Earth Data School
About
Full catalog/geoglam
geoglam·dataset

Global Crop Condition Monitor

GEOGLAM Crop Monitor
biosphere NASA VEDA COG
In plain English

What it measures. A worldwide assessment of how the major food crops, wheat, maize, rice, and soybeans, are faring in the big producing and trading countries, plus weather factors likely to affect harvests.

How it's made. Built by the GEOGLAM Crop Monitor, a consensus of over 40 partner agencies, universities, and space programs combining satellite and field observations.

How & where you'd use it. Gives markets and governments early, neutral information on crop conditions to support food-supply stability.

What's measured

geoglam

Coverage & cadence

  • Time span2020-01-01 → 2025-03-31
  • Spatial extent-180.004, -90, 180.006, 90
  • FormatsCOG

What you can do with it

  • Map vegetation, forests and biomass
  • Monitor ecosystem productivity and carbon
  • Support habitat and biodiversity studies
Official description

The Crop Monitors were designed to provide a public good of open, timely, science-driven information on crop conditions in support of market transparency for the G20 Agricultural Market Information System (AMIS). Reflecting an international, multi-source, consensus assessment of crop growing conditions, status, and agro-climatic factors likely to impact global production, focusing on the major producing and trading countries for the four primary crops monitored by AMIS (wheat, maize, rice, and soybeans). The Crop Monitor for AMIS brings together over 40 partners from national, regional (i.e. sub-continental), and global monitoring systems, space agencies, agriculture organizations and universities. Read more: https://cropmonitor.org/index.php/about/aboutus/

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("geoglam")
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).