Water Surface Emissivity Research Articles

Retrieval of Plateau Lake Water Surface Temperature from UAV Thermal Infrared Data

The lake water surface temperature (LWST) is a critical parameter influencing lake ecosystem dynamics and addressing challenges posed by climate change. Traditional point measurement techniques exhibit limitations in providing comprehensive LWST data. However, the emergence of satellite remote sensing and unmanned aerial vehicle (UAV) Thermal Infrared (TIR) technology has opened new possibilities. This study presents an approach for retrieving plateau lake LWST (p-LWST) from UAV TIR data. The UAV TIR dataset, obtained from the DJI Zenmuse H20T sensor, was stitched together to form an image of brightness temperature (BT). Atmospheric parameters for atmospheric correction were acquired by combining the UAV dataset with the ERA5 reanalysis data and MODTRAN5.2. Lake Water Surface Emissivity (LWSE) spectral curves were derived using 102 hand-portable FT-IR spectrometer (102F) measurements, along with the sensor’s spectral response function, to obtain the corresponding LWSE. Using estimated atmospheric parameters, LWSE, and UAV BT, the un-calibrated LWST was calculated through the TIR radiative transfer model. To validate the LWST retrieval accuracy, the FLIR Infrared Thermal Imager T610 and the Fluke 51-II contact thermometer were utilized to estimate on-point LWST. This on-point data was employed for cross-calibration and verification. In the study area, the p-LWST method retrieved LWST ranging from 288 K to 295 K over Erhai Lake in the plateau region, with a final retrieval accuracy of 0.89 K. Results demonstrate that the proposed p-LWST method is effective for LWST retrieval, offering technical and theoretical support for monitoring climate change in plateau lakes.

Improving the accuracy of time-lapse thermal infrared imaging for hydrologic applications

In recent years, thermal infrared (TIR) cameras have improved in resolution and accuracy while their cost has declined. By deploying a ground-based TIR camera to collect time-lapse images, it is now possible to acquire high-resolution stream temperatures through both space and time. However, while ground-based TIR is useful for qualitatively identifying stream temperature differences, acquisition of absolute stream temperatures remains difficult due to interference from reflected radiation. Therefore, improved correction approaches are still needed to extract absolute stream temperatures from ground-based, time-lapse TIR imagery. Using >1100 TIR images acquired every 10 minutes during two field seasons, we assess two methods for correcting time-lapse, ground-based TIR stream temperature data: (1) an analytical method derived from the literature that corrects for atmospheric transmissivity, reflected temperatures and water surface emissivity, which did not improve TIR temperature accuracy, and (2) an empirical approach that uses an offset correction created from in-stream control point temperatures, which reduced the mean absolute temperature difference between the TIR and in-situ stream temperatures. Examination of the analytical method revealed its sensitivity to reflected temperatures from the surrounding environment, a problem that is particularly pronounced in ground-based TIR imagery due to the lower stream emissivity at more oblique viewing angles. Since reflected temperatures and stream surface emissivity can be difficult to quantify and are misrepresented in previous hydrologic literature, the empirical correction approach offers an alternative method for extracting absolute stream temperatures from ground-based TIR imagery affected by these factors.

A Regression Model of Microwave Emission of a Water Surface at 37.5 GHz

This paper presents the functional dependence of the microwave emission of a rough water surface at a frequency of 37.5 GHz (wavelength of ~8 mm). The MiROSE model (Microwave Rough Ocean Surface Emission model) is based on the experimental studies of the own thermal radio emission of the water surface, which were carried out in 2005 and 2007 on the oceanographic platform of the Black Sea Hydrophysical Experimental Facility of the Russian Academy of Sciences. This paper demonstrates the steps of the simulation for selecting the optimal functions to describe the incident angle, wind, and temperature dependences of the increment of the own water surface emission. The following parameters can be calculated on the basis of the proposed model: the increment of the brightness temperature, radio-brightness contrast, and radio-brightness temperature for horizontal and vertical polarizations of the received emission. The model is applicable to water temperatures ranging from 12.5 to 25°C, wind speeds of 3–13 m/s, and incident angles of 30°–80° measured from the nadir.

Validation of ASTER/TIR standard atmospheric correction using water surfaces

The standard atmospheric correction algorithm for the five thermal infrared (TIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is based on radiative transfer calculation using the MODTRAN code. Atmospheric profiles input to MODTRAN are extracted from either the Global Data Assimilation System (GDAS) product or the Naval Research Laboratory (NRL) climatology model. The present study provides validation results of this algorithm. First, in situ lake surface temperatures measured in 13 vicarious calibration (VC) experiments were compared with surface temperatures retrieved from ASTER data. As the results, the mean bias was 0.8 and 1.8 K for GDAS and NRL, respectively. The NRL model performed worse than GDAS for four experiments at Salton Sea, CA, probably because the model was not suitable for this site, which has typically higher surface temperature and humidity than other VC sites. Next, the algorithm was validated based on the max-min difference (MMD) of water surface emissivity retrieved from each of 163 scenes acquired globally. As a result, the algorithm error increased quadratically with the precipitable water vapor (PWV) content of the atmosphere, and the expected MMD error was 0.049 and 0.067 for GDAS and NRL, respectively, with a PWV of 3 cm, where 0.05 on MMD is roughly corresponding to -0.8 or +2.3 K on the retrieved surface temperature error. The algorithm performance degraded markedly when the surface temperature exceeded about 25/spl deg/C, particularly for NRL. Consequently, GDAS performs better than NRL as expected, while both will perform less well for humid conditions.

Polarized microwave emission from water waves

Partially polarimetric measurements of thermal emission from a striated water surface at 91.65 GHz illustrate the potential for remote sensing of water wave direction by passive microwave radiometry. The three Stokes parameter measurements were made using a precision polarimetric radiometer trained on a rotatable water wave tank at several elevation angles from near nadir to near grazing. The polarimetric measurements are well corroborated by calculations using a tilted‐facet geometrical optics model for the water surface emission and scattering. Multiple scattering of the incident background radiation is incorporated for observation angles approaching grazing. The downwelling background brightness is computed by using an atmospheric radiative transfer model. We show that azimuthal brightness variations in the third Stokes parameter are in phase quadrature with the first and second modified Stokes parameters. For observation angles near ∼60°–70° from nadir the first three parameters have particularly large azimuthal brightness variations and thus have significant potential for measuring ocean wave direction. Moreover, the azimuthal brightness variations caused by water waves are not negligible for many passive microwave atmospheric sounding and surface remote sensing purposes, even at nadir. A range of elevation angles resulting in minimal azimuthal variations is identified.

Laboratory Determinations of Water Surface Emissivity

Abstract A spectrophotometer was used to determine surface emissivity of water samples in a laboratory. The results confirm a previous field result that emissivity is independent of water composition and is approximately equal to 0.97. This value was reduced by about 3% in the presence of surface oil films but the effect of different types of oil was negligible.