High-resolution maps of rice cropping intensity across Southeast Asia

Southeast Asia contributes 20% of the world's rice production and 29% of global rice methane emissions, highlighting the need for accurate data on harvested areas to support food security and greenhouse gas accounting. However, existing paddy rice maps often lack information on cropping intensity, spatial resolution, and accuracy due to diverse cultivation practices. This study presents a 10-m resolution, open-access dataset of rice cropping intensity, enabling the precise estimation of growing and harvested areas across Southeast Asia. The Local Unsupervised Classification with Phenological Labelling (LUCK-PALM) was used to generate the map by combining Sentinel-1A and Sentinel-2A/B data (2020-2021). Validation at the pixel level (n = 58,885) shows an overall accuracy of 0.98, a kappa coefficient of 0.870, and an F1 score of 0.879 in identifying rice areas. This comprehensive dataset is available in a public repository and can be used to enhance food and water security strategies and refines estimates of methane emissions.

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Publication Details

Journal
Scientific Data
Published
2025-08-12
DOI
https://doi.org/10.1038/s41597-025-05722-1
Citations
2
Primary Topic
Rice Cultivation and Yield Improvement
Type
article
Field-Weighted Citation Impact
3.50
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article

High-resolution maps of rice cropping intensity across Southeast Asia

Fatchurrachman, Aaron Davitt, Dian Fiantis, Ramisah Mohd Shah et al.
2 citations
Scientific Data
Rice Cultivation and Yield Improvement
3.50
article

High-resolution maps of rice cropping intensity across Southeast Asia

Fatchurrachman, Aaron Davitt, Dian Fiantis, Ramisah Mohd Shah, Budiman Minasny, Budi Indra Setiawan, Frisa Irawan Ginting, Sunny Goh Eng Giap, Rudiyanto Rudiyanto, Norhidayah Che Soh, Sam Schiller
article en
2 citations

Abstract

Southeast Asia contributes 20% of the world's rice production and 29% of global rice methane emissions, highlighting the need for accurate data on harvested areas to support food security and greenhouse gas accounting. However, existing paddy rice maps often lack information on cropping intensity, spatial resolution, and accuracy due to diverse cultivation practices. This study presents a 10-m resolution, open-access dataset of rice cropping intensity, enabling the precise estimation of growing and harvested areas across Southeast Asia. The Local Unsupervised Classification with Phenological Labelling (LUCK-PALM) was used to generate the map by combining Sentinel-1A and Sentinel-2A/B data (2020-2021). Validation at the pixel level (n = 58,885) shows an overall accuracy of 0.98, a kappa coefficient of 0.870, and an F1 score of 0.879 in identifying rice areas. This comprehensive dataset is available in a public repository and can be used to enhance food and water security strategies and refines estimates of methane emissions.

Scientific DataVol. 12(1)
The University of Sydney (AU), Universiti Malaysia Terengganu (MY), IPB University (ID), World Water Watch (US), Asian Health Coalition (US), Nano Carbon (Poland) (PL), Andalas University (ID)
Zero hunger
Openalex Percentile: Top 7%
Rice Cultivation and Yield Improvement
3.50
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High-resolution maps of rice cropping intensity across Southeast Asia — Fatchurrachman, Aaron Davitt, et al. · Scientific Data (2025) | TGRS Research Map | TGRS