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Internal enhancements and improvements: Improve default datasets #818

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amyburness opened this issue Jul 4, 2024 · 3 comments
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@amyburness
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Improve default datasets by making CHIRPS data available to users for national reporting drought hazard (SO3-1), allowing users to import national population data for use in SO2-3/SO3-2 indicators.

@Samweli Samweli added the size 60 It will take between 2 to 3 weeks label Jul 19, 2024
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amyburness commented Aug 7, 2024

Notes from UR meetings:

  • @gabrieldaldegan hve the standardised precipitation index CHIRPS Data set as an alternative that must be incorporated as a default data set.
  • We must allow users to use custom data sets stored locally (Nationalion data)
  • These national data sets have to be processed locally and not in the cloud for the security of the data.
  • We validate the custom data sets -> validation (document data standard with a validation message if incorrect)
  • We may need to standardise the file type for custom data and document that.
  • The national data for population will likely be census data and may come in different formats we will need to think about how it incorporates this. the data may not even be geospatial data.
  • Currently, the default offered is graded world pop data.
  • @azvoleff has the CHIRPS data and that has gone through some analysis to make it analysis ready.

@amyburness amyburness added this to the Kartoza Support 2024 milestone Sep 15, 2024
@amyburness amyburness reopened this Sep 18, 2024
@amyburness
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If they choose CHIRPS then there is a disclaimer saying it is not global. 50 north 50 south.
national level- the user will need to preprocess the data set e.g. population rasterise the data.
-land cover
-land productivity

@amyburness amyburness reopened this Nov 18, 2024
@amyburness amyburness assigned dimasciput and unassigned Samweli Nov 20, 2024
@amyburness
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@dimasciput I think the tasks can be broken down as follows

  • incorporate CHIRPS data set (with non-global disclaimer)
  • Allows users to incorporate population raster dataset (land cover and productivity)

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