DOI: 10.57760/sciencedb.33549
title: EA-MSRice: A 10-m Resolution Multi-Season Paddy Rice Dataset for East Asia (2017–2024)
title: 东亚2017-202410米分辨率多季水稻数据集

description: The East Asia Multi-Season Paddy Rice Dataset (EA-MSRice) is a long-term, high-spatial-resolution paddy rice mapping product covering East Asia, providing annual 10-m resolution rice distribution maps for China, Japan, South Korea, and North Korea from 2017 to 2024. The dataset was generated using the Optical–SAR Rice Mapping Framework (OSRMF), which integrates phenological metrics derived from Sentinel-2 optical imagery through the Optical Paddy Rice Index (OPRI) with the previously validated SAR Paddy Rice Index (SPRI).OSRMF adopts an adaptive decision-tree strategy that dynamically adjusts to optical data availability. In regions with high-quality optical observations, OPRI serves as the primary discriminator, while multiple SPRI-based criteria are embedded as independent decision nodes to progressively refine classification results. When optical data are limited or unavailable, the framework shifts to an SPRI-dominant hierarchy, using available optical information as auxiliary constraints to ensure classification stability under complex observational conditions. All annual products were systematically validated using nearly 200,000 ground reference samples and official agricultural statistics, achieving overall accuracies exceeding 93% in major rice-producing regions, with user’s and producer’s accuracies mostly above 90% and strong agreement with statistical records.EA-MSRice effectively captures the latitudinal zonation and multi-cropping patterns of paddy rice across East Asia, providing a consistent, high-resolution, and long-term baseline dataset for food security assessment, water resource management, agricultural monitoring, and climate change impact studies.
description: The East Asia Multi-Season Paddy Rice Dataset (EA-MSRice) is a long-term, high-spatial-resolution paddy rice mapping product covering East Asia, providing annual 10-m resolution rice distribution maps for China, Japan, South Korea, and North Korea from 2017 to 2024. The dataset was generated using the Optical–SAR Rice Mapping Framework (OSRMF), which integrates phenological metrics derived from Sentinel-2 optical imagery through the Optical Paddy Rice Index (OPRI) with the previously validated SAR Paddy Rice Index (SPRI).OSRMF adopts an adaptive decision-tree strategy that dynamically adjusts to optical data availability. In regions with high-quality optical observations, OPRI serves as the primary discriminator, while multiple SPRI-based criteria are embedded as independent decision nodes to progressively refine classification results. When optical data are limited or unavailable, the framework shifts to an SPRI-dominant hierarchy, using available optical information as auxiliary constraints to ensure classification stability under complex observational conditions. All annual products were systematically validated using nearly 200,000 ground reference samples and official agricultural statistics, achieving overall accuracies exceeding 93% in major rice-producing regions, with user’s and producer’s accuracies mostly above 90% and strong agreement with statistical records.EA-MSRice effectively captures the latitudinal zonation and multi-cropping patterns of paddy rice across East Asia, providing a consistent, high-resolution, and long-term baseline dataset for food security assessment, water resource management, agricultural monitoring, and climate change impact studies.