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 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}