ELL61wZE0bAZk4zsPoB8Qnxs9O5d9DaLmFC9_rGdfw/edit#gid=0

Reasoning for f in some file names and not others:

"The devegetated holes were left empty in the 0.5 m/pixel, 1 m/pixel, and 2 m/pixel resolutions. Since we wanted to analyze the roughness of lava flows, we had the code skip areas containing holes within the moving window frame. There were many holes in the 0.1 m/pixel resolution, however, so skipping the holes prevented the code from generating results. Therefore, we filled all the holes with the average of the surrounding pixels. The validity of this choice was tested in the 0.5 m/pixel resolution, for which we could compare calculation results from filled and unfilled vegetation holes; the impact that this had on roughness values is discussed in the results section of this paper. The downsampled and devegetated DTM rasters were exported as point data for use in the code." (Mallonee, 2021)

--> Created a new working folder with all the-filled 10cm files renamed to 10cm so that the script would pull them as intended. Removed all duplicated 50cmf files as these seem to only be used to validate filling the 10cm files and were not actually used in Hester's analysis (also fixed the files missing the smth label).

The Juan de Fuca Ridge & Methods for Dating Lava Flows:

Clague, D. A., Dreyer, B. M., Paduan, J. B., Martin, J. F., Caress, D. W., Gill, J. B., Kelley, D. S., Thomas, H., Portner, R.A., Delaney, J.R., Guilderson, T.P.,  & McGann, M. L. (2014). Eruptive and tectonic history of the Endeavour Segment, Juan de Fuca Ridge, based on AUV mapping data and lava flow ages. Geochemistry, Geophysics, Geosystems, 15(8), 3364-3391. DOI: 10.1002/2014GC005415

• Summary / Abstract:

• Just north of the Gorda Ridge, high-resolution AUV mapping of the Juan de Fuca Ridge began in 2005. Mid-ocean ridges are typically limited in their ability to constrain ages relative to volcanic, tectonic, and hydrothermal events due to limited presence of radioactive materials in mid-ocean ridge basalts (MORBs). However, the minimum and maximum ages of lava flows can be determined by radiocarbon dating plankton which settle on top of the lava flows over time and foraminifera which are preserved beneath the lava flow. While this research focuses primarily on reconstructing the history of the Juan de Fuca Ridge, their data acquisition methods provide further evidence to support different sedimentation patterns on different submarine lava morphologies. They found that it was easiest to sample sediments from lobate and small pillow lavas rather than higher relief morphologies which captured thicker pools of sediment in deeper recesses and lower relief morphologies, such as sheet flows, where sediment was distributed more evenly in thin layers. Additionally, ROV observations of minimal sedimentation on young lavas further support a positive correlation between lava age and sediment cover.

• Questions:

  • • Q: What is hydrothermal sediment and roughly how much of sediment on the seafloor does it account for?

      • • A:

Fast-spreading Midocean Ridge Theories Tested on Slower Spreading Ridge (Alarcon Rise):

Clague, D. A., Caress, D. W., Dreyer, B. M., Lundsten, L., Paduan, J. B., Portner, R. A., Spelz-Madero, R., Bowles, J. A., Castillo, P. R., Guardado-France, R., Saout, M. L., Martin, J. F., Santa Rosa-del Rio, M. A., & Zierenberg, R. A. (2018). Geology of the Alarcon Rise, southern Gulf of California. Geochemistry, Geophysics, Geosystems, 19(3), 807-837. DOI: 10.1002/2017GC007348

• Summary / Abstract:

• Previous studies of fast-spreading mid ocean ridges reveal that there is a high degree of variability along the ridge axis which can be modeled by segmenting the ridge based on tectonic, magmatic, and hydrothermal parameters that are largely a function of different upwelling zones along the ridge. This research specifically compares these observations of fast-spreading ridges to intermediate spreading ridges in order to better understand how slower spreading rates may change these interpretations. Additionally, they were specifically interested in analyzing the entire ridge, rather than just segments as had been done in previous studies. They found that the inflated and most active part of the ridge is not necessarily located in the center of the segment as had previously been proposed, and in the case of the Alarcon Rise is instead located to the south of the segment’s center. → Is this due to rotation and shifting of the axis itself? What could influence it being skewed off-center? However, their findings do support previous proposals that the most active part of the ridge is the most inflated, has the youngest lava flows, contains the most MgO, and coincides with the most active vents.

• Questions:

  • • Q: "They found that the inflated and most active part of the ridge is not necessarily located in the center of the segment as had previously been proposed, and in the case of the Alarcon Rise is instead located to the south of the segment’s center." → Is this due to rotation and shifting of the axis itself? What could influence it being skewed off-center?

      • • A:

• Data Discussion:

  • • Q: Is it correct to assume that I'll be focusing on the very northern part of the MBARI data, where there is the center of the ridge and then ~3-4 steps extending east?

      • • A:

The Gorda Ridge:

Clague, D. A., Paduan, J. B., Caress, D. W., McClain, J., & Zierenberg, R. A. (2020). Lava flows erupted in 1996 on North Gorda Ridge segment and the geology of the nearby Sea Cliff hydrothermal vent field from 1-M resolution AUV mapping. Frontiers in Marine Science, 27. DOI: 10.3389/fmars.2020.00027

• Summary / Abstract:

• Initial modification of the crust at mid-ocean ridges involves the creation of crust at different rates, volumes, frequencies, and styles, such as hummocky pillow lavas or channelized sheet lavas. However, studying the post-eruptive modification of the crust–such as burial from sedimentation and the creation of crustal faults–is just as important as understanding the initial emplacement mechanisms. The entire Gorda ridge consists of the North Gorda, Jackson, Central, Phoenix and Escanaba segments which trend roughly northeast-southwest. The North Gorda and Escanabana segments particularly have been studied extensively due to the presence of hydrothermal vents. The North Gorda ridge mostly consists of hummocky pillow lavas, including steep-sided hummocks, hummocks with summit collapses, and ponded channelized flows, all of which range from 25 m to 150 m tall and are typically less than 200 m across. An eruption on the ridge in 1996 formed 3 main hummocky flows, consisting of 29 pillow mounds, all of which have relatively heterogeneous compositions that are identical to a previous eruption in the same location, demonstrating the importance of frequent monitoring and sampling of these sites as it can be difficult to distinguish different events based solely on composition. In 2009, the bathymetry of the latest 1996 eruption along the North Gorda Ridge was surveyed using sensors on Autonomous Underwater Vehicles (AUV) at approximately 1 m horizontal and 0.1 m vertical resolutions. This research details the strengths and weaknesses of each of the different AUV dives and their respective data collections. Additionally, this source specifically provides evidence to support a direct positive correlation between the lavas’ age and sediment cover with increasing distance from the ridge axis based on in-situ observations of sediment thickness and direct lava ages from 238U—230Th dating.

• Questions:

  • • Q: Is the bathymetry data entirely based on the Tiburon AUV dives? Tiburon had the best navigation, but was it's coverage enough for the entire mapped area, or was it supplemented by other dives as well?

      • • A:

    • Q: I am concerned about the default symbology that the PointToRaster files come in with, I believe the data was more or less "more continuous" when I did this step manually. However, unless this seems obviously wrong to you, I still need to complete the next step in the script to actually verify if this is going to work or if I need to modify the PointToRaster section somehow.

Surface Roughness Techniques:

Cao, W., & Cai, Z. (2018). Improved multiscale roughness algorithm for lunar surface. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(7), 2336-2345. DOI: 10.1109/JSTARS.2018.2822297 

• Summary / Abstract:

• MSR (morphological surface roughness) is a spatial domain of roughness parameters calculated with mathematical algorithms that has successfully mapped the roughness of lunar topography at multiple scales. This research focuses on improving these methods by quantifying the frequency of surface variations across different scales using a new method called improved morphological roughness (IMR), which is able to capture more complicated roughness measurements than other methods such as MSR and RMS height. In order to evaluate the performance of IMR, they compared it to the results from an RMS height analysis, a multiscale morphological (MM) spatial domain algorithm (SDA) calculation, a Fourier roughness analysis, and a statistic based Kurtosis roughness analysis. Ideal measures of surface roughness should be able to perform across multiple scales and maintain patterns for scale-dependent properties of the surface, represent the overall trends of the surface roughness without being altered by rotation or translation of features, and provide statistical information for many subsets of the data–not just for the entire data set as a whole. “Surface roughness” is not represented by a single, definitive calculation. Instead, it is often a combination of several roughness measurement techniques that vary from person to person. Not all surface roughness analyses use the same methods, which changes the ways in which they can be interpreted. However, most of these methods are based on SDAs that use topographic and elevation data. Roughness maps generated using SDAs often lose details and are limited in comparison to methods that instead use morphological surface roughness (MSR) algorithms to analyze and map surface roughness. After being compared to RMS height, MM, Fourier, Kurtosis, and finally MSR roughness maps, the researchers determined that IMR is capable of providing more detailed surface roughness measurements across multiple scales. Large deviations in surface vectors indicate rough surfaces while smaller deviations indicate smoother surfaces. Lunar regolith thickness has a smoothing effect on the surface that increases over time and can be used to date impact craters. In regards to my thesis, this article provides a detailed understanding of several surface roughness methodologies and their limitations with respect to each other and with respect to a new proposed methodology for specifically analyzing lunar surfaces. Additionally, it supports the ideas that increasing sediment along the North Gorda Ridge will smooth the surface, make it more difficult to classify the underlying morphology, and serve as an analog for lunar surfaces where regolith cover increases with age.

• Questions:

  • • "represent the overall trends of the surface roughness without being altered by rotation or translation of features" is paraphrased from: "reflect intrinsic property of the surface, and invariant with respect rotation or translation" and I don't actually understand what this means.

    • How different to slope and roughness maps tend to be? Below, it describes low roughness values as being characterized as flat, but surely flat surfaces could also have high roughness values as well right? These roughness maps seem very similar to what I would expect slope maps to look like for these study sites. 

      • • "For typical overview, the rugged bowl-shape wall of A1 area relates with low roughness values on the MSR map. As shown in Fig. 4(b), the floor of A1 is not as flat as those characterized in Fig. 5(a). The resulting map of IMR can provide a better roughness observations to represent the roughness details in the floor of A1. On the other hand, A2 shows the central peak complex of Humboldt crater and its “triangle” structure is like wall terrace in the southeastern part of the crater. MSR can reflect the roughness features of the sharp peak complex by corresponding with high roughness values from 0.6 to 0.8. However, the surroundings of the peak complex [bright and dark units in Fig. 4(c)] are characterized as flat by associating with low roughness values. On the IMR map, these roughness details are reserved by corresponding with the roughness values from 0.4 to 0.6."

        • A: Detrending = accounting for slope to measure roughness over large areas

Earth Analogs for Mars Volcanic Terrain:

Hughes, S. S., Haberle, C. W., Kobs Nawotniak, S. E., Sehlke, A., Garry, W. B., Elphic, R. C., ... & Lim, D. S. (2019). Basaltic terrains in Idaho and Hawai ‘i as planetary analogs for Mars geology and astrobiology. Astrobiology, 19(3), 260-283. doi: 10.1089/ast.2018.1847 

• Summary / Abstract:

• The habitability of other planets is a complex question that isn’t simple to answer as there are many factors to account for. However, the geologic substrate and the climatic conditions of other planets play a major role in beginning to understand planetary environments. Planets with highly active volcanic histories, such as Mars, can be further understood through the study of similar volcanic events and terrains on Earth. Volcanic sites in Idaho and Hawaii have been identified as suitable planetary analogs for Mars due to the basaltic lava features that cover the majority of the landscape–similar to the volcanic terrain observed on Mars. Specifically, the textural and topographic characteristics of lava flows at these sites can be compared to similar features on Mars in order to better understand the geologic past, present, and future of Mars. In relation to my research, this source defines the utility of studying regions such as Craters of the Moon as an Earth analog for lava emplacement controls on other planetary bodies. Sites such as Big Craters and the Highway lava flow at Craters of the Moon are useful analogs due to their basaltic composition and their accessibility. Studying these sites, describing their textural classifications, and analyzing trends in slope for various types of lava flows are crucial first steps in better understanding the volcanic history of Mars.

• Questions:

  • •  Is syn-eruptive alteration less common? I don’t think I’ve ever even seen noticeable red, orange, or yellow oxidation on lavas as pictured in Figure 2, much less purple.

    • They describe ESRP basalts as tholeiitic, which seems strange if tholeiitic means that it came from a mid-ocean ridge? Tholeiitic = compositional, not necessarily source.

    • Not a question, I just thought that this was really cool: "“Chemical breakdown of primary minerals, regardless of size, by normal low-temperature weathering or hydrothermal activity depends on temperature, pH, crystal composition, and structure. The long-term resistance to weathering of dominant minerals in basaltic rocks generally decreases in the order: plagioclase–pyroxene–glass–olivine (e.g., Hausrath et al., 2008). Olivine, the least resistant, may decompose within a few thousand years in warm, moist climates and thus may contribute to accumulation of available Fe and Mg for biologic activity. Volcanic glass may take much longer (several hundred k.a.); however, much faster rates of decomposition for all minerals are expected under nonambient conditions.”

Submarine Lava Flow Morphologies:

Gregg, T. K., & Fink, J. H. (1995). Quantification of submarine lava-flow morphology through analog experiments. Geology, 23(1), 73-76. PDF

• Summary / Abstract:

  • The chemical composition of a lava does not directly control the lava’s morphology; instead, lava morphology is more strongly correlated with factors such as temperature, flow rate, viscosity, and crystallinity. Submarine lavas can be described by three main morphologies: “Pillow lavas” that most commonly occur when lava effuses slowly over gentler slopes and cools rapidly, “Sheet lavas” that form in response to rapid effusion and slower cooling over steeper slopes, and “Lobate lavas” that serve as an intermediary between pillow and sheet lava types. Using laboratory experiments and wax-based lava analogs, a dimensionless ratio (𝛙) was established based on the time it takes to form a crust on a flowing material against the velocity of lateral flow. Specific values of 𝛙 assigned to specific submarine flow types allowing the rate of effusion of past eruptions to be predicted based on existing flow morphologies in relation to emplacement conditions and lava composition. In order to use 𝛙 as the basis for estimating the overall effusion rate of a submarine eruption, the most representative morphology type for the entire lava flow must be identified and the volume, viscosity, and temperature of the erupted material must be determined. Additionally, emplacement conditions such as ambient temperature, pressure, and slope must also be well understood. 

• Questions

  • What is meant by "the time scale of horizontal advection"? 

• Velocity controlled by mass discharge and slope/topography surrounding vent

Surface Lava Flow Morphologies:

Gregg, T. K. P. (2017). Patterns and processes: Subaerial lava flow morphologies: A review. Journal of Volcanology and Geothermal Research, 342, 3–12. doi: 10.1016/j.jvolgeores.2017.04.022

• Summary / Abstract:

  • Basaltic flows, characterized by relatively low viscosities, are the most frequently erupted type of lava and play a large role in shaping the surface of terrestrial planetary bodies. There are two predominant types of basaltic lava; pahoehoe and 'a'a. These morphologies arise from distinctive emplacement methods and are clearly distinguishable in surface, cross-section, and thin-section observations. Pahoehoe and 'a'a are most easily distinguished by their different surface textures. Pahoehoe is smoothed and wrinkled while 'a'a is angular and rubbly. Pahoehoe and ‘a’a are also distinguishable in cross section, in which pahoehoe has three distinct layers with a smooth and glassy top layer and thin basal layer, while ‘a’a has two distinct rubbly layers. Pahoehoe and ‘a’a are also distinctly different in thin section, with pahoehoe having larger, fewer crystals and ‘a’a having many smaller crystals. In addition to pahoehoe and ‘a’a lava textures, there are also features such as lava tubes and lava channels that are largely influential in classifying lava morphologies. Lava channels typically develop early in an eruption, during periods of rapid lava effusion. In contrast, lava tubes tend to form during slower stages of the eruption, potentially evolving from pre-existing lava channels if newly erupted lava continues to flow at a constant rate. It is also important to consider the impact of lava-flow inflation on lava morphologies and in predicting emplacement processes. Viscosity is dependent on temperature, composition, and the crystal and bubble content of the lava. As lavas move away from the vent and viscosity increases, pahoehoe flows can become ‘a’a. Steep terrain can also increase the shear rate on a pahoehoe flow and increase its viscosity until it transitions into an ‘a’a. A single flow may transition between pahoehoe and ‘a’a depending on how the viscosity of the flow changes in response to kinetic and spatial variability. Understanding the interplay between emplacement processes, lava morphologies, and transitions between pahoehoe and 'a'a textures is essential for interpreting the volcanic history of terrestrial planetary bodies. 

• Questions

  • Why exactly do turbulent flows cool faster? Do they also travel faster?

    • Is turbulence contained in interior? If sealed--the carapace is the limiting factor in cooling, advection helps get heat towards the edges while laminar transport

    • As velocity increases, Reynolds number increases, so if all remains constant: increased turbulence = increased velocity

The pixels are visually identical in size for the 3x3 1m and 7x7 1m (and same for 2m ,10cm, 50cmf). I'm suspecting that I did this part wrong and that the 3x3 is in meters, not pixels? However, the history in the ArcGIS Pro Project is empty and the properties only specify the vertical unit. It may be worth just redoing this part--I also am much more comfortable with ArcGIS Pro then I was when I originally did this so it probably wouldn't take as long.

I also forgot the reasoning behind the empty spots in the 10cm data, and I believe the "f" in 50cmf data means it was filled--do you remember the reasoning for only filling the 50cm data (and some 10cm)?

Reorientation to Project Processes:

• Acquired clipped raster data from Hester

• Resampled and calculated slope for the rasters w/ 3x3 and 7x7 neighborhood distances for all study sites / lava types

• Exported calculated slope and frequencies to excel

• Began compiling values in excel to display the normalized frequency data for each bin for each study area. 8 different charts; 3x3 cell windows at 1m, 20m, 10cm, and 50cm and 7x7 cell windows at 1m, 2m, 10cm, and 50cm resolutions. Almost done with 3x3 frequencies, still need to do 7x7 frequencies.

Hester's Thesis:

• Summary / Abstract:

  • The study aimed to standardize a classification scheme for lava morphologies through statistical methods. Lava formations hold key information about their emplacement conditions, but the existing practice of subjective field classification is prone to human error and inconsistent terminology. Additionally, improving our understanding of terrestrial lavas and developing remote methods of analyzing their characteristics can translate directly to the study of planetary lavas and the conditions at their time of emplacement. While planetary lavas are commonly classified using two dimensional profile methods, three dimensional methods may more accurately determine the roughness and textural characteristics of planetary lavas. Using a combination of aerial imagery and field observation, there were nine specific lava types identified across the Craters of the Moon lava fields in southeast Idaho upon which this study was conducted. Two methods of 3D surface analysis were used including Root-Mean-Square (RMS) height and Area Ratio (AR) for measuring roughness at various resolutions and window sizes. Through unsupervised k-means clustering, the study determined the number of morphology classes based on statistically clustered results from the RMS height and AR roughness measurements. Results did not conclude whether moving window size or data resolution was more influential and instead found that different combinations of window size and data resolution are best suited for identifying specific lava morphologies. Future research might involve slope analysis with moving windows and exploring slope deviation for enhanced lava type classification.

• Questions:

  • These two different window sizes were used to visualize lava flows of different scales. Some larger features visible in a 7x7 may not be visible in a 3x3 (which seems backwards to me)

  • Usually there’s an issue with features being finer than the resolution of the data, but there seems to be a more of an issue here with features being too large to be fully captured given the limitations of the moving window size, or is the resolution of the data also a limitation for large scale features?

Lava Types Nomenclature: 

Harris, A. J. L., Rowland, S. K., Villeneuve, N., & Thordarson, T. (2017). Pāhoehoe, ‘a‘ā, and block lava: an illustrated history of the nomenclature. Bulletin of Volcanology, 79(1), [7]. https://doi.org/10.1007/s00445-016-1075-7

• Summary / Abstract:

  • Early lava classifications were overly complex and lacked consistent or clear terminology–they were based on detailed descriptions of perceived characteristics, many of which could exist for an identical lava type depending on the narrative style of the observer. Not only were the descriptive terms themselves highly subjective and variable, but the interpretation of these descriptions was also highly subjective and varied strongly across cultural and spatial contexts. Ultimately, an early classification system using the Hawaiian nomenclature, pahoehoe and ‘a’a, was widely accepted across most of the world, even despite controversial arguments against the culturally defined terminology. Eventually, block lavas were designated as being distinctly different enough from ‘a’a that it became its own separate class, resulting in the tripartite classification scheme of three main lava types; pahoehoe, ‘a’a, and block lava. While pahoehoe and ‘a’a are generally described as smooth and angular basaltic lavas respectively, and block lavas are described as angular silicic lavas, each of these morphologies has been further classified into subtypes based on the scale and characteristics of textures and mechanisms by which they were formed. Using distinct descriptor words in conjunction with their respective broad classifications can help simplify how lava is described and communicated within the scientific community. 

• Questions:

  • N/A?