%A %T Analyses of Land Surface Emissivity Characteristics in Mid-Infrared Bands %0 Journal Article %D 2018 %J SPECTROSCOPY AND SPECTRAL ANALYSIS %R 10.3964/j.issn.1000-0593(2018)05-1393-07 %P 1393-1399 %V 38 %N 05 %U {https://www.gpxygpfx.com/CN/abstract/article_9803.shtml} %8 2018-05-01 %X Land surface temperature (LST) plays an important role in the process of ground-air interaction and is an parameter in global change research. At the same time, the emissivity of land surface is the key input parameter of LST inversion. Mid-infrared spectrum (3~5 μm) is between visible-near infrared (0.38~2.5 μm) and thermal infrared spectrum (8~14 μm). The emissivities of terrestrial materials exhibit unique characteristics in mid-infrared spectrum, which can be used for frost monitoring and mineral composition analysis et al. Energy detected with sensor in the mid-infrared region, however, is a combination of emitted radiation from terrestrial materials and reflected radiation due to sun irradiance. The energy separation mechanism of these two parts is complicated. Therefore, there are few relevant literatures about researches on emissivities of terrestrial materials in mid-infrared spectrum. In this paper, the effective emissivities of MODIS infrared channels were calculated for a single uniform surface and a complex region with mixed pixel. It is found that the effect of surface temperature is insignificant for effective emissivity calculation in a single uniform surface. Under complex surface, the effective emissivity has a coupling effect with composition ratio of materials in the mixed pixel and surface temperatures of these materials. Within the allowable range of error, the effective emissivity of mixed pixel can ignore the effect of materials’ surface temperature. The sensitivity of emissivity error to the precision of LST inversion varies with wavelength. An accuracy of 1 K in LST retrieval requires emissivity error be constrained to within 0.04 in mid-infrared region, while within 0.02 in thermal infrared region. It can be seen that mid-infrared spectrum has much potentials in LST retrieval.