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There are five widely used kernel-driven models in the thermal infrared domain designed for the angular correction of land surface temperature (LST), including three-parameter Roujean Lagouarde (RL), Vinnikov, RossThick-LiSparseR (Ross-Li), LiStrahlerFriedl-LiDenseR (LSF-Li), and four-parameter Vinnikov-RoujeanLagouarde (Vinnikov-RL). Their fitting accuracies with hundreds of observation angles (i.e., sufficient angle) were studied; however, the fitting ability of these five models with limited observation angles is unknown, which makes it difficult to choose the appropriate one in applications. To solve this problem, 30 600 groups of multiangle directional brightness temperature (DBT) datasets were simulated by the unified optical-thermal 4-stream model considering scattering by arbitrary inclined leaves (4SAIL) model considering ten different leaf area index values, three leaf inclination distribution functions, two hotspot factors, 17 different component temperatures, five solar zenith angles, and six solar azimuth angles. Each group contains DBT values in 21 960 viewing directions [i.e., 61 viewing zenith angle (VZA) x 360 viewing azimuth angle (VAA)]. We assume that all limited observations are in the plane with VAA = 180°/0° and VZA changing from -60° to 60° with a step of 10°. There are 13 candidate angles to be selected. Five, seven, nine, and 11 angle sampling schemes include 225, 400, 225, and 36 limited multiangle combinations, respectively. Each combination was used to drive these five kernel-driven models to fit 21 960 DBTs for 30 600 groups of 4SAIL simulations. The root-mean-square error (RMSE) of each combination and mean RMSE of all 886 combinations were used to assess the overall fitting ability of five kernel-driven models. In addition, 1 k errors were added to the driven DBTs to evaluate the models' robustness. Four groups of airborne measured DBTs were adopted to validate the assessment conclusions. Results show that the recommended order of these five models driven by 5-11 multiangle DBTs is Vinnikov-RL, LSF-Li, Vinnikov, Ross-Li, and RL when the driven DBTs do not contain errors; Vinnikov-RL, Vinnikov, LSF-Li, Ross-Li, and RL when the driven DBTs contain 1k errors; and Vinnikov-RL, LSF-Li, Ross-Li, RL, and Vinnikov for four groups of airborne measured datasets.
Xueting Ran; Biao Cao; Boxiong Qin; Zunjian Bian; Yongming Du; Hua Li; Qing Xiao; Qinhuo Liu. Assessment of Five Thermal Infrared Kernel-Driven Models Using Limited Multiangle Observations. IEEE Geoscience and Remote Sensing Letters 2021, PP, 1 -5.
AMA StyleXueting Ran, Biao Cao, Boxiong Qin, Zunjian Bian, Yongming Du, Hua Li, Qing Xiao, Qinhuo Liu. Assessment of Five Thermal Infrared Kernel-Driven Models Using Limited Multiangle Observations. IEEE Geoscience and Remote Sensing Letters. 2021; PP (99):1-5.
Chicago/Turabian StyleXueting Ran; Biao Cao; Boxiong Qin; Zunjian Bian; Yongming Du; Hua Li; Qing Xiao; Qinhuo Liu. 2021. "Assessment of Five Thermal Infrared Kernel-Driven Models Using Limited Multiangle Observations." IEEE Geoscience and Remote Sensing Letters PP, no. 99: 1-5.
Surface upward longwave radiation (SULR) is one of the four components of the surface radiation budget, which is defined as the total surface upward radiative flux in the spectral domain of 4-100 μm. The SULR is an indicator of surface thermal conditions and greatly impacts weather, climate, and phenology. Big Earth data derived from satellite remote sensing have been an important tool for studying earth science. The Advanced Baseline Imager (ABI) onboard the Geostationary Operational Environmental Satellite (GOES-16) has greatly improved temporal and spectral resolution compared to the imager sensor of the previous GOES series and is a good data source for the generation of high spatiotemporal resolution SULR. In this study, based on the hybrid SULR estimation method and an upper hemisphere correction method for the SULR dataset, we developed a regional clear-sky land SULR dataset for GOES-16 with a half-hourly resolution for the period from 1st January 2018 to 30th June 2020. The dataset was validated against surface measurements collected at 65 Ameriflux radiation network sites. Compared with the SULR dataset of the Global LAnd Surface Satellite (GLASS) longwave radiation product that is generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the polar-orbiting Terra and Aqua satellites, the ABI/GOES-16 SULR dataset has commensurate accuracy (an RMSE of 15.9 W/m2 vs 19.02 W/m2 and an MBE of −4.4 W/m2 vs −2.57 W/m2), coarser spatial resolution (2 km at nadir vs 1 km resolution), less spatial coverage (most of the Americas vs global), fewer weather conditions (clear-sky vs all-weather conditions) and a greatly improved temporal resolution (48 vs 4 observations a day). The published data are available at http://www.dx.doi.org/10.11922/sciencedb.j00076.00062.
Boxiong Qin; Biao Cao; Zunjian Bian; Ruibo Li; Hua Li; Xueting Ran; Yongming Du; Qing Xiao; Qinhuo Liu. Clear-sky land surface upward longwave radiation dataset derived from the ABI onboard the GOES–16 satellite. Big Earth Data 2021, 5, 161 -181.
AMA StyleBoxiong Qin, Biao Cao, Zunjian Bian, Ruibo Li, Hua Li, Xueting Ran, Yongming Du, Qing Xiao, Qinhuo Liu. Clear-sky land surface upward longwave radiation dataset derived from the ABI onboard the GOES–16 satellite. Big Earth Data. 2021; 5 (2):161-181.
Chicago/Turabian StyleBoxiong Qin; Biao Cao; Zunjian Bian; Ruibo Li; Hua Li; Xueting Ran; Yongming Du; Qing Xiao; Qinhuo Liu. 2021. "Clear-sky land surface upward longwave radiation dataset derived from the ABI onboard the GOES–16 satellite." Big Earth Data 5, no. 2: 161-181.
In order to improve the simulation accuracy of directional brightness temperature (DBT) and the retrieval accuracy of component temperature, a model considering intra-row heterogeneity to simulate the DBT angular distribution over crop canopy is proposed. At individual scale, the probability of leaf appearance is inversely proportional to the distance from central stem. On the basis of this assumption, we formulated leaf area volume density (LAVD) spatial distribution at three hierarchical scales: individual scale, row scale, and scene scale. The equations for directional gap probability and bi-directional gap probability were modified to adapt the heterogeneity of row structure. Afterwards, a straightforward radiative transfer model was built based on the gap probabilities. A set of simulated data was generated by the thermal radiosity-graphics combined model (TRGM) as the benchmark to evaluate both forward simulation and inversion ability of the new model; we compared the new DBT model against an existing model assuming row as homogeneous box. With the growth of crops, the canopy structure of row crops will gradually change from row structure to continuous canopy. The new DBT model agreed with the TRGM model much better than the homogeneous row model at the middle stage of the crop growth season. The new model and the homogeneous row model achieve similar accuracy at early stage and end stage. At the middle growth stage, the new model can improve the accuracy of soil temperature retrieval. We recommend the new DBT model as an option to improve the DBT simulation and component temperature retrieval for row-planted crop canopy. In particular, the more accurate component temperatures during the middle growth stage are fundamentally important in characterizing crop water status, evapotranspiration, and soil moisture, which are subsequently critical for predicting crop productivity.
Yongming Du; Biao Cao; Hua Li; Zunjian Bian; Boxiong Qin; Qing Xiao; Qinhuo Liu; Yijian Zeng; Zhongbo Su. Modeling Directional Brightness Temperature (DBT) over Crop Canopy with Effects of Intra-Row Heterogeneity. Remote Sensing 2020, 12, 2667 .
AMA StyleYongming Du, Biao Cao, Hua Li, Zunjian Bian, Boxiong Qin, Qing Xiao, Qinhuo Liu, Yijian Zeng, Zhongbo Su. Modeling Directional Brightness Temperature (DBT) over Crop Canopy with Effects of Intra-Row Heterogeneity. Remote Sensing. 2020; 12 (17):2667.
Chicago/Turabian StyleYongming Du; Biao Cao; Hua Li; Zunjian Bian; Boxiong Qin; Qing Xiao; Qinhuo Liu; Yijian Zeng; Zhongbo Su. 2020. "Modeling Directional Brightness Temperature (DBT) over Crop Canopy with Effects of Intra-Row Heterogeneity." Remote Sensing 12, no. 17: 2667.
An operational split-window (SW) algorithm was developed to retrieve high-temporal-resolution land surface temperature (LST) from global geostationary (GEO) satellite data. First, the MODTRAN 5.2 and SeeBor V5.0 atmospheric profiles were used to establish a simulation database to derive the SW algorithm coefficients for GEO satellites. Then, the dynamic land surface emissivities (LSEs) in the two SW bands were estimated using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED), fractional vegetation cover (FVC), and snow cover products. Here, the proposed SW algorithm was applied to Himawari-8 Advanced Himawari Imager (AHI) observations. LST estimates were retrieved in January, April, July, and October 2016, and three validation methods were used to evaluate the LST retrievals, including the temperature-based (T-based) method, radiance-based (R-based) method, and intercomparison method. The in situ night-time observations from two Heihe Watershed Allied Telemetry Experimental Research (HiWATER) sites and four Terrestrial Ecosystem Research Network (TERN) OzFlux sites were used in the T-based validation, where a mean bias of −0.70 K and a mean root-mean-square error (RMSE) of 2.29 K were achieved. In the R-based validation, the biases were 0.14 and −0.13 K and RMSEs were 0.83 and 0.86 K for the daytime and nighttime, respectively, over four forest sites, four desert sites, and two inland water sites. Additionally, the AHI LST estimates were compared with the Collection 6 MYD11_L2 and MYD21_L2 LST products over southeastern China and the Australian continent, and the results indicated that the AHI LST was more consistent with the MYD21 LST and was generally higher than the MYD11 LST. The pronounced discrepancy between the AHI and MYD11 LST could be mainly caused by the differences in the emissivities used. We conclude that the developed SW algorithm is of high accuracy and shows promise in producing LST data with global coverage using observations from a constellation of GEO satellites.
Ruibo Li; Hua Li; Lin Sun; Yikun Yang; Tian Hu; Zunjian Bian; Biao Cao; Yongming Du; Qinhuo Liu. An Operational Split-Window Algorithm for Retrieving Land Surface Temperature from Geostationary Satellite Data: A Case Study on Himawari-8 AHI Data. Remote Sensing 2020, 12, 2613 .
AMA StyleRuibo Li, Hua Li, Lin Sun, Yikun Yang, Tian Hu, Zunjian Bian, Biao Cao, Yongming Du, Qinhuo Liu. An Operational Split-Window Algorithm for Retrieving Land Surface Temperature from Geostationary Satellite Data: A Case Study on Himawari-8 AHI Data. Remote Sensing. 2020; 12 (16):2613.
Chicago/Turabian StyleRuibo Li; Hua Li; Lin Sun; Yikun Yang; Tian Hu; Zunjian Bian; Biao Cao; Yongming Du; Qinhuo Liu. 2020. "An Operational Split-Window Algorithm for Retrieving Land Surface Temperature from Geostationary Satellite Data: A Case Study on Himawari-8 AHI Data." Remote Sensing 12, no. 16: 2613.
As a surface component, the tree trunk affects the top-of-canopy (TOC) emissivity and thermal infrared (TIR) radiance over a forest with fewer leaves, which is important for the inversion of land surface temperatures (LSTs) and further applications such as predicting forest fires and monitoring drought conditions. Therefore, the tree trunk effect was analyzed in this article using a thermal radiation directionality model, in which the forest structure was considered by the geometric optical (GO) theory and the spectral invariance theory was introduced into the GO framework for the single-scattering effect between components. The model used was evaluated using unmanned aerial vehicle (UAV)-based measurements with root-mean-square errors (RMSEs) lower than 0.25 °C for directional anisotropies (DAs) of brightness temperatures (BTs). Comparison with a 3-D radiative transfer model, discrete anisotropic radiative transfer (DART), also indicated an acceptable tool of the proposed model for the trunk effect with RMSEs lower than 0.003 °C and 1.2 °C for DAs of emissivity and BTs, respectively. In this study, the root-mean-squared difference (RMSD) levels between the vegetation-soil and vegetation-trunk-soil canopies, which were viewed as an equivalent indicator of the trunk effect, were provided for the TOC emissivity and BTs as well as their DAs, by combination with the changes in the leaf area index (LAI), stand density, trunk shape, and component temperatures, which can help identify the cases in which the trunk effect should be considered. According to a comprehensive analysis, for cases with sparse stand density (α <0.04), the tree trunk should be considered for a BT RMSD level lower than 0.5 °C when the LAI value was lower than 0.6. The corresponding LAI value was 0.8 for an RMSD level of BT DA lower than 0.3 °C. Moreover, for the cases with low soil emissivity, the difference in the TOC emissivity with and without trunk can reach up to 0.035, and the RMSD was still larger than 0.01 when the stand density and LAI were 0.05 and 0.6, respectively.
Zunjian Bian; Biao Cao; Hua Li; Yongming Du; Wenjie Fan; Qing Xiao; Qinhuo Liu. The Effects of Tree Trunks on the Directional Emissivity and Brightness Temperatures of a Leaf-Off Forest Using a Geometric Optical Model. IEEE Transactions on Geoscience and Remote Sensing 2020, 59, 5370 -5386.
AMA StyleZunjian Bian, Biao Cao, Hua Li, Yongming Du, Wenjie Fan, Qing Xiao, Qinhuo Liu. The Effects of Tree Trunks on the Directional Emissivity and Brightness Temperatures of a Leaf-Off Forest Using a Geometric Optical Model. IEEE Transactions on Geoscience and Remote Sensing. 2020; 59 (6):5370-5386.
Chicago/Turabian StyleZunjian Bian; Biao Cao; Hua Li; Yongming Du; Wenjie Fan; Qing Xiao; Qinhuo Liu. 2020. "The Effects of Tree Trunks on the Directional Emissivity and Brightness Temperatures of a Leaf-Off Forest Using a Geometric Optical Model." IEEE Transactions on Geoscience and Remote Sensing 59, no. 6: 5370-5386.
In this study, two collection 6 (C6) Moderate Resolution Imaging Spectroradiometer (MODIS) level-2 land surface temperature (LST) products (MYD11_L2 and MYD21_L2) from the Aqua satellite were evaluated using temperature-based (T-based) and radiance-based (R-based) validation methods over barren surfaces in Northwestern China. The ground measurements collected at four barren surface sites from June 2012 to September 2018 during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) experiment were used to perform the T-based evaluation. Ten sand dune sites were selected in six large deserts in Northwestern China to carry out an R-based validation from 2012 to 2018. The T-based validation results indicate that the C6 MYD21 LST product has a better accuracy than the C6 MYD11 product during both daytime and nighttime. The LST is underestimated by the C6 MYD11 products at the four T-based sites during the daytime, with a mean bias of -2.82 K and a mean RMSE of 3.82 K, whereas the MYD21 LST product has a mean bias and RMSE of -0.51 and 2.53 K, respectively. The LST is also underestimated at night by the C6 MYD11 products at the four T-based sites, with a mean bias of -1.40 K and a mean RMSE of 1.72 K, whereas the MYD21 LST product has a mean bias and RMSE of 0.23 and 1.01 K, respectively. For the R-based validation, the MYD11 results are associated with large negative biases during both daytime and nighttime at three sand dune sites and biases within 1 K at the other seven sites, whereas the MYD21 results are more consistent at all ten sand dune sites, with a mean bias of 0.45 and 0.70 K for daytime and nighttime, respectively. The emissivities for these two products in MODIS bands 31 and 32 were compared with each other and then compared with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) emissivity and laboratory emissivity. The results indicate that the emissivities in MODIS bands 31 and 32 of MYD11 at the four T-based and three of the R-based validation sites are overestimated and result in LST underestimation, whereas the emissivities of MYD21 are more consistent with the laboratory emissivity. Besides, an experiment was carried out to demonstrate that the physically retrieved dynamic emissivity of the MYD21 product can be utilized to improve the accuracy of the split-window (SW) algorithm for barren surfaces, making it a valuable data source for retrieving LST from different remote sensing data.
Hua Li; Ruibo Li; Yikun Yang; Biao Cao; Zunjian Bian; Tian Hu; Yongming Du; Lin Sun; Qinhuo Liu. Temperature-Based and Radiance-Based Validation of the Collection 6 MYD11 and MYD21 Land Surface Temperature Products Over Barren Surfaces in Northwestern China. IEEE Transactions on Geoscience and Remote Sensing 2020, 59, 1794 -1807.
AMA StyleHua Li, Ruibo Li, Yikun Yang, Biao Cao, Zunjian Bian, Tian Hu, Yongming Du, Lin Sun, Qinhuo Liu. Temperature-Based and Radiance-Based Validation of the Collection 6 MYD11 and MYD21 Land Surface Temperature Products Over Barren Surfaces in Northwestern China. IEEE Transactions on Geoscience and Remote Sensing. 2020; 59 (2):1794-1807.
Chicago/Turabian StyleHua Li; Ruibo Li; Yikun Yang; Biao Cao; Zunjian Bian; Tian Hu; Yongming Du; Lin Sun; Qinhuo Liu. 2020. "Temperature-Based and Radiance-Based Validation of the Collection 6 MYD11 and MYD21 Land Surface Temperature Products Over Barren Surfaces in Northwestern China." IEEE Transactions on Geoscience and Remote Sensing 59, no. 2: 1794-1807.
Surface upward longwave radiation (SULR) is a critical component in the calculation of the Earth’s surface radiation budget. Multiple clear-sky SULR estimation methods have been developed for high-spatial resolution satellite observations. Here, we comprehensively evaluated six SULR estimation methods, including the temperature-emissivity physical methods with the input of the MYD11/MYD21 (TE-MYD11/TE-MYD21), the hybrid methods with top-of-atmosphere (TOA) linear/nonlinear/artificial neural network regressions (TOA-LIN/TOA-NLIN/TOA-ANN), and the hybrid method with bottom-of-atmosphere (BOA) linear regression (BOA-LIN). The recently released MYD21 product and the BOA-LIN—a newly developed method that considers the spatial heterogeneity of the atmosphere—is used initially to estimate SULR. In addition, the four hybrid methods were compared with simulated datasets. All the six methods were evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Surface Radiation Budget Network (SURFRAD) in situ measurements. Simulation analysis shows that the BOA-LIN is the best one among four hybrid methods with accurate atmospheric profiles as input. Comparison of all the six methods shows that the TE-MYD21 performed the best, with a root mean square error (RMSE) and mean bias error (MBE) of 14.0 and −0.2 W/m2, respectively. The RMSE of BOA-LIN, TOA-NLIN, TOA-LIN, TOA-ANN, and TE-MYD11 are equal to 15.2, 16.1, 17.2, 21.2, and 18.5 W/m2, respectively. TE-MYD21 has a much better accuracy than the TE-MYD11 over barren surfaces (NDVI < 0.3) and a similar accuracy over non-barren surfaces (NDVI ≥ 0.3). BOA-LIN is more stable over varying water vapor conditions, compared to other hybrid methods. We conclude that this study provides a valuable reference for choosing the suitable estimation method in the SULR product generation.
Boxiong Qin; Biao Cao; Hua Li; Zunjian Bian; Tian Hu; Yongming Du; Yingpin Yang; Qing Xiao; Qinhuo Liu. Evaluation of Six High-Spatial Resolution Clear-Sky Surface Upward Longwave Radiation Estimation Methods with MODIS. Remote Sensing 2020, 12, 1 .
AMA StyleBoxiong Qin, Biao Cao, Hua Li, Zunjian Bian, Tian Hu, Yongming Du, Yingpin Yang, Qing Xiao, Qinhuo Liu. Evaluation of Six High-Spatial Resolution Clear-Sky Surface Upward Longwave Radiation Estimation Methods with MODIS. Remote Sensing. 2020; 12 (11):1.
Chicago/Turabian StyleBoxiong Qin; Biao Cao; Hua Li; Zunjian Bian; Tian Hu; Yongming Du; Yingpin Yang; Qing Xiao; Qinhuo Liu. 2020. "Evaluation of Six High-Spatial Resolution Clear-Sky Surface Upward Longwave Radiation Estimation Methods with MODIS." Remote Sensing 12, no. 11: 1.
When ground-leaving radiance from low-temperature surface is similar to downwelling radiance from the sky, the singular values arise in the retrieved land surface emissivity (LSE) at some specific spectral bands. In addition, too many singular values eventually cause temperature/emissivity separation algorithms to fail. To reduce the occurrence of these singular points, we formulate two indices, including the land-atmosphere radiance contrast index (LACI) and neighbor band contrast index (NBCI). LACI characterizes the contrast between surface radiance and sky downwelling radiance. NBCI characterizes the contrast between the radiance at neighboring bands. These two indices are used as filters to select bands which participate in the iterative spectrally smooth calculation. Thus, we modify the iterative spectrally smooth temperature and emissivity separation (ISSTES) algorithm for low-temperature surfaces. Two methods have been used to evaluate the modified algorithm. First, numerical experiments are conducted to evaluate if the modified algorithm can accurately retrieve the ``true'' LSE from the simulated data. Second, an artificial low-temperature surface cooled by liquid nitrogen is measured to validate the modified algorithm. The results show that the modified algorithm can effectively avoid singular values, and behaves much better than the original algorithm with errors of less than 0.01 in retrieved emissivity when applied to low-temperature regions, while the modified algorithm brings limited improvement in retrieved temperature.
Yongming Du; Hua Li; Biao Cao; Zunjian Bian; Jianming Zhao; Qing Xiao; Qinhuo Liu; Yijian Zeng; Zhongbo Su. A Modified Interactive Spectral Smooth Temperature Emissivity Separation Algorithm for Low-Temperature Surface. IEEE Transactions on Geoscience and Remote Sensing 2020, 58, 7643 -7653.
AMA StyleYongming Du, Hua Li, Biao Cao, Zunjian Bian, Jianming Zhao, Qing Xiao, Qinhuo Liu, Yijian Zeng, Zhongbo Su. A Modified Interactive Spectral Smooth Temperature Emissivity Separation Algorithm for Low-Temperature Surface. IEEE Transactions on Geoscience and Remote Sensing. 2020; 58 (11):7643-7653.
Chicago/Turabian StyleYongming Du; Hua Li; Biao Cao; Zunjian Bian; Jianming Zhao; Qing Xiao; Qinhuo Liu; Yijian Zeng; Zhongbo Su. 2020. "A Modified Interactive Spectral Smooth Temperature Emissivity Separation Algorithm for Low-Temperature Surface." IEEE Transactions on Geoscience and Remote Sensing 58, no. 11: 7643-7653.
Land surface temperature (LST) is the direct driving force of turbulent heat fluxes at the surface and atmosphere interface and is widely used in the fields of evapotranspiration estimation (Su et al., 2002) and energy budget (Liang et al., 2019). Remote sensing products offer the only possibility for measuring LST with completely spatially averaged values. The thermal radiation directionality (TRD) effect has been widely concerned in the area of thermal infrared (TIR) remote sensing over 50 years which can lead to the directional brightness temperature (DBT) difference between different viewing directions up to 10 K (Cao et al., 2019). Many models have been proposed to simulate the DBT patterns over different underlying surfaces aimed to achieve the TRD effect correction for the satellite LST products. In practice, it is advised to handle only TRD models having a limited number of input parameters for operational normalization of LST products. The use of TIR kernel-driven models appears a good tradeoff between physical accuracy and operationality. It remains that the existing 4 TIR kernel-driven models (Ross-Li, LSF-Li, Vinnikov, RL) underestimate the hotspot effect, especially for continuous canopies. In this study, a new general framework of TIR kernel-driven modeling is proposed to overcome such issue. It is a linear combination of three kernels (including a base shape kernel, a hotspot kernel and an isotropic kernel) with the ability to simulate the bowl, dome and bell shapes in the solar principal plane. 4 specific models (Vinnikov-RL, LSF-RL, Vinnikov-Chen, LSF-Chen) within the new framework were further developed to assess their fitting abilities for both continuous and discrete vegetation canopies. To evaluate 4 existing models and 4 new models comprehensively, it was prepared 102 groups of 4SAIL/DART generated multi-angle datasets considering 6 different canopy architectures and 17 component temperatures. Results show that the 4 new models behave slightly better than the 4 existing models over discrete canopies (R2 increases from 0.791~0.989 to 0.976~0.996) whereas they significantly improved the fitting accuracy over continuous canopies (R2 increases from 0.661~0.970 to 0.940~0.997). The innovative new general framework with three kernels and four parameters improve the fitting ability significantly since the addition of one more degree of freedom. This new kernel-driven modeling framework is a potential tool to achieve angular correction of LST products.
Biao Cao; Qinhuo Liu; Yongming Du; Hua Li; Zunjian Bian; Tian Hu; Qing Xiao. A General Framework of Kernel-driven Modeling in the Thermal Infrared Band for Land Surface Temperature Normalization. 2020, 1 .
AMA StyleBiao Cao, Qinhuo Liu, Yongming Du, Hua Li, Zunjian Bian, Tian Hu, Qing Xiao. A General Framework of Kernel-driven Modeling in the Thermal Infrared Band for Land Surface Temperature Normalization. . 2020; ():1.
Chicago/Turabian StyleBiao Cao; Qinhuo Liu; Yongming Du; Hua Li; Zunjian Bian; Tian Hu; Qing Xiao. 2020. "A General Framework of Kernel-driven Modeling in the Thermal Infrared Band for Land Surface Temperature Normalization." , no. : 1.
Biao Cao; Qinhuo Liu; Yongming Du; Jean-Louis Roujean; Jean-Philippe Gastellu-Etchegorry; Isabel F. Trigo; Wenfeng Zhan; Yunyue Yu; Jie Cheng; Frederic Jacob; Jean-Pierre Lagouarde; Zunjian Bian; Hua Li; Tian Hu; Qing Xiao. A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives. Remote Sensing of Environment 2019, 232, 1 .
AMA StyleBiao Cao, Qinhuo Liu, Yongming Du, Jean-Louis Roujean, Jean-Philippe Gastellu-Etchegorry, Isabel F. Trigo, Wenfeng Zhan, Yunyue Yu, Jie Cheng, Frederic Jacob, Jean-Pierre Lagouarde, Zunjian Bian, Hua Li, Tian Hu, Qing Xiao. A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives. Remote Sensing of Environment. 2019; 232 ():1.
Chicago/Turabian StyleBiao Cao; Qinhuo Liu; Yongming Du; Jean-Louis Roujean; Jean-Philippe Gastellu-Etchegorry; Isabel F. Trigo; Wenfeng Zhan; Yunyue Yu; Jie Cheng; Frederic Jacob; Jean-Pierre Lagouarde; Zunjian Bian; Hua Li; Tian Hu; Qing Xiao. 2019. "A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives." Remote Sensing of Environment 232, no. : 1.
In this study, to improve the accuracy of land surface temperature (LST) products over barren surfaces, we present an operational algorithm to retrieve the LST from Moderate-Resolution Imaging Spectroradiometer (MODIS) thermal infrared data using physically retrieved emissivity products. The LST algorithm involved two steps. First, the emissivity in the two MODIS split-window (SW) channels was estimated using the vegetation cover method, with the bare soil component emissivity derived from the ASTER global emissivity data set. Then, the LST was retrieved using a modified generalized SW algorithm. This algorithm was implemented in the MUlti-source data SYnergized Quantitative (MuSyQ) remote sensing product system. The MuSyQ MODIS LST product and the Collection 6 MODIS LST product (MxD11_L2) were compared and validated using ground measurements collected from four barren surface sites in Northwest China during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) experiment from June 2012 to December 2015. In total, 2268 and 2715 clear-sky samples were used in the validation for Terra and Aqua, respectively. The evaluation results indicate that the MuSyQ LST products provide better accuracy than the C6 MxD11 product during both daytime and nighttime at all four sites. For the daytime results, the LST is underestimated by the C6 MxD11 products at all four sites, with a mean bias of -1.78 and -2.86 K and a mean root-mean-square error (RMSE) of 3.16 and 3.94 K for Terra and Aqua, respectively, whereas the mean biases of the MuSyQ LST products are within 1 K, with a mean bias of -0.26 and -1.03 K and a mean RMSE of 2.45 and 2.71 K for Terra and Aqua, respectively. For the nighttime results, the LST is also underestimated by the C6 MxD11 products at all four sites, with a mean bias of -1.60 and -1.26 K and a mean RMSE of 1.93 and 1.60 K for Terra and Aqua, respectively, whereas the mean biases of the MuSyQ LST products are 0.16 and 0.58 K and the mean RMSEs are 1.12 and 1.25 K for Terra and Aqua, respectively. The results indicate that the underestimation of the C6 MxD11 LST product at all four sites mainly results from the overestimation of the emissivities in MODIS bands 31 and 32. This study demonstrates that physically retrieved emissivity products are a useful source for LST retrieval over barren surfaces and can be used to improve the accuracy of global LST products.
Hua Li; Qinhuo Liu; Yikun Yang; Ruibo Li; Heshun Wang; Biao Cao; Zunjian Bian; Tian Hu; Yongming Du; Lin Sun. Comparison of the MuSyQ and MODIS Collection 6 Land Surface Temperature Products Over Barren Surfaces in the Heihe River Basin, China. IEEE Transactions on Geoscience and Remote Sensing 2019, 57, 8081 -8094.
AMA StyleHua Li, Qinhuo Liu, Yikun Yang, Ruibo Li, Heshun Wang, Biao Cao, Zunjian Bian, Tian Hu, Yongming Du, Lin Sun. Comparison of the MuSyQ and MODIS Collection 6 Land Surface Temperature Products Over Barren Surfaces in the Heihe River Basin, China. IEEE Transactions on Geoscience and Remote Sensing. 2019; 57 (10):8081-8094.
Chicago/Turabian StyleHua Li; Qinhuo Liu; Yikun Yang; Ruibo Li; Heshun Wang; Biao Cao; Zunjian Bian; Tian Hu; Yongming Du; Lin Sun. 2019. "Comparison of the MuSyQ and MODIS Collection 6 Land Surface Temperature Products Over Barren Surfaces in the Heihe River Basin, China." IEEE Transactions on Geoscience and Remote Sensing 57, no. 10: 8081-8094.
The land surface emissivity (LSE) in the MYD21 product contains the effects of viewing zenith angle. The influence of the angular variation of LSE on the surface upwelling longwave radiation (SULR) estimation is still unexplored at the satellite scale. We performed statistical analyses of MYD21 emissivity retrievals over different land surface types for three longwave bands centred around 8.55 μm (Band 29), 11 μm (Band 31) and 12 μm (Band 32), respectively. A look-up table was generated to describe the angular variations for both single-band and broadband emissivities. The results showed that the angular variation of directional emissivity in Band 29 could reach up to 0.03, but was <0.01 for Bands 31 and 32. The angular variation in broadband emissivity was intermediate to that for individual bands. In all cases, the directional emissivity was greatest and symmetric around nadir. By integrating the directional broadband emissivity, the influence of angular variation of the LSE on estimated SULR was quantified using simulation and measurements at seven stations from the US surface radiation budget network (SURFRAD). The difference between the directional and integrated hemispheric broadband emissivity was within 0.01. As a result, the influence of angular variation of LSE on the SULR estimation was modest. For the SURFRAD stations, the differences of root-mean-square error (RMSE) before and after considering the angular variation of LSE were generally <1 W m−2. We conclude that the angular variation of broadband emissivity is not pronounced because of the small linear weight for Band 29 in the calculation of broadband emissivity. Ignoring the anisotropy of emissivity does not introduce large errors in SULR estimation generally.
Tian Hu; Luigi J. Renzullo; Biao Cao; Albert Van Dijk; Yongming Du; Hua Li; Jie Cheng; Zhihong Xu; Jun Zhou; Qinhuo Liu. Directional variation in surface emissivity inferred from the MYD21 product and its influence on estimated surface upwelling longwave radiation. Remote Sensing of Environment 2019, 228, 45 -60.
AMA StyleTian Hu, Luigi J. Renzullo, Biao Cao, Albert Van Dijk, Yongming Du, Hua Li, Jie Cheng, Zhihong Xu, Jun Zhou, Qinhuo Liu. Directional variation in surface emissivity inferred from the MYD21 product and its influence on estimated surface upwelling longwave radiation. Remote Sensing of Environment. 2019; 228 ():45-60.
Chicago/Turabian StyleTian Hu; Luigi J. Renzullo; Biao Cao; Albert Van Dijk; Yongming Du; Hua Li; Jie Cheng; Zhihong Xu; Jun Zhou; Qinhuo Liu. 2019. "Directional variation in surface emissivity inferred from the MYD21 product and its influence on estimated surface upwelling longwave radiation." Remote Sensing of Environment 228, no. : 45-60.
This letter presents an experiment to explore the nonisothermal effects on temperature and emissivity separation (TES). The innovation of this experiment lies in its design, which highlights the contrast between isothermal and nonisothermal conditions in emissivity measurements. We artificially created a sharply contrasting nonisothermal soil surface using liquid nitrogen cooling and solar heating. The iterative spectrally smooth TES (ISSTES) algorithm was used to process the experimental data. The analyzed results of the experimental data show that the nonisothermal conditions have a significant effect on TES. The bias of retrieved emissivity increases with the component temperature difference as well as with wavelength. The bias around the split window band can reach up to 1% when the difference of the component temperature is 40K. Considering that 1% error in emissivity can cause approximately 1K error of retrieved land surface temperature (LST), the nonisothermal effects on emissivity cannot be ignored. We hope that this experiment will arouse attention of the nonisothermal effects on TES and call for more efforts to be devoted to this issue in the future.
Yongming Du; Biao Cao; Hua Li; Qing Xiao; Qinhuo Liu; Yijian Zeng; Zhongbo Su. An Experimental Study on Separating Temperature and Emissivity of a Nonisothermal Surface. IEEE Geoscience and Remote Sensing Letters 2019, 16, 1610 -1614.
AMA StyleYongming Du, Biao Cao, Hua Li, Qing Xiao, Qinhuo Liu, Yijian Zeng, Zhongbo Su. An Experimental Study on Separating Temperature and Emissivity of a Nonisothermal Surface. IEEE Geoscience and Remote Sensing Letters. 2019; 16 (10):1610-1614.
Chicago/Turabian StyleYongming Du; Biao Cao; Hua Li; Qing Xiao; Qinhuo Liu; Yijian Zeng; Zhongbo Su. 2019. "An Experimental Study on Separating Temperature and Emissivity of a Nonisothermal Surface." IEEE Geoscience and Remote Sensing Letters 16, no. 10: 1610-1614.
Many physical models have been proposed to simulate the directional anisotropy in the thermal infrared (TIR) region over vegetation canopies to produce angular corrected directional brightness temperature or land surface temperature. However, too many input parameters obstruct their operational use. Semiempirical kernel-driven models are designed to be a tradeoff between physical accuracy and operationality. Recently, four kernel-driven models have been proposed: the first two are direct extensions of kernel models in the visible- and near-infrared region and the last two were directly designed for the TIR region. In this paper, 153 continuous and 153 discrete canopies with varying structures and temperature distributions were considered in order to evaluate their accuracies against two physical models (4SAIL and DART). Their error distribution, scatterplots, and directional anisotropy patterns are compared. LSF-Li model, followed by Ross-Li, Vinnikov, and RL model, gave the best fitting results for all the scenes. The R² of all four kernel models can reach up to 0.82 for discrete scenes; however, the kernel-driven models underestimate the hotspot effect from continuous scenes; therefore, further improvements are necessary for operational use with future TIR satellite missions.
Biao Cao; Jean-Philippe Gastellu-Etchegorry; Yongming Du; Hua Li; Zunjian Bian; Tian Hu; Wenjie Fan; Qing Xiao; Qinhuo Liu. Evaluation of Four Kernel-Driven Models in the Thermal Infrared Band. IEEE Transactions on Geoscience and Remote Sensing 2019, 57, 5456 -5475.
AMA StyleBiao Cao, Jean-Philippe Gastellu-Etchegorry, Yongming Du, Hua Li, Zunjian Bian, Tian Hu, Wenjie Fan, Qing Xiao, Qinhuo Liu. Evaluation of Four Kernel-Driven Models in the Thermal Infrared Band. IEEE Transactions on Geoscience and Remote Sensing. 2019; 57 (8):5456-5475.
Chicago/Turabian StyleBiao Cao; Jean-Philippe Gastellu-Etchegorry; Yongming Du; Hua Li; Zunjian Bian; Tian Hu; Wenjie Fan; Qing Xiao; Qinhuo Liu. 2019. "Evaluation of Four Kernel-Driven Models in the Thermal Infrared Band." IEEE Transactions on Geoscience and Remote Sensing 57, no. 8: 5456-5475.
Mingzhu Guo; Biao Cao; Wenjie Fan; Huazhong Ren; Yaokui Cui; Yongming Du; Qinhuo Liu. Scattering Effect Contributions to the Directional Canopy Emissivity and Brightness Temperature Based on CE-P and CBT-P Models. IEEE Geoscience and Remote Sensing Letters 2019, 1 -5.
AMA StyleMingzhu Guo, Biao Cao, Wenjie Fan, Huazhong Ren, Yaokui Cui, Yongming Du, Qinhuo Liu. Scattering Effect Contributions to the Directional Canopy Emissivity and Brightness Temperature Based on CE-P and CBT-P Models. IEEE Geoscience and Remote Sensing Letters. 2019; ():1-5.
Chicago/Turabian StyleMingzhu Guo; Biao Cao; Wenjie Fan; Huazhong Ren; Yaokui Cui; Yongming Du; Qinhuo Liu. 2019. "Scattering Effect Contributions to the Directional Canopy Emissivity and Brightness Temperature Based on CE-P and CBT-P Models." IEEE Geoscience and Remote Sensing Letters , no. : 1-5.
A new directional canopy emissivity model (CE-P) based on spectral invariants is proposed in this paper. First, we prove the existence of the spectral invariant properties in the thermal infrared (TIR) band using a Monte Carlo model. Based on it, the equation of the new model is derived from the perspective of absorption. In this expression, single-scattering and multiscattering effects are separated analytically in the TIR band. We find that the overall contribution of multiple scatterings is less than 0.005 when the component emissivities are over 0.90, and the overall contribution decreases with increasing leaf or soil emissivity. Furthermore, the new model can avoid the logical difficulty encountered when using the traditional cavity effect factor to simulate the emissivity of a sparse vegetation canopy. The results of 4SAIL and Discrete Anisotropic Radiative Transfer (DART) are selected to do cross validation. The CE-P can achieve a high accuracy compared with 4SAIL and DART, with an absolute bias less than 0.002 when the leaf (soil) emissivity is equal to 0.98 (0.94). Four widely used analytical models are selected for comparison. The resulting accuracies of these models are ordered from CE-P to REN15, FR97, FR02, and VALOR96 with the most serious error up to 0.002, 0.002, 0.007, 0.013, and 0.014, respectively. Three main conclusions are obtained through the sensitivity analysis: the multiscattering between vegetation and the background can be ignored when the leaf (soil) emissivity is no less than 0.94 (0.90), the second and higher order scattering within the vegetation can also be ignored when the leaf (soil) emissivity is no less than 0.94 (0.90), and the single-scattering effect within the canopy should be considered which can be calculated using three view factors.
Biao Cao; Mingzhu Guo; Wenjie Fan; Xiru Xu; Jingjing Peng; Huazhong Ren; Yongming Du; Hua Li; Zunjian Bian; Tian Hu; Qing Xiao; Qinhuo Liu. A New Directional Canopy Emissivity Model Based on Spectral Invariants. IEEE Transactions on Geoscience and Remote Sensing 2018, 56, 6911 -6926.
AMA StyleBiao Cao, Mingzhu Guo, Wenjie Fan, Xiru Xu, Jingjing Peng, Huazhong Ren, Yongming Du, Hua Li, Zunjian Bian, Tian Hu, Qing Xiao, Qinhuo Liu. A New Directional Canopy Emissivity Model Based on Spectral Invariants. IEEE Transactions on Geoscience and Remote Sensing. 2018; 56 (12):6911-6926.
Chicago/Turabian StyleBiao Cao; Mingzhu Guo; Wenjie Fan; Xiru Xu; Jingjing Peng; Huazhong Ren; Yongming Du; Hua Li; Zunjian Bian; Tian Hu; Qing Xiao; Qinhuo Liu. 2018. "A New Directional Canopy Emissivity Model Based on Spectral Invariants." IEEE Transactions on Geoscience and Remote Sensing 56, no. 12: 6911-6926.
Multi-angle information extraction is very important for the validation of land surface models, such as bi-directional reflectance distribution function (BRDF) model and directional brightness temperature (DBT) model. The experiment can be done in the near surface, on the plane, and on the satellite. The spatial-temporal average method is widely-used on the scale of plane. In this paper, we try to extend it to extract the multi-angle information from near surface observation sensors. We found this method can obtain good result over homogeneous land surface, but the observation protocol is critical over heterogeneous land surface. For instance, the observation plane should be perpendicular to the row direction. In addition, we found that the hot spot area will be shaded by the observation platform which leads to the BRDF result to be affected seriously.
Biao Cao; Zunjian Bian; Qing Xiao; Junyong Fang; Huaguo Huang; Junhua Bai; Wenjie Fan; Yongming Du; Hua Li; Qinhuo Liu. Evaluation the Spatial-Temporal Average Method in the Multi-Angle Information Extraction Based on Near Surface Observation Sensors. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium 2018, 9222 -9225.
AMA StyleBiao Cao, Zunjian Bian, Qing Xiao, Junyong Fang, Huaguo Huang, Junhua Bai, Wenjie Fan, Yongming Du, Hua Li, Qinhuo Liu. Evaluation the Spatial-Temporal Average Method in the Multi-Angle Information Extraction Based on Near Surface Observation Sensors. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. 2018; ():9222-9225.
Chicago/Turabian StyleBiao Cao; Zunjian Bian; Qing Xiao; Junyong Fang; Huaguo Huang; Junhua Bai; Wenjie Fan; Yongming Du; Hua Li; Qinhuo Liu. 2018. "Evaluation the Spatial-Temporal Average Method in the Multi-Angle Information Extraction Based on Near Surface Observation Sensors." IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium , no. : 9222-9225.
In this paper, we proposed a temperature and emissivity separation (TES) algorithm for the simultaneous retrieval of land surface temperature and emissivity (LST&E) from the thermal infrared data of Chinese GaoFen-5 (GF-5) satellite's Multiple Spectral-Imager (MSI) payload. In order to improve the accuracy of the TES algorithm, a water vapor scaling (WVS) method for atmospheric correction was adopted. The Seebor V5.0 global atmospheric profile database and MODTRAN 5 were used to simulate the WVS coefficients. A total of 11 ASTER scenes were used to simulate the MSI images and concurrent ground measurements acquired in the HiW ATER experiment were used to validate the algorithm. The results showed that the bias and root mean square error (RMSE) in the retrieved LST were 0.47 K and 1.70 K, respectively, and the absolute emissivity differences between MSI and the ground measurements were smaller than 0.01 for the four MSI TIR bands, which demonstrated that the proposed algorithm can be used to retrieve high accurate and high spatial resolution LST&E from GF-5 MSI data.
Yikun Yang; Hua Li; Yongming Du; Biao Cao; Qinhuo Liu; Lin Sun; Jinshan Zhu; Fan Mo. A Temperature and Emissivity Separation Algortihm for Chinese Gaofen-5 Satelltie Data. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium 2018, 2543 -2546.
AMA StyleYikun Yang, Hua Li, Yongming Du, Biao Cao, Qinhuo Liu, Lin Sun, Jinshan Zhu, Fan Mo. A Temperature and Emissivity Separation Algortihm for Chinese Gaofen-5 Satelltie Data. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. 2018; ():2543-2546.
Chicago/Turabian StyleYikun Yang; Hua Li; Yongming Du; Biao Cao; Qinhuo Liu; Lin Sun; Jinshan Zhu; Fan Mo. 2018. "A Temperature and Emissivity Separation Algortihm for Chinese Gaofen-5 Satelltie Data." IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium , no. : 2543-2546.
A new directional canopy emissivity model (CE-P) based on spectral invariants can separate the multiple scattering effect and single scattering in vegetation canopy. So we can further evaluate the contribution of scattering effect to the canopy emissivity and brightness temperature based on CE-P model. Numerical analysis shows that the contribution of more than three times scattering can be ignored when the leaf (soil) emissivity is no less than 0.90. Then, we optimize CE-P model and obtain the expressions containing the first twice collisions (ε2) and first three times collisions (ε3). The result shows that ε3 can simulate the emissivity in any case with an error less than 0.001. Furthermore, we simulate the brightness temperature distribution using the optimized model and compare it with DART model. The difference between them is less than 0.3K and the R 2 of them is over 0.96 in all of the selected samples.
Mingzhu Guo; Biao Cao; Wenjie Fan; Huazhong Ren; Yaokui Cui; Yongming Du; Qinhuo Liu. Evaluation the Contribution of Scattering Effect to the Directional Canopy Emissivity and Brightness Temperature Simulation Based on CE-P Model. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium 2018, 5485 -5488.
AMA StyleMingzhu Guo, Biao Cao, Wenjie Fan, Huazhong Ren, Yaokui Cui, Yongming Du, Qinhuo Liu. Evaluation the Contribution of Scattering Effect to the Directional Canopy Emissivity and Brightness Temperature Simulation Based on CE-P Model. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. 2018; ():5485-5488.
Chicago/Turabian StyleMingzhu Guo; Biao Cao; Wenjie Fan; Huazhong Ren; Yaokui Cui; Yongming Du; Qinhuo Liu. 2018. "Evaluation the Contribution of Scattering Effect to the Directional Canopy Emissivity and Brightness Temperature Simulation Based on CE-P Model." IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium , no. : 5485-5488.
In this study, two latest Collection 6 (C6) MODIS level-2 LST products (MxD11_L2 and MxD21_L2) from both the Terra and Aqua satellites were evaluated against ground measurements collected in an arid area of northwest China during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) experiment. Ground measurements of four and a half years at four barren surface sites were used to carry out the evaluation, which took place from June 2012 to December 2016. The results show that the C6 MxD21 LST products demonstrate a better accuracy than C6 MxD11 LSTproducts both at daytime and nighttime for the four sites. For the daytime result, C6 MxD11 products underestimate the LST at the four barren surface sites, with an average bias of -1.77 K for Terra and -2.63 K for Aqua, while the average biases of MxD21 LST products are much smaller, with an average bias of 0.34 K for Terra and -0.67 K for Aqua, respectively. For the nighttime result, C6 MxD11 products also underestimate the LST at the four sites, with an average bias of -1.41 K for Terra and -1.01 K for Aqua, while the average biases of K LST products are 0.14 K for Terra and 0.54 K for Aqua, respectively.
Hua Li; Yikun Yang; Yongming Du; Biao Cao; Qinhuo Liu. Preliminary Evaluation of the Two Collection 6 Modis Land Surface Temperature Products in an Arid Area of Northwest China. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium 2018, 2531 -2534.
AMA StyleHua Li, Yikun Yang, Yongming Du, Biao Cao, Qinhuo Liu. Preliminary Evaluation of the Two Collection 6 Modis Land Surface Temperature Products in an Arid Area of Northwest China. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. 2018; ():2531-2534.
Chicago/Turabian StyleHua Li; Yikun Yang; Yongming Du; Biao Cao; Qinhuo Liu. 2018. "Preliminary Evaluation of the Two Collection 6 Modis Land Surface Temperature Products in an Arid Area of Northwest China." IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium , no. : 2531-2534.