A 30 m winter wheat distribution dataset for the North China Plain from 2000 to 2024

Winter wheat is a major food crop in China, with the North China Plain (NCP) serving as the primary production region and playing a critical role in national food security. However, long-term, high-resolution winter wheat maps for this region remain limited. This study presents a 30 m resolution winter wheat distribution dataset for the NCP (WheatMapNCP) from 2000 to 2024, generated by combining automated training sample generation with a random forest (RF) classifier. A stratified random sampling framework was used to estimate unbiased winter wheat area. Validation results show that the produced maps achieved an average overall accuracy (OA) of 95.98 ± 1.15%, and an average F1 score of 86.4%. The estimated planted areas show a consistent temporal trend with official statistics, and the mapped areas show strong correlation to statistics at the provincial (R² = 0.97-0.98) and municipal (R² = 0.84-0.96) levels. The dataset not only provides long-term, high-quality support for monitoring winter wheat dynamics, but also offers a reliable approach for generating timely, transparent wheat area estimates based on satellite data.

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Publication Details

Journal
Scientific Data
Published
2026-04-14
DOI
https://doi.org/10.1038/s41597-026-07216-0
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

A 30 m winter wheat distribution dataset for the North China Plain from 2000 to 2024

Yuval Sadeh, Josef Wagner, Jean Rehbinder, Inbal Becker‐Reshef et al.
Scientific Data
Remote Sensing in Agriculture
article

A 30 m winter wheat distribution dataset for the North China Plain from 2000 to 2024

Yuval Sadeh, Josef Wagner, Jean Rehbinder, Inbal Becker‐Reshef, Fangjie Li, Francoise Nerry
article en

Abstract

Winter wheat is a major food crop in China, with the North China Plain (NCP) serving as the primary production region and playing a critical role in national food security. However, long-term, high-resolution winter wheat maps for this region remain limited. This study presents a 30 m resolution winter wheat distribution dataset for the NCP (WheatMapNCP) from 2000 to 2024, generated by combining automated training sample generation with a random forest (RF) classifier. A stratified random sampling framework was used to estimate unbiased winter wheat area. Validation results show that the produced maps achieved an average overall accuracy (OA) of 95.98 ± 1.15%, and an average F1 score of 86.4%. The estimated planted areas show a consistent temporal trend with official statistics, and the mapped areas show strong correlation to statistics at the provincial (R² = 0.97-0.98) and municipal (R² = 0.84-0.96) levels. The dataset not only provides long-term, high-quality support for monitoring winter wheat dynamics, but also offers a reliable approach for generating timely, transparent wheat area estimates based on satellite data.

Scientific Data
Microsoft (United States) (US), Centre National de la Recherche Scientifique (FR), Laboratoire des Sciences de l'Ingénieur, de l'Informatique et de l'Imagerie (FR), Microsoft Research (United Kingdom) (GB), Monash University (AU), University of Maryland, College Park (US), Université de Strasbourg (FR)
China Scholarship Council
Zero hunger
Openalex Percentile: Top 16%
Remote Sensing in Agriculture
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A 30 m winter wheat distribution dataset for the North China Plain from 2000 to 2024 — Yuval Sadeh, Josef Wagner, et al. · Scientific Data (2026) | TGRS Research Map | TGRS