A UAV-Proxied Satellite Remote Sensing Approach for Winter Wheat Plant Nitrogen Concentration Mapping
Abstract
Accurate and real-time prediction of plant nitrogen concentration (PNC) is crucial for assessing the N status of winter wheat. Satellite remote sensing enables large-scale PNC monitoring but suffers from coarse spatial resolution, causing scale mismatches with field sampling. Unmanned aerial vehicle (UAV) remote sensing bridges this gap, linking satellite observations with ground measurements. This study mapped regional-scale winter wheat PNC using ground-measured PNC, UAV (DJI Phantom 4 Multispectral), and satellite (PlanetScope, Sentinel-2) data. First, UAV-based vegetation indices (VIs) with machine learning (ML) predicted PNC at the field scale. Next, UAV data were aggregated to match satellite resolution, producing field-scale PNC maps. These were then used as regional-scale samples, combined with satellite VIs, to develop PNC estimation models. At the regional scale, SVR with Sentinel-2 VIs performed best (R2 = 0.95, RMSE = 0.09%, RPD = 4.70). Validation with ground samples and UAV-scale PNC maps confirmed the reliability of cross-scale models (R2 = 0.75–0.96, RMSE = 0.09–0.29%, RPD = 1.93–4.85). Among the two satellite sensors evaluated, Sentinel-2 outperformed PlanetScope in PNC estimation, likely due to its more optimal red-edge spectral configuration. These findings highlight the effectiveness of UAV-satellite cross-scale remote sensing for regional-scale PNC mapping, providing a valuable tool for large-scale crop N monitoring.
Xiaokai Chen, Fenling Li, Qingrui Chang, Yuxin Miao, Chao Wang, Weilong Qin, & Kang Yu (2025). A UAV-Proxied Satellite Remote Sensing Approach for Winter Wheat Plant Nitrogen Concentration Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing: 1–12.
Dr. Xiaokai Chen
Researcher, Shanxi University
My research focuses on crop nitrogen nutrition monitoring and diagnosis using multi-scale remote sensing, involving near-ground, UAV and satellite remote sensing.
Dr. Weilong Qin
Assistant Researcher (current)
My research interests include remote sensing, plant physiology, and crop resilience.
Prof. Dr. Kang Yu
Professor of Precision Agriculture
My research interests include precision crop farming, hyperspectral remote sensing, and AI in agriculture.