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grdi-filled-missing-values-count·dataset

Global Deprivation Index: Filled-In Data Map

GRDI Filled Missing Values Count
land NASA VEDA COG
In plain English

What it measures. A global map showing, for each cell, how many of the underlying data inputs had to be filled in because original values were missing, indicating where the deprivation index relies on estimated data.

How it's made. Built for the Global Gridded Relative Deprivation Index by counting inputs filled in per cell using a fill-missing-values tool.

How & where you'd use it. Helps users judge how reliable the deprivation index is in different places when interpreting it.

What's measured

grdifilledmissingvaluescount

Coverage & cadence

  • Time span2010-01-01 → 2021-12-31
  • Spatial extent-180, -55.983, 179.817, 82.183
  • FormatsCOG

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

Global Gridded Relative Deprivation Index (GRDI) raster showing count of constituent inputs that were filled in per cell using the Fill Missing Values tool.

Get the data

veda_access.py
# NASA VEDA — open STAC API, anonymous (cloud-optimized GeoTIFFs)
from pystac_client import Client

cat = Client.open("https://openveda.cloud/api/stac")
col = cat.get_collection("grdi-filled-missing-values-count")
items = list(col.get_items())          # browse the analysis-ready COGs
# open an asset with rioxarray:
# import rioxarray; da = rioxarray.open_rasterio(items[0].assets["cog_default"].href)
NASA VEDA is an open STAC catalog — browse and stream the cloud-optimized GeoTIFFs anonymously (no login).