The ecological environment of the Yellow River Basin in China is characterized by drought, which has been exacerbated by global warming. It is critical to keep accurate track of the region’s agricultural drought conditions. To enhance the vegetation health index (VHI), the optimal time scale for the standardized precipitation evapotranspiration index (SPEI) was determined by using the maximum correlation coefficient method, and the calculation method for VHI was optimized. The contributions of the vegetation condition index (VCI) and the temperature condition index (TCI) to the VHI were scientifically optimized, leading to the development of the optimal VHI (VHIopt). Soil moisture anomaly (SMA) and the SPEI were employed for assessing the performance of VHIopt. Furthermore, the temporal and spatial evolution of agricultural drought in the Yellow River Basin (YRB) was analyzed using VHIopt. The results indicate the following: (1) In the YRB, the optimal contribution of the VCI to the VHI is lower than that of the TCI. (2) The drought monitoring accuracy of VHIopt in forests, grasslands, croplands, and other vegetation types exceeds that of the original VHI (VHIori). Additionally, it demonstrates a high level of consistency with the SMA and the SPEI03 regarding spatial and temporal characteristics. (3) Agricultural drought in the YRB is gradually diminishing; however, significant regional differences remain. Generally, the findings of this study highlight that VHIopt is better suited to the specific climate and vegetation conditions of the Yellow River Basin, enhancing its effectiveness for agricultural drought monitoring in this region.

The radiometric stability of satellite thermal infrared (TIR) channels is an indispensable prerequisite for the accurate retrieval of land surface temperature (LST) and the generation of reliable climate data records. This study evaluates the on-orbit radiometric calibration stability of the Fengyun-3D (FY-3D)/MEdium Resolution Spectral Imager-II (MERSI-II) TIR channels (channels 24 and 25) over four years (2021–2024) via a rigorous cross-calibration framework against Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS). By imposing stringent spectral, spatial, temporal, and angular constraints to ensure the high fidelity of collocated pixel pairs, the cross-calibration results demonstrate that FY-3D/MERSI-II exhibits exceptional radiometric stability. Absolute brightness temperature biases are typically less than 0.1 K, with root mean square errors (RMSEs) limited to 1.20 K over a range of diurnal and seasonal conditions, demonstrating no noticeable systematic degradation. Furthermore, the downstream impact of this calibration on LST retrieval was quantified using the adapted National Oceanic and Atmospheric Administration Joint Polar Satellite System Enterprise algorithm. Validated against independent ground-based longwave radiation measurements collected from the Heihe Watershed Allied Telemetry Experimental Research network (HiWATER) and the Surface Radiation Budget Network (SURFRAD), the retrieved LST yielded overall biases of 0 K and −0.37 K, respectively, with RMSEs below 2.5 K. Cross-calibration demonstrates a limited and context-dependent impact on daytime LST, while the nighttime LST accuracy can be marginally improved using seasonal calibration coefficients derived from combined day/night matchups. Mechanistically, the integration of a soil directional emissivity model into the retrieval algorithm effectively mitigates viewing-zenith-angle (VZA)-induced uncertainties, systematically reducing biases by 0.12–0.20 K and RMSEs by 0.04–0.06 K. These findings confirm that the on-orbit radiometric calibration of FY-3D/MERSI-II meets scientific quality requirements and provide practical guidance for optimizing LST retrieval.