Abstract: Chlorophyll content is one of the important agronomic parameters affecting winter wheat yield and quality, while the difference in the farmland soil moisture content can obviously affect the winter wheat growth. It is of significance to realize the hyperspectral remote sensing monitoring of winter wheat chlorophyll content both in irrigated and dry lands. This paper analyzed the winter wheat canopy characteristics in irrigated and dry lands of Shanxi, extracted the sensitive bands, and constructed the optimal remote sensing models of chlorophyll content through correlation analysis. The spectral reflectance and the first derivative spectra had the similar variation trend, but their values had greater differences for the irrigated and dry lands. The spectral characteristic bands of the winter wheat canopy in irrigated lands and in dry lands were 624, 780, 958, 1053, and 1082 nm, and 691, 848, 871, 1199, and 1212 nm, respectively, and the prediction models for monitoring the chlorophyll content of winter wheat in the irrigated lands and dry lands had the best effect when constructed by FDMSAVI (1082, 624) and FDMSAVI (1082, 624), with the R² being 0.8447 and 0.8627, respectively. It was considered that to utilize hyperspectral technology to monitor the chlorophyll content of winter wheat both in irrigated and in dry lands would be feasible, and could provide technical supports for the scientific management and decision-making of wheat field.