Evidence map›Paper›PMID 40213049›Full record

ArticleData in brief2025

A dataset of yearly probabilistic crop type maps for the EU from 1990 to 2018.

Josef Baumert, Thomas Heckelei, Hugo Storm

Abstract read
In one paragraph

Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Josef BaumertInstitute for Food and Resource Economics, University of Bonn, Meckenheimer Allee 174, 53115 Bonn, Germany.
Thomas HeckeleiInstitute for Food and Resource Economics, University of Bonn, Meckenheimer Allee 174, 53115 Bonn, Germany.
Hugo StormInstitute for Food and Resource Economics, University of Bonn, Meckenheimer Allee 174, 53115 Bonn, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We provide an ensemble of probabilistic crop type maps for the entire European Union, mapping the shares of 25 different crop types at 1km resolution for all years from 1990 to 2018. We generate the maps using a recently developed approach based on a model of the data generating process from field- to region: essentially, we link knowledge about which crops farmers are more likely to grow under certain environmental conditions with data on regional crop acreages. Consequently, the resulting crop share estimates are consistent with regional crop area statistics while considering spatial heterogeneity. To reflect estimation uncertainty of the provided crop shares, we sample 100 maps per year and EU country, each being coherent with regional or national information. This ensemble of maps allows users to sample from potentially different but similarly likely spatial crop type distributions and thereby adequately reflect uncertainty in their applications, for example, in an environmental model. We additionally provide maps with only the most likely crop shares for users mainly interested in point estimates. The maps provide researchers, policy makers, and other stakeholders information to evaluate the impact of changing political, economic, and environmental conditions over three decades on agricultural production in the European Union.

Indexed as

DownscalingProbabilistic crop mappingSpatial disaggregationUncertainty quantification

Identifiers

PMID40213049
PMCPMC11985063

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.