ArticleScientific data2024
Global Gridded Crop Production Dataset at 10 km Resolution from 2010 to 2020.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
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Who cites it
9 citing papers in PubMed.
- Mapping the global threat of Mythimna separata (Walker) and its economic implications for Brazil's agriculture.Pest management science · 2026Article
- The Silent Expansion of Fire Activity in Continental Tropical Asia shaped by natural and anthropogenic forces.Nature communications · 2026Article
- A 1-km Dataset of Water Consumption and Irrigation for Major Grain Crops in the Yellow River Basin Based on the Crop Water Production Function.Scientific data · 2026Article
- A 10 m maize, rice and soybean yield dataset from 2016 to 2021 in Northeast China.Scientific data · 2026Article
- A multimodal geospatial foundation model anticipates crop stress and yield failure across climates and species.Frontiers in plant science · 2026Article
- Spatial prediction of Spodoptera frugiperda expansion in India using MaxEnt under shifting climate regimes.Scientific reports · 2025Article
- An Africa-wide agricultural production database to support policy and satellite-based measurement systems.Scientific data · 2025Article
- The SESAME Human-Earth Atlas.Scientific data · 2025Article
- The 500-meter long-term winter wheat grain protein content dataset for China from multi-source data.Scientific data · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The global gridded crop production dataset at 10 km resolution from 2010 to 2020 (GGCP10) for maize, wheat, rice, and soybean was developed to address limitations of existing datasets characterized by coarse resolution and discontinuous time spans. GGCP10 was generated using a series of adaptively trained data-driven crop production spatial estimation models integrating multiple data sources, including statistical data, gridded production data, agroclimatic indicator data, agronomic indicator data, global land surface satellite products, and ground data. These models were trained based on agroecological zones to accurately estimate crop production in different agricultural regions. The estimates were then calibrated with regional statistics for consistency. Cross-validation results demonstrated the models' performance. GGCP10's accuracy and reliability were evaluated using gridded, survey, and statistical data. This dataset reveals spatiotemporal distribution patterns of global crop production and contributes to understanding mechanisms driving changes in crop production. GGCP10 provides crucial data support for research on global food security and sustainable agricultural development.
Identifiers
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Registered trials
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.