Data for "A Two-Step Method for Monitoring Annual Paddy Rice Planted Area in Tropical Region by Integrating Rice Identification and Cropping Intensity Estimation"

This dataset accompanies the research article "A Two-Step Method for Monitoring Annual Paddy Rice Planted Area in Tropical Region by Integrating Rice Identification and Cropping Intensity Estimation" , comprising two primary components for Vietnam in 2020: (1) the high-resolution paddy rice spatial distribution data and (2) the paddy rice cropping intensity data. The paddy rice spatial distribution data was generated through a machine learning workflow where Random Forest classifier was trained using rice/non-rice samples and features extracted from Sentinel-1 SAR and Sentinel-2 MSI images. This classification process was specifically constrained within the Rice Potential Zone (RPZ) to enhance accuracy. Based on the fine spatial distribution of paddy rice, the Sentinel-1 SAR time series images were smoothed by Harmonic Analysis of Time Series (HANTS), and then the quadratic difference method was used to generate the cropping intensity information of rice. Please refer to the original article for more details on the methodology and implementation. DOI: https://doi.org/10.1109/tgrs.2025.3549296