Research on the Application of Multispectral Remote Sensing Technology Based on NDVI and NDRE with Case Analysis of Precision Nitrogen Management in Drip-Irrigated Winter Wheat

Abstract

This study presents a precision fertilization management method based on monitoring vegetation indices (NDVI and NDRE). By integrating canopy spectral data with quantitative relationships between fertilization rates and crop yield, the approach provides scientific fertilization recommendations for different growth stages. Case analysis demonstrates significant positive correlations between NDVI/NDRE values and nitrogen application rates in drip-irrigated winter wheat. Specifically, NDVI exhibits stronger linear relationships with nitrogen levels during the recovering and flowering stages, while NDRE shows superior performance from jointing to milking stages (jointing, booting, grain-filling, and milking). Both indices effectively diagnose crop nitrogen status, optimize fertilization amounts, reduce waste, and enhance yield. Furthermore, this method is adaptable to other crops (e.g., corn, soybeans) and can be implemented at scale using UAV-mounted multispectral cameras, offering robust technical support for precision agriculture.