Overview

Global Spatially-Disaggregated Crop Production Statistics Data for 2020 Version 2.0 Release 2, represented as a gridded crop production data cube. The record describes crop area, harvested area, production, and yield by crop and production technology at 5 arc-minute resolution.

#food security #crop production #spatial distribution #gridded agriculture

Important note

Derived from available subnational statistics; local national or subnational data providers may hold more precise source statistics for some locations.

Quick start

Python

import xarray as xr

url = "https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/spam2020-v2r2.zarr"
ds = xr.open_zarr(url)

import rioxarray

url = "https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/cog/spam2020-physical_area-all.tif"
da = rioxarray.open_rasterio(url, masked=True)

library(stars)

url <- 'ZARR:"/vsicurl/https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/spam2020-v2r2.zarr"'
ds <- read_mdim(url, proxy = TRUE)

library(terra)

url <- "/vsicurl/https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/cog/spam2020-physical_area-all.tif"
r <- rast(url)

Full access details and endpoints

Intended uses

global and regional analysis of crop area, production, and yield patterns
food security and agricultural systems assessment
spatial targeting at national and sub-national scale

Not recommended for

field-scale farm management

Why: the grid is too coarse for field-scale operational decisions.

Use instead: local survey or administrative production data.

Commodities

Cereals ↗Root/tuber crops with high starch or inulin content ↗Leguminous crops ↗Oilseed crops and oleaginous fruits ↗Sugar crops ↗Fibre crops ↗Stimulant crops ↗Fruit and nuts ↗Vegetables and melons ↗Tobacco ↗Rubber ↗

Access & use

Files, endpoints, and worked examples for each distribution.

Data

zarr287 MB

Zarr representation of the source MAPSPAM files.

Format: Zarr — best for cloud-native analysis, reading just the slices you need from the full cube

Variables: physical_area, harvested_area, production, yield

Dimensions: cell × crop × technology

Data dictionary →

Access the data

https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/spam2020-v2r2.zarr

Usage examples

Python

import xarray as xr

url = "https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/spam2020-v2r2.zarr"
ds = xr.open_zarr(url)

# Clip a window (East Africa) — subsets every variable in the store
window = ds.sel(x=slice(28, 52), y=slice(18, -12))

# ...or sample a single point
point = ds.sel(x=36.8, y=-1.3, method="nearest")

Other access methods

S3:s3://digital-atlas/cdh/data/mapspam2020-v2r2/spam2020-v2r2.zarr

cogs

Cloud Optimized GeoTIFFs, one per variable and technology, with one band per crop in the order of the crop dimension.

Format: Cloud-Optimized GeoTIFF — best for single-file downloads, visualisation, and traditional GIS tools

Variables: physical_area, harvested_area, production, yield

Dimensions: cell × crop × technology

Data dictionary →

List of files 12 filesDownload CSV

Individual file

VariableTechnology

Download

https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/cog/spam2020-physical_area-all.tif

Usage examples

Python

import rioxarray

url = "https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/cog/spam2020-physical_area-all.tif"
da = rioxarray.open_rasterio(url, masked=True)

# Clip a window (East Africa)
window = da.rio.clip_box(
    minx=28, miny=-12, maxx=52, maxy=18
)

# ...or sample a single point
point = da.sel(x=36.8, y=-1.3, method="nearest")

library(terra)

url <- "/vsicurl/https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/cog/spam2020-physical_area-all.tif"
r <- rast(url)

# Clip a window (East Africa)
window <- crop(r, ext(28, 52, -12, 18))

# ...or sample a single point
point <- extract(r, cbind(36.8, -1.3))

Other access methods

File pattern: spam2020-{variable}-{technology}.tif

HTTPS directory:https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/cog/

S3 directory:s3://digital-atlas/cdh/data/mapspam2020-v2r2/cog/

Additional assets

crop codesmetadatadescribedby5 KB

Dimension code list for crop values.

Format: application/json

Access the dataOpen

https://digital-atlas.s3.amazonaws.com/cdh/data/mapspam2020-v2r2/crop-codes.json

Data dictionary

What each file holds. A layout describes how the data is stored in a file: its variables, the dimensions they vary over, and any keys.

File layouts

Files	Format	Variables	Dimensions	No data
zarr	Zarr	physical_area, harvested_area, production, yield	cell × crop × technology	NaN
cogs	Cloud-Optimized GeoTIFF	physical_area, harvested_area, production, yield	cell × crop × technology	-3.4028235e+38

In every file

Variables

Variable	Type	Unit	Description
physical_area	float32	ha	Physical crop area allocated to each grid cell.
harvested_area	float32	ha	Harvested crop area allocated to each grid cell.
production	float32	t	Crop production allocated to each grid cell. Absolute quantity; regional summaries should sum values across cells.
yield	float32	kg ha-1	Crop yield for each grid cell. Relative quantity; do not sum yield values across grid cells. Regional summaries should use a weighted mean with harvested_area as the weight.

Dimensions

cellxy

5 arc-minutes (~10km at equator).

Grid spacing: 0.08333333 degree

crop

MAPSPAM crop code.

whea Wheat
rice Rice
maiz Maize
barl Barley
mill Small Millet
pmil Pearl Millet
sorg Sorghum
ocer Other Cereals
pota Potato
swpo Sweet Potato
yams Yams
cass Cassava
orts Other Roots
bean Bean
chic Chickpea
cowp Cowpea
pige Pigeon Pea
lent Lentil
opul Other Pulses
soyb Soybean
grou Groundnut
cnut Coconut
oilp Oilpalm
sunf Sunflower
rape Rapeseed
sesa Sesame Seed
ooil Other Oil Crops
sugc Sugarcane
sugb Sugarbeet
cott Cotton
ofib Other Fibre Crops
coff Arabic Coffee
rcof Robusta Coffee
coco Cocoa
teas Tea
toba Tobacco
bana Banana
plnt Plantain
citr Citrus
trof Other Tropical Fruit
temf Temperate Fruit
toma Tomato
onio Onion
vege Other Vegetables
rubb Rubber
rest Rest of Crops

Show all 46 valuesShow fewer

technology

MAPSPAM production system; all is the sum of irrigated and rainfed.

all
irrigated
rainfed

Technical metadata

The full spatial, temporal, and modeling detail behind the summaries elsewhere on this page.

Spatial

CRS: EPSG:4326
Extent (W S E N): [-180, -90, 180, 90]
Coverage: World
Grid spacing: 5 arc-minutes (~9.3 km at the equator)

Temporal

Reference date: 2020

Provenance

Ordered processing steps, from source to publication.

source2026-04-22
Original MAPSPAM 2020 v2 release.
Derived from: Source MAPSPAM dataset ↗
Code: mapspamc ↗ @ v0.0.2
cloud-optimize2026-07-07
Conversion of source MAPSPAM files to a consolidated Zarr data cube.
Code: mapspam.py ↗ @ 47f9830

How to cite

Please cite the dataset and any associated peer-reviewed publications.

International Food Policy Research Institute (IFPRI) (2026) Global Spatially-Disaggregated Crop Production Statistics Data for 2020 Version 2.0 Release 2. Version v2r2. Harvard Dataverse. https://doi.org/10.7910/DVN/SWPENT. Accessed through the CGIAR Climate Action Data Hub, https://cgiar-climate-data-hub.github.io/catalog/spam2020_v2r2/.

BibTeX

@misc{spam2020_2026,
  title     = {Global Spatially-Disaggregated Crop Production Statistics Data for 2020 Version 2.0 Release 2},
  author    = {{International Food Policy Research Institute (IFPRI)}},
  year      = {2026},
  version   = {v2r2},
  publisher = {Harvard Dataverse},
  doi       = {10.7910/DVN/SWPENT},
  note      = {Accessed through the CGIAR Climate Action Data Hub, https://cgiar-climate-data-hub.github.io/catalog/spam2020_v2r2/}
}

Contacts

Who produced this dataset, and who to reach about it.

Zhe GuoMaintainer

International Food Policy Research Institute (IFPRI)

Producer

z.guo@cgiar.org www.ifpri.org/ ↗

Brayden YoungbergMaintainer

Alliance of Bioversity International and CIAT

b.youngberg@cgiar.org

International Food Policy Research Institute (IFPRI)Licensor

www.ifpri.org/ ↗

Shuang Zhou

International Food Policy Research Institute (IFPRI)

Producer

s.zhou@cgiar.org www.ifpri.org/ ↗

Liangzhi You

International Food Policy Research Institute (IFPRI)

Producer

MAPSPAM 2020

Important note

Quick start

Intended uses

Not recommended for

Commodities

Data

Additional assets

File layouts

In every file

Variables

Dimensions

Spatial

Temporal

How to cite

Related publications

Contacts