SPACE-GEOLOGY

Report

General Introduction

Exercise I: Deep-time Earth Reconstruction

Context and Objectives

Explain here the overall scope of this exercise, especially in the context of applying GIS tools to geology.

Methodology

What tools and libraries did you use ? To what purpose ?

Results

Breakdown your results (screenshots and code you modified or added) for the exercises’s three parts.

Part I: Reconstructing Earth’s Past – From a Snapshot to Deep Time

Part II: How Fast Was Earth’s Engine Running?

Part III: Palaeogeography Meets Palaeoclimatology

Discussion

Refer to the “Points for Discussion” in each part of the exercise I. You may answer with text ( a few paragraphs) and/or by adding references to scientific articles from the literature.

Part I: Reconstructing Earth’s Past – From a Snapshot to Deep Time

  • When we loaded the data and metadata from the GeoServer, we found a transform attribute. What does this attribute describe ?
  • What are the pros and cons of using WCS requests, compared with traditional ways, to access data ?
  • We got familiar with the masking function to discriminate land and ocean. Could this mask be used to generate new statistics ? Which ones ?
  • What is the use of these statistics in understanding the evolving palaeogeography throughout the Phanerozoic ?

Part II: How Fast Was Earth’s Engine Running?

  • What is the rationale behind writing functions to automate workflows ?
  • What does the histograms of 0Ma versus 100Ma tell us about the rate of oceanic seafloor production ?
  • Compare the properties of the data handling structures we usedinthis exercise: xr.DataArray, xr.DataSet, and pd.DataFrame. How are these complementary to handle geospatial layers and key stats ? Are you awayre about other structures ?
  • Using your knowledge about the supercontinent cycles, and the timing for formation/break-up of these supercontinents, do you see these cycles linked with the data we have ?

Part III: Palaeogeography Meets Palaeoclimatology

  • What do you think is the role of palaeogeography for climate modelling of the past ?
  • What are the advantages of having NetCDF file formats versus GeoTiFF ?
  • Why aren’t NetCDF files more used in the traditional geospatial world? Why is GeoTiFF still dominant ?
  • How could the Köppen-Geiger maps be used to understand deep-time evolution of the Earth in future studies ?
  • Do you see risks and/or limitations about combining maps that have vers different resolutions ?

Perspectives

Add a brief conclusion about limitations of the tools we used in this exercise.

How does this exercise compared to the traditional “Dekstop”-based workflows you are used to, for instance with QGIS and/or ArcGIS ?

Exercise II: Landslide Susceptibility Analysis

Context and Objectives

Explain here the overall scope of this exercise, especially in the context of applying GIS tools to geology.

Methodology

What tools and libraries did you use ? To what purpose ?

Results

Breakdown your results (screenshots and code you modified or added).

Discussion

Refer to the “Points for Discussion”. You may answer with text ( a few paragraphs) and/or by adding references to scientific articles from the literature.

  • The Threshold Assumption: We assume the mean slope of existing instabilities represents the internal friction angle (\(\phi\)). How valid is this assumption across different lithological units?
  • Data Resolution: How does the 25m pixel size affect the precision of the slope calculation and the resulting hazard boundaries?
  • Model Limitations: This model relies solely on slope and lithology. How would you integrate dynamic triggers (e.g., precipitation data, seismic history) into this Python workflow?
  • List your results:
    • What proportion (in %) of the area of the favorable lithologies is currently instable ? Provide all the necessary numbers used for the calculation.
    • What proportion (in %) of the zones situated on favorable lithologies could be more likely destabilized in the future? Provide all the necessary numbers used for the calculation.
    • What proportion (in %) of the study area is affected by instabilities ? Provide all the necessary numbers used for the calculation.
    • What proportion (in %) of the area of the existing instabilities is susceptible to new instabilities. Provide all the necessary numbers used for the calculation.
    • What proportion (in %) of the study area is still susceptible to instabilities? Provide all the necessary numbers used for the calculation.

Perspectives

Add a brief conclusion about limitations of the tools we used in this exercise.

How does this exercise compared to the traditional “Dekstop”-based workflows you are used to, for instance with QGIS and/or ArcGIS

General Conclusion

Did this course provide a satisfactory introduction to geospatial analysis with Python applied to geology ?

Did you have any experience coding with Python before ?

Are you likely to continue working with Python in the future ? If yes, why ? I no, why not ?

Suggest improvements to this course.