ArticleScientific data2025
A long-term paddy rice distribution dataset in Asia at a 30 m spatial resolution.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- City-Scale, Source-Resolved Methane Inventories Reveal Drivers and Mitigation Pathways Across China's Cities.Environmental science & technology · 2026Article
- A 30-m annual distribution dataset of major crops in China from 2001-2024.Scientific data · 2026Article
- Integrating Metabolomics and Proteomics to Reveal the Regulatory Network Governing the Natural Variation in Rice Seed Germination Rate.Plants (Basel, Switzerland) · 2026Article
- A 10 m maize, rice and soybean yield dataset from 2016 to 2021 in Northeast China.Scientific data · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rice is a staple food for over half the global population and contributes to more than 10% of global anthropogenic methane emissions. Precise mapping of rice distribution in Asia, the primary region for rice cultivation responsible for over 60% of global production, is crucial for monitoring food security and greenhouse gas emissions. However, due to cloud cover impacts on optical remote sensing imagery, there is still a lack of long-term, high-resolution rice distribution datasets for the entire Asian region. This study develops the Global Crop Dataset-Rice (GCD-Rice) dataset to map rice cultivation across three seasons in 16 Asian countries from 1990 to 2023. Using Landsat and Sentinel-1 datasets, along with a phenological approach and a random forest model, the maps were validated with 258,547 field samples. Results show an average user accuracy of 89.88%, a producer accuracy of 88.52%, and an overall accuracy of 88.85%. Furthermore, comparing with statistical area reveals an overall average R² value of 0.768, a slope of 0.874, and an RMSE of 0.346.
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