Xiaokang Kou

Estimation of Land Surface Temperature through Blending MODIS and AMSR-E Data with the Bayesian Maximum Entropy Method

Land surface temperature (LST) plays a major role in the study of surface energy balances. Remote sensing techniques provide ways to monitor LST at large scales. However, due to atmospheric influences, significant missing data exist in LST products retrieved from satellite thermal infrared (TIR) remotely sensed data. Although passive microwaves (PMWs) are able to overcome these atmospheric influences while estimating LST, the data are constrained by low spatial resolution. In this study, to obtain complete and high-quality LST data, the Bayesian Maximum Entropy (BME) method was introduced to merge 0.01° and 0.25° LSTs inversed from MODIS and AMSR-E data, respectively. The result showed that the missing LSTs in cloudy pixels were filled completely, and the availability of merged LSTs reaches 100%. Because the depths of LST and soil temperature measurements are different, before validating the merged LST, the station measurements were calibrated with an empirical equation between MODIS LST and 0~5 cm soil temperatures. The results showed that the accuracy of merged LSTs increased with the increasing quantity of utilized data, and as the availability of utilized data increased from 25.2% to 91.4%, the RMSEs of the merged data decreased from 4.53 °C to 2.31 °C. In addition, compared with the filling gap method in which MODIS LST gaps were filled with AMSR-E LST directly, the merged LSTs from the BME method showed better spatial continuity. The different penetration depths of TIR and PMWs may influence fusion performance and still require further studies.

Modeling of the Permittivity of Holly Leaves in Frozen Environments

The dielectric property of vegetation has a considerable effect on the characteristics of the microwave radiation of vegetation. In frozen environments, when the temperature is colder than normal, changes such as increased soluble sugar and decreased moisture content (MC) can occur in the vegetation. The dielectric property of vegetation, which is almost entirely controlled by its free and bound water content, will also change. To characterize the dielectric behavior of vegetation in frozen regions, a sensitive experiment was conducted on holly leaves with a high-performance coaxial probe over a frequency range from 0.5 to 40 GHz and a temperature range from 0°C to -20°C. Based on the measurements and the physical properties of the constituent substances of vegetation, a semiempirical dielectric model for holly leaves in low temperature environments was developed. In this model, a decrease in MC, which causes a reduction in the complex permittivity, was described as an increase in the ice content. The complex permittivity of bound water was measured using a saturated sucrose solution at -6.5°C. The research will provide a reference for the dielectric property study of the vegetation in frozen environments.

Calibration of the L-MEB Model for Croplands in HiWATER Using PLMR Observation

The Soil Moisture and Ocean Salinity (SMOS) mission was initiated in 2009 with the goal of acquiring global soil moisture data over land using multi-angular L-band radiometric measurements. Specifically, surface soil moisture was estimated using the L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model. This study evaluated the applicability of this model to the Heihe River Basin in Northern China for specific underlying surfaces by simulating brightness temperature (BT) with the L-MEB model. To analyze the influence of a ground sampling strategy on the simulations, two resampling methods based on ground observations were compared. In the first method, the simulated BT of each point observation was initially acquired. The simulations were then resampled at a 1 km resolution. The other method was based on gridded data with a resolution of 1 km averaged from point observations, such as soil moisture, soil temperature, and soil texture. The simulated BTs at a 1 km resolution were then obtained using the L-MEB model. Because of the large variability in soil moisture, the resampling method based on gridded data was used in the simulation. The simulated BTs based on the calibrated parameters were validated using airborne L-band data from the Polarimetric L-band Multibeam Radiometer (PLMR) acquired during the HiWATER project. The root mean square errors (RMSEs) between the simulated results and the PLMR data were 6 to 7 K for V-polarization and 3 to 5 K for H-polarization at different angles. These results demonstrate that the model effectively represents agricultural land surfaces, and this study will serve as a reference for applying the L-MEB model in arid regions and for selecting a ground sampling strategy.

A new method to determine the freeze-thaw erosion

Freeze-thaw erosion is the third largest soil erosion type after water erosion and wind erosion, which is a serious threat to agricultural land and various buildings, especially for water projects. In this paper, a new method based on the passive microwave remote sensing technique was proposed to classify and assess the freeze-thaw erosion. The core of this new method is at two important indices: the freeze-thaw cycling days per year, and the phase transition water content per day. The first index can be used to determine the freeze-thaw erosion region and the second index can be used to evaluate the degree of freeze-thaw erosion. The application of this new method in China shows good result. It indicates that the freeze-thaw erosion regions in China are mainly distributed in Tibet, Mongolia and the province of Qinghai, Xinjiang, Gansu, Sichuan and Heilongjiang. Furthermore, the comparably serious freeze-thaw erosion region is located in Tibet Plateau.

Evaluation and comparison of FY-2E VISSR, MODIS and IMS snow cover over the Tibetan Plateau

Snow cover information is crucial to global climate change research and hydrological applications. Snow cover over the Tibetan Plateau is important to water resources and Asian climate. Based on high temporal resolution of geostationary satellite data, snow cover map with less cloud obscuration can be obtained daily. In this paper, geostationary meteorological satellite FY2E VISSR data is used to obtain the snow cover information over the Tibetan Plateau in year 2010 and 2011 winter seasons. Meteorological station observations are used to evaluate the performance of snow cover maps. In addition, MODIS and IMS snow cover products are used for comparison and validation. Results indicate VISSR snow cover maps show good performance in reducing cloud obscuration. MODIS snow cover maps present highest overall accuracy, followed by VISSR and IMS. VISSR and IMS snow cover maps show slight over-estimation of snow cover over the Tibetan Plateau.

A new dielectric model for vegetation in frozen environment—Part I: Modeling section

Dielectric constant is an important parameter in microwave remote sensing. The microwave scattering/radiation signal of vegetation is closely related to its dielectric constant. Many related models have been established by now. However, most of them can only be used in room temperature. Therefore, it brings errors in the research of vegetation in frozen environment. In this study, a new dielectric model, which can be used at frequencies ranged from 3GHz to 40GHz under temperatures between -20°C and -4°C, has been established. It was developed based on Debye-Cole dual-dispersion model. The validation shows it has an acceptable precision.

A new approach for the validation of coarse-resolution satellite soil moisture products

Soil moisture plays a crucial role in the terrestrial water cycle. It can be estimated by manual measurements for a small watershed, while this is very time-consuming when applied in the large scale. The remote sensing technology provides a new approach to monitor the soil moisture in a large scale. However, it should be evaluated before being used. In the study, the L-band Microwave Emission of the Biosphere model (L-MEB) model was used to retrieve the soil moisture based on the airborne brightness temperature in the Heihe River Basin, then the retrieved soil moisture was aggregated to 25km based on the area weighting factor method. The aggregated soil moisture was used to validate the two AMSR2 data: the JAXA soil moisture products and the LPRM soil moisture products. The results shows the JAXA SM products has an underestimation compared with the pixel-averaged SM, and the LPRM SM products is higher than the pixel-averaged SM.

Evaluation of organic matter effect on brightness temperature simulated over Genhe region, China

Soil moisture is an important parameter in many fields. Since the dielectric constant of soil is directly related with its moisture content, many soil dielectric constant models have been established and used in the application of soil moisture inversion. As an effective composition of soil, organic matter could increase the adsorption of soil particles and affect the dielectric constant. However, due to its little content, it was seldom considered in soil moisture inversion and brightness simulation. In this study, a semi-empirical organic dielectric model was used in the forward simulation of brightness temperature in Genhe River basin. The results show that it has a higher accuracy about 1.6k~2.4k than using TMD model at C-band and X-band.

Simulation of microwave brightness temperature over heterogeneous land surface using L-MEB model in HIWATER

Soil moisture is an important parameter in hydrological circulation. For the microwave signal at L-band is very sensitive to the soil moisture, there have been many algorithms to retrieve soil moisture at L-band. The Soil Moisture and Ocean Salinity (SMOS) mission is launched in 2009, and the surface soil moisture retrieving is based on the inversion of the Lband Microwave Emission of the Biosphere (L-MEB) radiative transfer model. Due to the heterogeneity of the surface, the capability of the model remains to be verified in some region. In the study, the brightness temperature at L-band in Heihe River Basin is simulated by using the τ-ω model firstly. Secondly, the sensitivity analysis of the model on the parameters is conducted to get the optimal results. At last, the simulated brightness temperature is calculated by using the adjusted parameters, and the PLMR microwave brightness temperature is used to validate the simulation results. It turns out that the root-mean-square errors between L-MEB simulated and PLMR are 9K to 12K for V-polarization, and 6K to 8K at H-polarization respectively at different angles, which proves the L-MEB model have an good capability in the of China.

A new dielectric model for vegetation in frozen environment—Part II: Validation section

A new dielectric model for vegetation in frozen environment based on the Debye-Cole dual-dispersion model was already developed in part I. This model can be used at a wide frequency range (0.5GHz - 40GHz) and even applicable for negative temperatures reached -20°C. In this paper, a matrix-doubling microwave emission model was used to evaluate vegetation effects in a frozen environment at 6.925, 10.65, 18.7 and 36.5GHz (V and H polarization). To verify the new developed dielectric model, a kind of young tree named Populus tomentosas was measured based on the Truck-mounted Multi-frequency Microwave Radiometer in December of 2012. In the experiment, the ground was irrigated to get rid of the soil signals. Also, the row-structures effect on the trees can be eliminated when water covered the whole ground surface. Comparisons and analysis between model simulations and field measurements showed the dielectric model can be applied to microwave emission model as input data. Furthermore, the characteristics of microwave radiation of vegetation in frozen environment were evaluated and how the vegetation dielectric constant affected the electric field and physical property of vegetation layer was explained.