Heshun Wang

Evaluation of the NCEP and MODIS Atmospheric Products for Single Channel Land Surface Temperature Retrieval With Ground Measurements: A Case Study of HJ-1B IRS Data

In this paper, two atmospheric profile sources were assessed for land surface temperature (LST) retrieval purposes for the HJ-1B IRS (Infrared Scanner) single-channel thermal infrared (TIR) data. One profile source is the National Center for Environmental Prediction (NCEP) operational global analysis data, and the other source is the Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric profiles product (MOD07). The atmospheric profiles were used as the input to the MODTRAN 4 radiative transfer model to calculate the atmospheric parameters involved in LST retrieval. The LST retrievals from the HJ-1B IRS data were compared with ground measured temperatures obtained from a series of field campaigns in Hebei province, China, from May to September of 2010. Ground measurements were performed over four land-cover types: bare soil, full-cover wheat, full-cover corn, and water surfaces. A total of 11 points of measurements was collected over a period of eight days. The results indicate that the LST derived from HJ-1B IRS data using either the NCEP or MOD07 profiles showed good agreement with the ground LSTs, with an root mean square error (RMSE) of 1.16 and 1.21 K for the NCEP and MOD07, respectively. In addition, we found that the MOD07 profiles may cause greater error for the atmospheric parameters estimation in the TIR domain for the regions of higher altitude due to a lack of data at the lower altitude levels. Thus, we proposed a method for combination of the MOD07 and NCEP profiles for LST retrieval. The results show that the combined profile is able to produce more reliable results than the use of only one type of profile because the combination offers both high spatial resolution and the necessary level of accuracy. This result implies that the combined profiles may be highly useful for accurate LST retrieval when local soundings are not available and particularly for sensors with only one thermal channel.

A single-channel algorithm for land surface temperature retrieval from HJ-1B/IRS data based on a parametric model

Land surface temperature (LST) is required for a wide variety of scientific studies, from climatology to hydrology and ecology. This paper proposes a single-channel parametric model (SC-PM) algorithm for retrieving land surface temperature from the HJ-1B/IRS thermal infrared data. The SC-PM algorithm is based on the parametric model (PM) developed by Ellicott et al. (2009), the coefficients of PM are updated for HJ-1B/IRS, and the altitude is considered when extracting atmospheric profile from NCEP data. The proposed algorithm is evaluated by simulated data and MODIS LST products. The results show an root mean square error (RMSE) of 0.22K for the simulated data, and 1.73K for the MODIS LST product. This indicates the algorithm is suitable for producing HJ-1B/IRS LST product.

Evaluation of the Airborne CASI/TASI Ts-VI Space Method for Estimating Near-Surface Soil Moisture

High spatial resolution airborne data with little sub-pixel heterogeneity were used to evaluate the suitability of the temperature/vegetation (Ts/VI) space method developed from satellite observations, and were explored to improve the performance of the Ts/VI space method for estimating soil moisture (SM). An evaluation of the airborne ΔTs/Fr space (incorporated with air temperature) revealed that normalized difference vegetation index (NDVI) saturation and disturbed pixels were hindering the appropriate construction of the space. The non-disturbed ΔTs/Fr space, which was modified by adjusting the NDVI saturation and eliminating the disturbed pixels, was clearly correlated with the measured SM. The SM estimations of the non-disturbed ΔTs/Fr space using the evaporative fraction (EF) and temperature vegetation dryness index (TVDI) were validated by using the SM measured at a depth of 4 cm, which was determined according to the land surface types. The validation results show that the EF approach provides superior estimates with a lower RMSE (0.023 m3·m−3) value and a higher correlation coefficient (0.68) than the TVDI. The application of the airborne ΔTs/Fr space shows that the two modifications proposed in this study strengthen the link between the ΔTs/Fr space and SM, which is important for improving the precision of the remote sensing Ts/VI space method for monitoring SM.

Temperature and emissivity separation algorithm for TASI airborne thermal hyperspectral data

This paper proposed a modified TES algorithm for retrieving land surface temperature and emissivity (LST&E) from Thermal Airborne Spectrographic Imager (TASI) hyperspectral data and the results were validated with in situ ground measurements. Firstly, the atmospheric correction of TASI data was performed by MODTRAN model with atmospheric profile extracted from NCEP data which was modified by local meteorological data. Then, the S-G filter was used to smooth the spectral data in order to reduce the noise effect of TASI data. Finally, the Temperature and Emissivity Separation (TES) algorithm was modified to retrieving LST&E from TASI data. The validation results indicated that the derived LST agreed with the ground LSTs well with RMSE lower than 1.5K, and the retrieved emissivity curve showed a good agreement with ground LSEs measured by an Fourier Transform Infrared (FTIR) spectroradiometer.

Investigating the Impact of Soil Moisture on Thermal Infrared Emissivity Using ASTER Data

This study investigates the effects of soil moisture (SM) on land surface emissivity (LSE) using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LSE data acquired in Heihe Watershed Allied Telemetry Experimental Research (HiWATER). Three bare surface sites with automatic meteorological stations that collected long-term SM data were chosen to evaluate the SM impact. The ASTER LSE retrieval was performed using the water vapor scaling method to improve the atmospheric correction results, and the validation results indicate that the emissivity uncertainties are better than 1%. The multitemporal LSE data reveal that there is an increase in the emissivity with increasing SM. A logarithmic linear relationship was established to describe the broadband emissivity dependence with SM over each site, with determination coefficients of 0.9429, 0.7705, and 0.4603. The modeled values calculated using coefficients derived in previous studies for samples with similar compositions yielded good agreements with ASTER broadband emissivities over two sites. The empirical model also shows that the diurnal variation in emissivity, particularly over one site, is so significant that it should not be neglected.

Modeling Directional Brightness Temperature Over Mixed Scenes of Continuous Crop and Road: A Case Study of the Heihe River Basin

A new geometric optical model is proposed in this letter to simulate the directional brightness temperature (DBT) distribution over mixed scenes of continuous crop and road. The DBT distributions of the crop and road zones are separately calculated, and the road zone consists of a road and adjacent crop sides. A road distribution polar map is designed to show all of the roads of different lengths, widths, and orientations in the scene. The airborne multiangle data set of the thermal infrared band that was acquired during the Heihe Watershed Allied Telemetry Experimental Research experiment is used for validation. The results demonstrate that the proposed model can simulate the DBT of a heterogeneous scene (90 × 90 m2) with a root-mean-square error equal to 1.1 K and good trend similarity.

Retrieval of Leaf, Sunlit Soil, and Shaded Soil Component Temperatures Using Airborne Thermal Infrared Multiangle Observations

Land surface component temperatures are important inputs in longwave radiation and evapotranspiration estimation models. Most component temperature inversion approaches focus only on two components, namely, soil and leaves, because space-based multiangle observations are lacking. This approach is inconsistent with ground-based measurements, which suggest that the temperatures of sunlit and shaded soil may significantly differ. This paper explores a three-component temperature inversion scheme that uses airborne multiangle thermal infrared observations to decrease the difference between the retrieved data and the actual subpixel temperature distribution. The FR97 model, which is an analytical directional brightness temperature model that was modified by dividing the soil component into sunlit and shaded portions, is adopted to calculate the matrix of component effective emissivity, which links multiangular observations and component temperatures. The new forward model and the inversion scheme are assessed using simulated data sets from the Scattering by Arbitrarily Inclined Leaves (4SAIL) model. The results indicate that the modified FR97 model provides good precision and that the inversion scheme based on the modified FR97 model is appropriate because of the models simplicity and accuracy and the inversions low sensitivity to noise. The inversion scheme is validated using airborne data collected by the wide-angle infrared dual-mode line/area array scanner over an area planted with maize and ground measurements collected during the Heihe Watershed Allied Telemetry Experimental Research campaign. The results indicate that the root mean square errors of the component temperatures of the leaves, sunlit soil, and shaded soil were 0.72 °C, 1.55 °C, and 2.73 °C, respectively. Because of the modified FR97s straightforward form and acceptable precision, we recommend this new retrieval scheme as an option for retrieving the component temperatures of leaves, sunlit soil, and shaded soil.

Evaluation of Land Surface Temperature Retrieval from FY-3B/VIRR Data in an Arid Area of Northwestern China

This paper uses the refined Generalized Split-Window (GSW) algorithm to derive the land surface temperature (LST) from the data acquired by the Visible and Infrared Radiometer on FengYun 3B (FY-3B/VIRR). The coefficients in the GSW algorithm corresponding to a series of overlapping ranges for the mean emissivity, the atmospheric Water Vapor Content (WVC), and the LST are derived using a statistical regression method from the numerical values simulated with an accurate atmospheric radiative transfer model MODTRAN 4 over a wide range of atmospheric and surface conditions. The GSW algorithm is applied to retrieve LST from FY-3B/VIRR data in an arid area in northwestern China. Three emissivity databases are used to evaluate the accuracy of different emissivity databases for LST retrieval, including the ASTER Global Emissivity Database (ASTER_GED) at a 1-km spatial resolution (AG1km), an average of twelve ASTER emissivity data in the 2012 summer and emissivity spectra extracted from spectral libraries. The LSTs retrieved from the three emissivity databases are evaluated with ground-measured LST at four barren surface sites from June 2012 to December 2013 collected during the HiWATER field campaign. The results indicate that using emissivity

Analysis of the Land Surface Temperature Scaling Problem: A Case Study of Airborne and Satellite Data over the Heihe Basin

Abstract: This study analyzed the scaling problem of land surface temperature (LST) data retrieved with the Temperature Emissivity Separation (TES) algorithm. We compiled a remotely sensed dataset that included Thermal Airborne Hyperspectral Imager (TASI) and satellite-based Advanced Spaceborne Thermal Emission Reflection (ASTER) data, which were acquired simultaneously. This dataset provided the range of spatial heterogeneities of land surface necessary for the study, which was quantified by the dispersion variance. The LST scaling problem was studied by comparing the remotely sensed LST products in two ways. First, the LST products calculated in the distributed method and the lumped method were compared. Second, the airborne and satellite-based LST products derived from the TES algorithm were compared. Four upscaling methods of LST were used in the process. A scaling correction methodology was developed based on the comparisons. The results showed that the scaling effect could be as large as 0.8 K when the spatial resolution of the TASI LST data was coarse. The scaling effect increases quickly with the spatial resolution until it reaches the characteristic scale of the landscape and is positively correlated with the spatial heterogeneity. The first two upscaling methods denoted as Methods 1–2 can upscale the LST more effectively when compared with the other two scaling methods (Methods 3–4). The scaling effect for the ASTER data is not notable. The comparison between the TASI and

Validation of the land surface temperature derived from HJ-1B/IRS data with ground measurements

Land surface temperature (LST) is required for a wide variety of scientific studies, from climatology to hydrology and ecology. The feasibility of using atmospheric profile extracted from NCEP data for LST retrieval from HJ-1B/IRS data was analyzed in this paper. A series of ground measurements were carried out to validate the IRS LST results in Hebei province, China, from May to September, 2010. The results indicate that the LST derived from IRS data by using NCEP data showed a good agreement with the ground LSTs, with RSEM lower than 1.5K. Therefore, it can be concluded that the profile extracted from NCEP data is a useful source for LST retrieval from HJ-1B/IRS data.