Validation of MODIS Temperature and Emissivity Products Based on Ground-Based Mid-Wave Hyperspectral Imaging Measurement in the Northwestern Plateau Region of Qinghai, China

Abstract

The climatic fluctuations in northern China exhibit remarkable variability, making it imperative to harness the power of MODIS data for conducting comprehensive investigations into the influences of desertification, desert expansion, and snow and ice melting phenomena. Consequently, the rigorous evaluation of MODIS land surface temperature (LST) and land surface emissivity (LSE) products takes on a momentous role, as this provides an essential means to ensure data accuracy, thereby instilling confidence in the robustness of scientific analyses. In this study, a high-resolution hyperspectral imaging instrument was utilized to measure mid-wave hyperspectral images of grasslands and deserts in the northwest plateau region of Qinghai, China. The measured data were processed in order to remove the effects of sensor noise, atmospheric radiation, transmission attenuation, and scattering caused by sunlight and atmospheric radiation. Inversion of the temperature field and spectral emissivity was performed on the measured data. The inverted data were compared and validated against MODIS land surface temperature and emissivity products. The validation results showed that the absolute errors of emissivity of grassland backgrounds provided by MCD11C1 in the three mid-wave infrared bands (3.66–3.840 μm, 3.929–3.989 μm, and 4.010–4.080 μm) were 0.0376, 0.0191, and 0.0429, with relative errors of 3.9%, 2.1%, and 4.8%, respectively. For desert backgrounds, the absolute errors of emissivity were 0.0057, 0.0458, and 0.0412, with relative errors of 0.4%, 4.9%, and 3.9%, respectively. The relative errors for each channel were all within 5%. Regarding the temperature data products, compared to the inverted temperatures of the deserts and grasslands, the remote sensing temperatures provided by MOD11L2 had absolute errors of ±2.3 K and ±4.1 K, with relative errors of 1.4% and 0.7%, respectively. The relative errors for the temperature products were all within 2%.