Daliedmarie Delgado Maisonet

Project: 

The presence of ice deposits on the Moon is key for NASA’s future human-based solar system exploration, but little is currently known about the ice volume and distribution. I will be using a terrestrial lunar analog in the ESRP to evaluate morphometric relationships that arise from progressive sediment cover burying various lava flow types, and how that evolving bulk roughness influences self-shadowing. UAS equipped with LiDAR will collect high-resolution (~1cm/pixel) elevation data, visible wavelength imagery, and thermal data from ESRP lava flows. Methods like rugosity, root-mean-square height, slope, and insolation will be used to calculate terrain roughness, shadowing, and reservoir volumes for potential Ice Stability Regions (ISR). The goal of this work is to generate high-resolution digital elevation models (DEM) from aerial imagery. 

 Goals: 

• Complete a Master's degree

• Improve scientific communication skills (written, presentations, networking)

• Improve fieldwork, lab, and coding skills

• Develop leadership skills

• Improve teaching skills

For 9/22:

• Roughness: The UAS curves are looking much better. But do you have images or other justification for switching the western low-albedo zone from rough to smooth? How does this influence other areas where albedo was used as a proxy?

• Albedo vs ATI:

  • Visual inspection doesn't match the non-correlation in UAS data for COTM. Re-look at how you're correlating them.

  • HHA: need to use ATI instead of dT to account for the shape of the hill on temperature

    • Re-access Tyler's RGB from HHA and get it to display correctly

• Sediment data:

  • It is currently dropping a bunch of dT values. Is it a problem with the export? Find the error and fix.

    • Re-do plots

  • Do supervised classification of rocks vs non-rocks in field photos

    • Do plots of 1) % rx (SKN field estimate) vs dT and 2) % rocks (classification of photos) vs dT

  • Do depth and %rock cover correlate to one another?

  • For the affirmed relationships, create equations 

  • Use the depth->dT equation and the topographicResidual-> depth equation to estimate sediment thickness rasters based on dT

  • Can you do a similar process for %rock cover?

<Pause while establishing at new job>

For 8/28:

• Crash recovery

• Roughness: The UAS curves are looking much better. But do you have images or other justification for switching the western low-albedo zone from rough to smooth? How does this influence other areas where albedo was used as a proxy?

• Albedo vs ATI:

  • It just seems off that we lose the correlation with better resolution, when it should go the other way. How certain are we that everything is correct? When files recovered, send SKN an image of the ATI or dT for the UAS datasets (COTM and HHA), plus an image of the RGB.

• Sediment data task: find in file recovery and send to SKN

• Fieldwork results:

  • Once recovered, send combined dT vs depth to SKN (use all points except zeros for cobbles). Also plot/recover dT vs %rock on surface using SKN field estimates and own photos (2 different plots). Use supervised classification for %rock from photos.

  • Do depth and %rock cover correlate to one another?

  • For the affirmed relationships, create equations 

  • Use the depth->dT equation and the topographicResidual-> depth equation to estimate sediment thickness rasters based on dT

  • Can you do a similar process for %rock cover?

• Keep writing :)

For 8/14:

• Roughness: 

  • Redo vegetation trained classification for UAS data to catch the sides of the bushes, not just the tops

  • Redo sediment slope curve

• Albedo vs ATI: 

  • Why do we see correlations in the Landsat but not the UAS? (continue)

  • Try creating average pixels (groups) of both albedo and ATI from UAS and plotting those larger pixels against each other. What happens with a new pixel size of 1 m? 5m?

• Sediment data:

  • remove pixels with human-driven change; write descriptions of how the human-driven change influences the values (roads = compacted sediment, exposed rock, low veg = what change relative to similarly low-veg, dusty pixels?) Use numbers

• Incorporate results from fieldwork:

  • plot depths vs dT. Is there a relationship? If so, quantify.

• Write! :)

8/4-6: Fieldwork

For 7/31:

• Roughness: re-check the sediment boundaries - the high values appear to be coming from imprecise placement of flow edge boundaries

• Albedo vs ATI:

  • for those with lower lumps in the x-y plots, check to see what is causing those lumps by using con statements to filter the pixels

  • Do plots for HHA UAS site -- do they also not have a correlation?

  • Albedo = 0.8 appears to be related to a transition in the ATI. Where is albedo <0.8 vs >0.8? What is the spatial relationship or cause?

  • Assuming that the above steps don't change what we're seeing, why do we have a much stronger relationship in the Landsat and essentially no relationship in the UAS data?

  • Table of properties and how they would influence: review draft and update as appropriate. Revise text accordingly.

  • Central question: Why do the different lava morphologies have different ATI values? Break down answer in detail, including trying to separate low albedo from self-shadowing.

• Sediment data:

  • test independent variables for collinearity

  • Use con statements to look at unusual zones in scatterplots to see if those are showing you areas with increased human influence, like the farm

  • For scatterplots of dT vs NDVI, NDBSI, etc. that have no correlation: put independent variables on the x-axes, write descriptions of threshold of influence for each (mostly zero influence, but think about the pivot irrigation farm by HHA -- that area has such extreme NDVI and NDWI that it really does change the dT <and ATI>)

  • Condense the written descriptions of lack of relationships, explaining the lack of correlation and identifying types of conditions (probably mostly human influence) that break the model locally

  • Refer to page 9 of the notebook (referring to CG)

  • Central question: Can we see things in the ATI (or dT) in the sediment areas that tell us how thin the sediment cover is, assuming we're below a given thickness threshold?

• Field points: revise to create sets closer to roads, select more that are up by Craters (think about UAS area and Landsat zone near Kimama dirt road). Suggest which points can be done on which days. Options are August 4-7 (includes driving days)

• Write! :)

For 7/24:

• Roughness: The sediment curve came out very differently despite that it should have barely changed. Trace back through steps to figure out what happened. The curves look different because I initially made the one with the super smooth sediment with the wrong raster (it's smooth and 1m/pixel res instead of 10cm/pixel) 

• Albedo vs ATI:

  • Make Albedo vs ATI plots grouped by insolation and slope for the UAS data  Plots with both positive and negative relationships

  • Write interpretations about why the albedo vs. ATI slopes look different (a'a vs. pahoehoe): Look into specific reasons, not just overall self-shadowing. It's not about just the rasters, but actual differences of a'a vs. pahoehoe properties (example: different thermal conductivities, different shadow shapes like bigger/longer vs smaller, more lichen growth, etc.)

  • Make a list of all the characteristics/properties of a'a and pahoehoe, and write down how each of them would conceptually influence albedo, delta T, specific heat (c) in the ATI calculation (example: does lichen influence albedo?) 

• Sediment data:

  • Make scatter plots of DEM residual rasters, NDVI, NDWI, and NDBSI against delta T for all locations. 

  • Write interpretations for the plots with rasters side by side. - COTM and HHA done

  • Read Sita Karki's thesis to check how she deals with checking the independence of independent variables (she has a section that talks about that)

• Pick locations for digging holes or using a metal rod (maybe Donna's or Sarah's lab) in the field 

For 7/17

• Roughness:

  • UAS data: For the eastern a'a polygon, draw a more conservative line (don't include the lobe). Exclude the northern a'a polygon in frequency curves

• Albedo vs. ATI

  • Write interpretations about why the albedo vs. ATI slopes look different (a'a vs. pahoehoe). 

  • What's the relationship between the temperature difference (delta T) and albedo in the rasters?

• OLS error:

  • Write interpretation of the plots (DEM vs OLS), and based on the interpretation, look in the rasters and search for evidence (example: is there more rocks in the higher elevation areas?)

  • Non-DEM rasters: Write the relationships across locations (word document). Use rasters as figures side by side and create scatter scatter plots 

For 7/10:

• Roughness:

  • UAS data: Double-check all the steps done for the supervised classification (blurry edges). Re-create frequency curves for sediment, a'a, and pahoehoe

• Albedo vs. ATI:

  • Add lines of best fit to the plot (the equation and R2)

  • Use (1 - albedo) for one of the groups and replot with 1 - albedo instead of just albedo.

  • Write the explanation and defend the relationship in the plots. Use some figures (plots) to support your ideas. Compare with what relation the ATI equation says it should be.

  • Talk to Kyleigh or David to check for gaps (tell them to try to shoot my ideas down)

• OLS error:

  • Detrend all sediment DEMs just like the Mauna Loa DEM: original DEM - smooth DEM (try different resolutions, ex:  30 m, 50 m, 100 m, etc.) = residual DEM

  • Make scatter plots: residual DEM  vs. OLS error

  • For non-DEM rasters: Look for relationships across locations and try to isolate patterns (should it not be a linear relationship). Start  with observations within the locations and then compare them to other locations

For 7/3 (zoom):

• Roughness: (T - W)

  • UAS data: use orthophotos to remove vegetation, re-create frequency curves for sediment, a'a, and pahoehoe

    • use supervised classification to find the sage and junipers and cut them out

  • Add to text: for Landsat data, NDVI is at 30 m/pixel but roughness DTM is at 1 m/pixel -- you cannot filter out all of the vegetation shapes from the DTM using the NDVI, so what did you do and what impact does that have on your interpretations? (Try using recent aerial imagery to clip sagebrush and junipers from DTM for Landsat stuff. Or is the original DTM data already filtered for vegetation?) - DEMs used for Landsat datasets are already filtered for vegetation.

• Albedo vs ATI: (lunes)

  • see note sheet from meeting. Use Harker diagram style, plot ATI vs albedo for various combinations of slope and insolation (use narrow ranges to define these groups; if you use a wider range for one of the filter variables, colorize the points in the plot based on that value to see how it effects the ATI vs albedo relationship) Note: for insolation try both with instantaneous and full-day-cumulative versions.

  • Create scatter plots. 

  • Is there a relationship between the albedo and ATI? How is that relationship different from what it's explained in the equation?

• OLS: there appears to be a relationship between local topographic highs and underestimation of ATI. Is this because the sediment is shallow covering a hill? Compare errors to elevation (scatterplot) for each area separately to see if you find a pattern. Do you see any other relationships in the data? At Cerro, are we looking at a veg change crossing the road south of Atomic City? - Yes, there is a change in veg crossing the road

• Tentative plan: field checks in 1st week of August; if conflict arises, let SKN know ASAP to coordinate alternative

For 6/26:

• Roughness: 

  • Check the drone data -- is there a cause for the high slope values in the sediment? (Check for other spatial patterns, too)

  • Put all of the normalized frequency distributions on y-axes that show the differences

• Albedo vs ATI

  • Do manually on ArcGIS (do it separately for a'a vs pahohoe): Divide data into smaller regions with different value ranges for aspect and slope (example: East facing pixels with slopes from 0 to 5 degrees). 

  • Create scatter plots and colorized/categorized them by albedo. 

  • Is there a relationship between the albedo and ATI? How is that relationship different from what it's explained in the equation?

• OLS residual calculation next step: where is it high or low, and why? Consider making the residual raster display in terms of relative error per pixel

For 6/19:

• Roughness

  • fix morphology polygons

  • fix the frequency curve distributions

• Albedo vs ATI

  • Do manually on ArcGIS (do it separately for a'a vs pahohoe): Divide data into smaller regions with different value ranges for aspect and slope (example: East facing pixels with slopes from 0 to 5 degrees). 

  • Create scatter plots and colorized/categorized them by albedo. 

  • Is there a relationship between the albedo and ATI? How is that relationship different from what it's explained in the equation?

• In thesis: write out exact math sequence you actually used (use the equations) - in process (started taking notes of all the math sequences I've done so far and then I'll add them)

• Relating to the Moon:

  • Add insolation to OLS. Use the ATI equation on the rasters and subtract from the actual ATI raster 

For 6/5:

• Roughness:

  • Fix the frequency curve distribution. There must be something wrong in the current process since the curves do not reflect the rasters. Start with Slope before moving to others. 

  • Untangling albedo vs shadowing: You need to use all of the variables used in the ATI calculation (don't skip aspect). Consider dividing the data into smaller sets of similar pixels (narrow range of slope and aspect) for different albedo groups. Do not include sediment pixels.

    • In thesis: write out exact math sequence you actually used (use the equations) - in process (started taking notes of all the math sequences I've done so far and then I'll add them)

• Relating to the Moon (one step at a time)

  • Dig into the sediment data: what can you interpret about sediment thickness based on ATI, roughness, and insolation. What do NDVI, NDBSI, NDWI, etc., tell you about the variation in the sediment zones? How much of the variation can you explain?

    • Relate this to the thermal inertia change estimates from Tyler's code. This includes explaining how things don't correspond, but be detailed based on what both the Earth and Moon models assume/include.

For 5/29:

• Roughness:

  • Work with Kyleigh about the frequency curve distributions, adding RMS Slope (and others?) to the analysis

  • At this scale/resolution, roughness isn't apparently differentiable. How can you separate them? (albedo, but albedo is already used in the ATI calculation... how do you tell which is just from the albedo vs the shadowing?)

• Relating to the Moon

  • Dig into the sediment data: what can you interpret about sediment thickness based on ATI, roughness, and insolation

    • Relate this to the thermal inertia change estimates from Tyler's code

    • Edit regolith model estimate to include thickness of added (smoothed) regolith (Don't do much on this, keep focus higher up)

For 5/22:

• Roughness:

  • What do the curves look like a) with smaller bin sizes, and b) for the other areas?

  • At this scale/resolution, roughness isn't apparently differentiable. How can you separate them? (albedo, but albedo is already used in the ATI calculation... how do you tell which is just from the albedo vs the shadowing?)

  • How do the normalized frequency dist curves look for the high-res topography? How does that compare to the lower-res curves? Can you tell the morphologies apart? Can you relate ATI to roughness using high-res topography? 

• Relating to the Moon

  • Dig into the sediment data: what can you interpret about sediment thickness based on ATI, roughness, and insolation

    • Relate this to the thermal inertia change estimates from Tyler's code

    • Edit regolith model estimate to include thickness of added (smoothed) regolith (Don't do much on this, keep focus higher up)

• Keep writing!

For 5/7:

• ATI: update error table

• ML: calculate roughness on residual (note: have to use original when calculating ATI)

• Roughness:

  • Work with Kyleigh to reproduce her workflow on pahoehoe vs aa patches (RMS Slope?) and compare curve shapes for same distributions

• Relating to the Moon

  • Dig into the sediment data: what can you interpret about sediment thickness based on TI, roughness, and insolation

    • Relate this to the thermal inertia change estimates from Tyler's code

  • Edit regolith model estimate to include thickness of added (smoothed) regolith (Don't do much on this, keep focus higher up)

• Keep writing!

For 5/2:

• ATI: fix overambitious cleaning and update error table

• ML: re-try detrend of DTM using coarser smoothing 

• Roughness:

  • Redo maps, re-plot frequency curves

• Relating to the Moon

  • Dig into the sediment data: what can you interpret about sediment thickness based on TI, roughness, and insolation

    • Relate this to the thermal inertia change estimates from Tyler's code

  • Using UAS data, work out how to create 1 m digital regolith - in process

    • smooth the DEM, cut accumulation over areas with slopes greater than angle of repose for Moon and regolith

• Keep writing :)

For 4/24:

• ATI: 

  • clean up remaining HHA points  there's some that I need to redo

  • Compile error into summary table 

• ML: redo detrending using raster subtraction method

• Use topographic roughness index on all of the DEM areas and check for distributions 

  • plot frequency curve distributions for different morphologies

• Relating to the Moon

  • Dig into the sediment data: what can you interpret about sediment thickness based on TI, roughness, and insolation

    • Relate this to the thermal inertia change estimates from Tyler's code

  • Using UAS data, work out how to create 1 m digital regolith - in process

    • smooth the DEM, cut accumulation over areas with slopes greater than angle of repose for Moon and regolith

• Keep writing

For 4/18:

• ATI

  • finish HHA ATI vs ATI cleanup, renormalizing  cleaning up some more

  • ATI error for each zone and for overall

• Step through process:

  • N Robbers

  • S Robbers

  • Mauna Loa (note: need to detrend the general slopes)

  • SP Crater

• Try another roughness metric (keep using 3x3), plot curves of frequency distributions for different morphologies - currently working on this

• Relating to the Moon

  • Dig into the sediment data: what can you interpret about sediment thickness based on TI, roughness, and insolation

    • Relate this to the thermal inertia change estimates from Tyler's code

  • Using UAS data, work out how to create 1 m digital regolith - in process

    • smooth the DEM, cut accumulation over areas with slopes greater than angle of repose for Moon and regolith

• Keep writing (Aiming for complete draft to SKN 6/2)

For 4/4 & 4/11:

• TI

  • finish review of wonky points in TI vs TI plots, removing points when appropriate

  • renormalize TI outputs after cloud/noise removals

  • Finish expanding no-rain datasets

  • Quantify the anticipated variation between days (standard error) -checking some divisions by zero issues

• Morphology

  • Cedar Butte is ~400ka and not basalt, so need to separate that for comparison

  • Get polygons from N and S Robbers

  • Check availability of data for Mauna Loa and Flagstaff (SP Crater) areas

  • Make figures illustrating how the roughness and insolation relate to one another, how they relate to TI - remember to consider whether an individual plot should use cumulative insolation to time X or total insolation for the day, also what your pixel sizes are

• Relating to the Moon

  • Dig into the sediment data: what can you interpret about sediment thickness based on TI, roughness, and insolation

    • Relate this to the thermal inertia change estimates from Tyler's code

  • Using UAS data, work out how to create 1 m digital regolith

    • smooth the DEM, cut accumulation over areas with slopes greater than angle of repose for Moon and regolith

• Slides for Colloquium talk 4/9: slides due 3/31

• Read LPSC abstract SKN sent, check the citations (looking for info about lunar cold spots for background and discussion)

For 3/21:

• TI: 

  • Use SKN's approach to cut the remaining clouds

  • Replot scatterplots with cloud wings removed

  • Rebuild HHA dataset

  • Quantify the anticipated variation between days

• Morphology & insolation

  • Redo roughness and insolation average calculations by morphology type

    • start with raster of interest

    • multiply by 1000 (or whatever appropriate)

    • convert to integer/build attribute table

    • calculate average and standard deviation

    • divide values by the previous multiplier

  • Make figures illustrating how the roughness and insolation relate to one another, how they relate to TI - the figures are not making a lot of sense

• Relating to the Moon

  • Dig into the sediment data: what can you interpret about sediment thickness based on TI, roughness, and insolation

    • Relate this to the thermal inertia change estimates from Tyler's code

  • Using UAS data, work out how to create 1 m digital regolith

    • smooth the DEM, cut accumulation over areas with slopes greater than angle of repose for Moon and regolith

• Writing - working on the methods section of Ch 3

For 3/7:

• TI:

  • finish removing clouds and reprocesssing

  • reprocess, from scratch, the two noisy TI images

  • Replot scatterplots and report slope and intercept for each

  • HHA: issues with rain associated with most dates. Investigate alternatives.

• HHA:

  • Sort out the data vs plots situation

• Morphology patches: 

  • Why is Cerro sed 100x rougher than COTM sed and 10x rougher than HHA?

  • Why is Cerro lava 10x rougher than COTM and HHA?

  • Redo roughness calculations, not using random number sampling, but using clip and data statistics (use a multiplier to temporarily increase values ahead of integer conversion to build attribute table)

• Meet with Donna about UAS values

For 2/28:

• TI:

  • check N Robbers values for being high, confirm that polygons are the same for clip

  • check HHA upper values for being low

  •  X,Y plots: dig into these. What is going on with the remaining "wings" and bad correlations? Need specific explanations. 

    • Re-do threshold for weirdo points with angled linear relationships (start with COTM, July 2023 sets)

• HHA:

  • Sort out the data vs plots situation

• Scatterplots comparing data types: plot in R, Matlab, or something else - will do them this weekend on Matlab

• Morphology patches: 

  • Why is Cerro sed 100x rougher than COTM sed and 10x rougher than HHA?

  • Why is Cerro lava 10x rougher than COTM and HHA?

  • Redo roughness calculations, not using random number sampling, but using clip and data statistics (use a multiplier to temporarily increase values ahead of integer conversion to build attribute table)

• Figure out why UAS TI is ~2x Landsat TI - could be due to spatial resolution differences, different times of data collection, sensor callibration differences? - Donna wants to take a look at them. We'll meet this Friday at 3:30pm

• Poster draft

For 2/21:

• TI: 

  • Check math on Sept 25 COTM, any others that have unusual ranges (Check N Robbers for values being high, check HHA for upper values being low) 

  • update notes to explain removed datasets

  • Need 2 more sets for N Robbers - have 1 (I'll ask Carrie or Donna how to deal with NoData values - everything I've troubleshoot so far hasn't work)

  • x-y plots: 

    • confirm that all plots in the powerpoint are from the updated datasets (is the one COTM with the "wing" and old one with clouds?)

    • make sure that all of the points are represented (where are the 0s?)

    • What does it mean that different plots have different slopes? - could be due to temporal differences? 

    • Re-do threshold for weirdo points with angled linear relationships (start with COTM, July 2023 sets)

• HHA:

  • Sort out the data vs plots situation

• Scatterplots comparing data types: plot in R, Matlab, or something else - will do them this weekend on Matlab

• Redo HHA polygon for morphology

• Check the morphology patches. Why don't the roughness values make sense? Check Cerro ranges (or is that the one that's right?). Redo numbers with improved HHA polygons 

• Figure out why UAS TI is ~2x Landsat TI - could be due to spatial resolution differences, different times of data collection, sensor callibration differences?

For 2/4:

• For normalized TI

  • Mask clouds from night images using threshold of ~282 (check values)

  • Check COTM July 22 and Sept 25 - values seem too high compared to rest of the COTM set - clouds (July 22 has them on top of lava and Sept 25 has them all over the sediment)

  • x-y plots: what is the cause of the noisy edges? Check all of them for 0 to 1 on both - these are numerically required if the math was done correctly. 

  • update x-y plots based on additional cloud masking 

• HHA lava tubes: check threshold values to confirm/reject our thoughts about vegetation and high cumulative insolation values

  • if it's the veg shadows, use NDVI to mask veg plus a buffer

  • do dual-mask to check for the locations/causes of the low diffT values at mid and high cumulative insolation (notes on PP)

  • What can we interpret about the x-y plots as a result? 

• Update TI and other calculations using night L2

• Build scatterplots between data types at pixels, moving descriptions from qualitative to quantitative - in process, I'm having problems opening the files because they are too big

• Redo polygons for different morphologies. Be inclusive.

• Do TI for UAS data

For 1/28:

• For normalized TI

  • finish clipping clouds - what I've been doing it's not working; looking for other options

  • clip irrigated areas, crops (use NDVI) - for HHA mostly

  • Re-check COTM_1_sep_24 pair - low TI values (check if there was a multiple of 3 problem)

  • update x-y plots

    • Cerro: check rasters for the cause of the low-value spike in y-values  - It's the clouds

    • HHA: is the odd lump associated with the crops? (first graph) - yes, it disappeared after clipping the crops

    • Finish COTM updates (if we lost 2 dates to rain, replace them) 

• HHA lava tubes: 

  • try same process as before, but with raw (not normalized) T difference

  • For plots (do both, but these are the #s for the normalized set):

    • change symbology on raster to highlight all pixels with cumulative insolation >4 and >4.3

    • Change symbology on raster to highlight all pixels with normalized diffT < 0.2

    • What can we interpret about the x-y plots as a result? 

• Moar day-night pairs - got 6, did 4 TI calculations. There's one dataset per location that can't be used, so I got to get more

• Meet with Carrie to discuss output of night L2 correction (ENVI Thermal Atmospheric Correction tool)

  • finish night L2 corrections for all - corrections are done for all the raw night imagery; in process of finishing redoing the TI calculations 

  • Build scatterplots between data types at pixels, moving descriptions from qualitative to quantitative - in process

• Check the polygons used for morphology-based groupings. What's going on with those changes?  It was the location of the polygons

• Meet with Donna about UAS thermal conversion to K

For 1/21:

• For normalized TI

  • clip out clouds - which one?

  • check raw data to see if the noisy ones get their noise from the raw data - noise is from the raw data

  • for HHA with the strange x-y distribution: look at the normalized images to figure out where the change is happening  - SE portion, maybe rain events?

  • COTM results with lower sediment values: do these correlate with prior rain?  - they correlate with prior rain

  • Based on possible revisions above: compile complete sets of x-y pixel relationships (export to make a single image group for each location) 

• Wet COTM date(s): put in Ch4 to discuss the influence of the water on the calculated TI

• For HHA lava tubes:

  • Subtract L2 night from L2 day, normalize, plot XY data vs insolation values for the Day image (cumulative to that time -and- snapshot of that time)

• Snag and process more day-night pairs

  • Talk to Carrie about how to most efficiently grab useful data pairs and about revising data management/organization

• Do atmospheric corrections for nights - in process

  • update summary table

• Build scatterplots between data types at pixels, moving descriptions from qualitative to quantitative - in process

• extract characteristic values from different roughness areas (aa, pahoehoe, sediment) and calculate % of TI change within any image as it relates to those three categories - same patch location across image groups, avoiding intermediate lava types  (like rubbly pahoehoe) and sediment with rocks

• Email DD to set up a meeting to discuss the UAS data (what's up with the scale of the "thermal" band?)

  • edit file accordingly and process - trying to figure out raw temperature unit issue

For 1/7:

• Explaining changes in TI

  • renormalize values to 0-1 for each image and compare (consider plotting two rasters against each other in xy space, etc.)

• Check diurnal thermal model results - in process

  • adjust for insolation on per-pixel basis (remember to match time exposure to data time)

• Snag and process more day-night pairs

• Email Carrie for atmospheric correction guidance

• Do atmospheric corrections for nights

  • update summary table

• Build scatterplots between data types at pixels, moving descriptions from qualitative to quantitative

• UAS data: fix; export to Arc; process 

• Write LPSC abstract, send to SKN by noon on 1/3

For 12/23:

• Finish class requirements

• Finish populating TI and weather table

  • What can explain the changes?

• Check skylights in low TI areas south of confirmed sites (no skylights)

• Make bullet points of how to estimate HHA roof thicknesses (varies spatially), send to SKN (in next few days)

  • Do the estimates for HHA - sort of

• Snag and process more day-night pairs

• Need to use L2 atmospheric corrections

  • look up process for night imagery corrections

  • replace values in summary table

• Combine data into master table

• Build scatterplots between data types at pixels, moving descriptions from qualitative to quantitative

• UAS data: fix; export to Arc; process - stand by, need field notes

For 12/12:

• How does the minimum/maximum/median TI value change? (add to table)

• Re-check skylights using insolation, hill shade, viz, and TI

• Estimate HHA roof thicknesses (varies spatially)

• COTM insolation issue: try splitting the file into 2 parts and running separately (then merge after); reminder: more datasets with same dates 

• Evaluate level 1 vs 2 data in terms of Kelvin, relate to weather conditions 

• Build scatterplots between data types at pixels, moving descriptions from qualitative to quantitative

• Email Donna about UAS ground control point issue

  • fix; export to Arc; process

For 12/5:

• Moar dates - got three more

• Compile table to compare/contrast sites across dates

  • How does the minimum/maximum/median value change?

  • What was the min/max air temp that day? Humidity? Min/max solar insolation?

• Use insolation to search for likely skylights at HHA

• What is the instrument accuracy for Landsat thermal? - the thermal infrared sensor has an accuracy of 0.2K 

• Replicate datasets using level 2 data - subtracted the raster to get the difference

• Build scatterplots between data types at pixels, moving descriptions from qualitative to quantitative

• Process UAS data - almost done

For 11/21:

• Keep processing additional dates, get more dates for different temperatures and humidities - 2 more done

• Why is Table Legs Butte showing a shadow-related TI anomaly?

• Check the COTM multiplier-of-three issue

• HHA: is the TI anomaly related to the tubes? (Mark skylights and compare)

• Double check atmospheric humidity adjustment in Landsat data, HHA UAS data

• Build scatterplots between data types at pixels, moving descriptions from qualitative to quantitative

• Process UAS data - Donna started to process it to check how it looks. We're meeting on Friday at 3:30 pm to talk about it.

For 11/14:

• Snag/process more Landsat dates for same locations

• Add text about TI vs roughness

  • add figures to text

  • Send to SKN before next meeting

• Check issues with masking for NDVI, clouds

• Fly UAS

For 11/7:

• Redo HHA resampled sets

• Redo the comparisons and update your text accordingly (rough draft)

• Mask by NDVI for Landsat

• Snag/process more Landsat dates for same locations

• Reach out to DD

For 11/4:

• Check in with revised maps

For 10/31:

• Keep pressing on fixes

For 10/24:

• Go back to equations and make sure that you're using the input files in the right units (check input rasters and other numbers)

  • Fix TI calculations: HHA and Landsat

• Redo HHA resampled sets

• Redo the comparisons and update your text accordingly

For 10/17:

• Solve mystery of rounding in TI from HHA

  • Update graphs to make sure independent variable is on x-axis, axes are labeled correctly (make graphs thesis-ready)

  • Update interpretations for each plot and overall interpretation text based on our discussion and your subsequent consideration. Write text in style of the thesis.

• Run HHA dataset with HHA resampled to 2 m/pixel and 10 m/pixel, compare results to 1 m/pixel

• Calculate TI fo other good day-night pair 

  • using both sets, write the interpretations from below - in process of making them pretty

• Make detailed work block schedule that covers RA and class tasks

For 10/10:

• Solve mystery of rounding in TI from HHA

• Update graphs to make sure independent variable is on x-axis, axes are labeled correctly (make graphs thesis-ready)

• Update interpretations for each plot and overall interpretation text based on our discussion and your subsequent consideration. Write text in style of the thesis.

• Run HHA dataset with HHA resampled to 1 m/pixel, compare results to above (it was already 1 m/pixel)

• Rerun ATI/TI on smaller areas with the good end of DEM coverage

• Rerun ATI/TI on whole area, but without clouds (stick to one pair for now)

  • How do ATI & TI change in the areas with more sediment cover? How does it change with albedo (as proxy for composition/texture/etc.)? How is this the same or different from HHA results?

    • write text for thesis - have stuff written down but is not thesis-ready

• Hold for now: add digital regolith

For 10/3:

• Make scatter plots of pixel values looking for relationships (may want to remove the shadowed pixels in the tubes)

  • Describe the relationships (text for thesis)

• Satellite

  • calculate ATI & TI - done for one pair (covering most of the ESRP)

  • How do ATI & TI change in the areas with more sediment cover? How does it change with albedo?

    • write text for thesis

• Add digital regolith to HHA

For 9/26:

• Go back to ATI and TI calculations and re-check them

  • What does it mean for a value to be negative?

  • Where are the negative values in space?

    • How do the negative values relate to the features?

  • Going back to the original day/night corrected images: are the night pixels all colder than their corresponding day pixels?

• Satellite:

  • download visible wavelengths

  • create albedo maps

  • Calculate ATI

  • How does ATI change in the areas with more sediment cover? How does it change with albedo?

• Not for now, holding for later: Add digital regolith to HHA

For 9/19:

• Rasters: remember to use multiplier to keep values when going in and out of integer format

  • Multiply by 100,000 before classification; divide by 100,000 after classification  (maybe?)

  • Write interpretation

• Finish coordinate review for The Breaks

  • emailed BZ for additional coordinates

• Landsat

  • double-check air temperature on paired images (get rid of any wildly different stuff)

  • Calculate ATI for paired images

  • How does ATI change in the areas with more sediment cover? How does it change with albedo?

• Ch2: add text about Landsat stuff

• Not for now, holding for later: Add digital regolith to HHA

For 9/12:

• Try out for the Olympics

• See if mofongo is available on campus

• Rasters: remember to use multiplier to keep values when going in and out of integer format

  • Write interpretation

• Finish coordinate review for The Breaks

• Grab 5 day-night pairs over swaths with varying sediment cover

  • look up weather conditions from those dates to decide whether we can keep the pair

  • calculate ATI for each surviving set

  • How does ATI change in the areas with more sediment cover? How does it change with albedo?

For 8/29:

• Fix the rasters (Con or Reclassify in Spatial Analyst) - tools made it worse, I used raster calculator to constrain the values

  • Write interpretation

• Finish coordinates associated with GoPro footage - The Breaks

• Download paired day-night thermal data

• Check date/time of Landsat thermal data

• Compile thermal data for variously aged lava flows from Landsat (?), evaluate the relationship between ATI and/or daytime temp with sediment cover (review Sita Karki thesis)

• Reply to Donna about UAS targets

For 8/22:

• Band 3 has values that cannot be real: fix

• Check publications for reasonable ATI ranges (Band 3)

• Write interpretation

• Organize GoPro footage, Gaia logs, and coordinate lists by traverse

  • Don't review the Gaia logs

  • Watch the footage and correct coordinates as best as possible - working my way through

• Start conversation with Donna about possible flight dates after the drone is back online

• Compile thermal and viz data for variously aged lava flows from Landsat (?), evaluate the relationship between ATI and/or daytime temp with sediment cover (review Sita Karki thesis)

For 7/31:

• After you have the TI thing sorted out: Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots (https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/image-scatter-plot.htm) - need to use composite tool to create multiband raster

  • (check for outliers, look at symbology scaling)

  • Write interpretation

• Finish revisions to maps

  • Print map books on Monday

• Pack for the field

For 7/19:

• Do ARI map in regular Arc - made a .tif but I'm trying to figure out why it is not showing up when I activate the layer

  • plot insolation vs thermal measurement on per-pixel basis. What is the relationship? 

  • After you have the TI thing sorted out: Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots (https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/image-scatter-plot.htm) - rasters only have one band

    • Write interpretation 

• IDEAS maps: send as printable atlas to SKN (3 sets)

• Add section numbering system to thesis draft sections

• Review thesis formatting requirements and start following them now

• If time: work on expanding Ch2

• Fix fall schedule

For 7/11:

• Implement topography algorithm to create ARI map (Finish by Monday COB)

  • plot insolation vs thermal measurement on per-pixel basis. What is the relationship? 

  • After you have the TI thing sorted out: Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots (https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/image-scatter-plot.htm) - rasters only have one band

    • Write interpretation 

• Finish updating IDEAS maps with alphanumeric values (Finish by Monday COB)

• Update Ch2 (moving stuff around, adding list for updating directly to document)

For 7/5: 

• For Ciazela et al.: go through the math and write out a plan to adopt it in Arc (workflow or code)

  • implement to create ATI map

• Send SKN day flight insolation summative from dawn to flight; compare with snapshot insolation calculated at time of flight  uploaded in shared drive

• plot insolation vs thermal measurement on per-pixel basis. What is the relationship? 

• After you have the TI thing sorted out: Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots (https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/image-scatter-plot.htm) - rasters only have one band

  • Write interpretation 

• Finish first draft of Ch1

• Ch2: start a list of intended revisions/additions

• Update IDEAS maps with alphanumeric values - all uploaded except for COTM because I messed up

For 6/20:

• Read/summarize thermal inertia papers for Mars and Earth

  • work on adapting their approach for Earth -or- keep searching

• Day flight insolation: summative from dawn until flight

• plot insolation vs thermal measurement on per-pixel basis. What is the relationship?

• After you have the TI thing sorted out: Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots (https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/image-scatter-plot.htm) - rasters only have one band

  • Write interpretation 

• Finish carving prospectus up into thesis chapters

For 6/6:

• Reply to Erika

• Finish N COTM inset-style guide

• Finish slope maps

• Check equations in Scheidt et al. (2010)

  • use for TI calc

  • If still an insolation echo, look for papers that adapt Scheidt method for variable slope/aspect

• Finish raster images: consider the color ramps and adjusting as needed to avoid swamping the signal on a few extreme pixel values: try using percentile symbology

• Make an insolation map for the same time of day as the daytime thermal flight

  • plot insolation vs thermal measurement on per-pixel basis. What is the relationship?

• After you have the TI thing sorted out: Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots (https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/image-scatter-plot.htm) - rasters only have one band

  • Write interpretation 

For 5/30:

• Finish: each image set, include inset-style guide - in process, doing slope map and waiting for feedback

• Email Brent/Erika/Donna for image feedback

• Redo thermal inertia calc to determine whether process was correct before

  • if process seems fine, check insolation and daytime thermal image -- appears to be an insolation time-of-day artifact

• Raster images: consider the color ramps and adjusting as needed to avoid swamping the signal on a few extreme pixel values

• start with visual inspection of similar/different patterns

  • Does the insolation map used make a big difference?

• Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots (https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/image-scatter-plot.htm) - rasters only have one band

  • Write interpretation 

• Create a shared Drive with SKN for the thesis document

  • Make a subfolder for each chapter

  • put in copies of prospectus, relevant figures

  • Start an outline/draft in each chapter folder

For 5/22:

• Send close/med/wide view imagery sets to Erika and Brent, hopefully via Erika's OneDrive folder

  • For each set, include inset-style guide - in process

• Add letters/numbers to grids -- make sure that lines keep their same names between views - in process 

• Put thermal inertia map, insolation map, and roughness map together as layers within GIS

  • start with visual inspection of similar/different patterns

    • Does the insolation map used make a big difference?

  • Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots - did something in arcpro, not sure if it's correct

    • Write interpretation - started it with the visual comparison; the graphs interpretation needs to be added

• Lunar thermal model: increase number of time steps (decrease duration of step)

  • for full sun: depth to freezing? (what is freezing/sublimating temp for water on moon?) - Sublimation rate for ice on the moon (Andreas, 2007), https://nssdc.gsfc.nasa.gov/planetary/ice/ice_moon.html

  • For 75%, 50%, 25%, 1%?

  • Write summary/interpretation

For 5/9:

• Finish map gridlines

• Check on bottom (deep) temperature used in thermal code (lower boundary?) and how the rock and regolith are handled

• Play with lunar thermal model to get stable output

  • for full sun: depth to freezing? (what is freezing/sublimating temp for water on moon?)

  • For 75%, 50%, 25%, 1%?

• Make thermal inertia map using the day/night thermal images

• <Hold: finish thermal inertia map questions below>

For 5/2:

• Finish prospectus final draft

• Maps (key thing: grids MUST stay consistent across zooms; Priority)

  • Bear Trap: make much wider view option to see lava flow context

  • COTM Caves: make a zoomed in version on the main set of caves; check Weng et al. for other cave coordinates; add maps for Needles, Last Chance, etc.

  • Cerro Grande: make series of zoomed-in maps; suggest targets of high interest

  • Grand View: zoom out

  • HHA: zoom in

  • The Breaks: zoom in on E-W chain and N-S chain of craters

  • N Robbers: zoom in (series)

  • Split: Zoom in and out

  • Northern COTM: make series

• Remove vegetation, fill holes, and re-run roughness (3x3 and 7x7)

• Check on bottom (deep) temperature used in thermal code (lower boundary?) and how the rock and regolith are handled

• Play with lunar thermal model to get stable output

  • for full sun: depth to freezing? (what is freezing/sublimating temp for water on moon?)

  • For 75%, 50%, 25%, 1%?

• Make thermal inertia map using the day/night thermal images (did something, not sure if it's right)

• <Hold: finish thermal inertia map questions below>

For 4/25:

• Geostats final project presentation and MATLAB project

• 6603 prospectus presentation

• Work on prospectus revisions

• Export map copies as pdfs and upload to Floe (server)

  • Make zoomed sections, too (Mud Lake and N COTM splits, in particular) - Mud Lake is done

• Remove vegetation, fill holes, and re-run roughness (3x3 and 7x7)

• Check on bottom (deep) temperature used in thermal code (lower boundary?) and how the rock and regolith are handled

• Play with lunar thermal model to get stable output

  • for full sun: depth to freezing? (what is freezing temp for water on moon?)

  • For 75%, 50%, 25%, 1%?

• Make thermal inertia map using the day/night thermal images

• <Hold: finish thermal inertia map questions below>

For 4/18:

• Clip NAIP images, overlay with 50 x 50 m grid, and upload to server by Monday morning

• Combine caves imagery/info into a single file; email a copy to Brent

• Roughness via 3x3 and 7x7 

  • check on whether veg was removed, whether holes were filled

  • convert to multi-color ramp

• Run thermal code (single point)

• Make thermal inertia map using the day/night thermal images 

• Put thermal inertia map, insolation map, and roughness map together as layers within GIS

  • start with visual inspection of similar/different patterns

    • Does the insolation map used make a big difference?

  • Export per-pixel values of insolation, thermal inertia, and roughness. Plot them as XY scatterplots

• <SKN: feedback on prospectus>

For 4/11:

• Combine/trim NAIP images to target features of interest - in process

• Finish last documentation for caves imagery

• Roughness rasters; compile outputs into a ppt

• replace all instances of cmd_inputs

  • run thermal code

• Add grids to NAIP images (50 x 50 m - needs to be checked) - in process

• Prospectus draft!

For 4/4:

• Combine/trim NAIP images to target features of interest

• Add documentation for caves imagery

• Roughness rasters; compile outputs into a ppt

• run thermal code

• Add grids to NAIP images (50 x 50 m - needs to be checked)

For 3/28:

• Check remaining NAIP groups

• See if less hazy coverage in another year

• Clean up NAIP folders

  • in each area, add an explanation file that includes an outline of where the NAIP images cover (use target polygons) and citation information

• Keep running roughness rasters

For 3/14:

• Finish revising poster and give awesomesauce presentation

• continue to download and organize NAIP imagery for field areas (floe) 

• Calculate roughness rasters

• Update python code for inputs

• Run thermal code

• Meet with CoSE IT for compiler installation (schedule visit this week for next week)

For 3/7:

• Why those scales (0.1, 0.5, 1, and 2 m)?

• Revise Methods section

• Calculate roughness rasters

• Contact geohelp@isu.edu for compiler fix (fortran90 for RMS and AreaRatio)  - they don't know a lot of fortran

• Run thermal code 

• Work with Brooks to install rugosity calculator (Brooks is available to do it today-Thursday)

• download and organize NAIP imagery for field areas (floe) - working on it

• Set up VPN

For 2/29:

• Get rugosity tool installed (talk to Donna/Brooks) - talked with Donna and she told me Brooks can get it installed by next week

  • calculate roughness rasters

• Get help from a PC user on fixing the matplotlib installation/path/whatever (working with Kyleigh on this; matplotlib is installed but now is giving me permission error)

• Run thermal code

  • After running code, return to roughness and insolation vs TI correlation

• Methods section to SKN by 8 pm Saturday (don't forget to include thermal stuff)

For 2/22:

• Calculate roughness rasters (try using rugosity tool in Arc; will need to install)

• Ask Kyleigh about how she installed her compiler(s)

• Use Tyler's thesis as a guide to reading the TI code; add comments to the code (almost done)

  • depending on how this goes, try running the code

    • After running code, return to roughness and insolation vs TI correlation

• Write and submit abstract for ISU Research Symposium (due 2/21)

For 2/15:

• Put insolation rasters on the same color ramp

• Extend cumulative to 24 hours and put on same color ramp

• Re-load roughness rasters

• Use Tyler's thesis as a guide to reading the TI code; add comments to the code

  • depending on how this goes, try running the code

    • After running code, return to roughness and insolation vs TI correlation

• Add content to TI paper summary

• Update Background, email SKN when re-uploaded

For 2/8:

• Take a screengrab of the insolation error message

• put instantaneous insolation images into a shared Google folder

• run cumulative insolation examples and add to folder

• Calculate thermal inertia (TI) of HHA dataset

• organize roughness rasters alongside thermal inertia and insolation rasters

• Correlate roughness - TI and insolation - TI

• Read/summarize a TI or other temperature modeling paper cited in Paladino Ch 5

For 2/1:

• Re-run insolation using the newly updated tool

• Identify the contribution of local lava roughness to thermal inertia or insolation in the HHA dataset

• Revise methodology plan to describe how you could use a 1D heat model like from Paladino to estimate regolith thickness. (Assume flat lava surface and a clean/dry regolith.) (Concentrate on Paladino)

For 1/25:

• Keep going with insolation maps (add the summation outputs)

• Put together a methodology plan (bullet points is fine) to identify the contribution of local lava roughness to thermal inertia or insolation in the HHA dataset

• Put together a methodology plan to describe how you could use a 1D heat model like from Paladino to estimate regolith thickness. (Assume flat lava surface and a clean/dry regolith.)

• Chat with Kyleigh

• Do first draft of problem statement

For 1/18:

• Revise Paladino summary to focus on what did(not) work and why

• Revisit Karki thesis and make a list of questions

• Do HHA insolation maps for 10 am, 2 pm, and 8 pm on July 1 (are you getting an instantaneous output or summation output?)

• Read/summarize lunar PSR paper

For 12/18 (zoom):

•  Read/summarize Paladino dissertation chapter about lava tubes and thermal inertia

• Meet with Kyleigh

• Calculate time-specific insolation on HHA data

• Read/summarize Karki thesis

For 12/5:

•  Read/summarize Paladino dissertation chapter about lava tubes and thermal inertia

• Meet with Kyleigh

• Calculate time-specific insolation on HHA data

• Read/summarize Karki thesis

For 11/28:

• Read/summarize Lopes-Gautier

• Try to identify source of plot error

• review proposal

• Try to meet with Kyleigh about what she's been working on

For 11/7 (email update):

• Focus on UAS stuff

• Scan book (send to SKN) and return it to library (if time, start reading)

• Plot U vs MgO and U vs SiO2; look to see if anything else is worth plotting (concentrate on trace)

For 10/31:

• ILL request for Lopes-Gautier, R. M. (2022). Extraterrestrial lava flows. Active Lavas, 107-144.

• Read/summarize Cao and Cai (2018)

• Review geochem maps: label key features, check scale bar, reduce number of breaks in scale

For 10/24:

• Read/summarize Theilig and Greeley (1986)

• With Geochem file: pick 3-4 elements and make a heat map of their distribution (ignore actual contacts, etc., and just look for major trends)

For 10/17:

• Read/summarize Magma Composition chapter in Encyc. of Volc.

• Read/summarize Greeley (1982)

• Revise planetary section of Hughes summary

For 10/10:

• Read/summarize Magma Composition chapter in Encyc. of Volc.

• Read/summarize Hughes et al. (2020)

• (for next week's readings: Greeley (1982)?)

• Study for Volc midterm

For 10/3:

• Read/summarize Xu et al. (2020), Warren (1985)

• Snag gear for field trip

For 9/26 (skipping Seminar week):

• Look for paper on lunar highlands

• Condense last week's summaries into <300 words each

For 9/12:

• Read/Summarize: Spudis (2000) and Kilburn (2000) (see big book)

• More social things

• Email Kyleigh to schedule time to talk about existing datasets; compare to the proposed flight polygons

For 9/5:

• Read/Summarize: Cai and Fa (2020), Neish et al. (2017); add text about project relevance

• Do another social thing... in addition to the department cookout

• Join IDEAS telecon

For 8/29:

• Populate upper part of website (ex. photos, simple project summary, mid- to long-term goals, etc.)

• Read IDEAS proposal, write ~1 paragraph summary (include any questions, critiques, etc.)

• Read Hester's thesis and write summary

• Do something fun/social unrelated to Geology

• {SKN: bring bike to campus; send Hester's thesis and proposal}