RGI version
RGI v7.0
Describe the issue
Reported by Owen King:
"RGI7 was used to measure glacier surface elevation change from 2000 onwards, alongside the elevation change estimates of Hugonnet et al. (2021). A subset of RGI7 was extracted where RGI7 and RGI6 polygons intersected. This was done to remove rock glaciers, perennial snowfields and other ice-debris landforms included in RGI7 in GTN-G 17. These features display little change in the elevation change grids of Hugonnet et al. (2021) and are so abundant (several thousand) that they bias catchment level elevation change signals."
Detective work that followed
Here are the outlines submission IDs available in GLIMS when RGI reg17 was generated:
- 700 is the Argentina glacier inventory. 708 is an update of 75 of its outlines, for unclear reasons (the outlines are still in 700)
- 730 is the Chilean glacier inventory
Both 700/708 and 730 have the same issues (rock glaciers) as for RGI16. Furthermore, the Argentina / Chile border makes both inventories pretty much useless as is (both inventories stop at the border). This situation is why submission 764 was created, a merge work done by Frank Paul and Philip Rastner. It's 764 that was used for the RGI, as single submission for all of RGI reg17.
I noted back in the day (1 Jul 2022) that all glacier classes were lost in the merger (primeclass attribute, containing categories for glacieret, rock glacier, etc.), to which Frank replied:
"Yes, unfortunately the topologic changes resulted in a more or less complete loss of all attribute information. With a spatial join it was possible to recover the satellite image IDs, but here we often had one to many and many to one issues so it was not 100% automated. It might also be possible to reassign the Primeclass attribute (or others) with a spatial join, but it might only be valid then for the unchanged glaciers."
This was not pursued further. If someone wants to have a look to investigate, here are the files of the state of GLIMS at the time RGI reg17 was created: https://cluster.klima.uni-bremen.de/~fmaussion/misc/rgi7_data/l2_sel_reg_tars/RGI17.tar.gz. A workflow should have a look at submissions 700/708, 730 and 764 and try to trace back what happened.
RGI version
RGI v7.0
Describe the issue
Reported by Owen King:
"RGI7 was used to measure glacier surface elevation change from 2000 onwards, alongside the elevation change estimates of Hugonnet et al. (2021). A subset of RGI7 was extracted where RGI7 and RGI6 polygons intersected. This was done to remove rock glaciers, perennial snowfields and other ice-debris landforms included in RGI7 in GTN-G 17. These features display little change in the elevation change grids of Hugonnet et al. (2021) and are so abundant (several thousand) that they bias catchment level elevation change signals."
Detective work that followed
Here are the outlines submission IDs available in GLIMS when RGI reg17 was generated:
Both 700/708 and 730 have the same issues (rock glaciers) as for RGI16. Furthermore, the Argentina / Chile border makes both inventories pretty much useless as is (both inventories stop at the border). This situation is why submission 764 was created, a merge work done by Frank Paul and Philip Rastner. It's 764 that was used for the RGI, as single submission for all of RGI reg17.
I noted back in the day (1 Jul 2022) that all glacier classes were lost in the merger (
primeclassattribute, containing categories for glacieret, rock glacier, etc.), to which Frank replied:"Yes, unfortunately the topologic changes resulted in a more or less complete loss of all attribute information. With a spatial join it was possible to recover the satellite image IDs, but here we often had one to many and many to one issues so it was not 100% automated. It might also be possible to reassign the Primeclass attribute (or others) with a spatial join, but it might only be valid then for the unchanged glaciers."
This was not pursued further. If someone wants to have a look to investigate, here are the files of the state of GLIMS at the time RGI reg17 was created: https://cluster.klima.uni-bremen.de/~fmaussion/misc/rgi7_data/l2_sel_reg_tars/RGI17.tar.gz. A workflow should have a look at submissions 700/708, 730 and 764 and try to trace back what happened.