Retrieving Sun-Induced Chlorophyll Fluorescence from Hyperspectral Data with TanSat Satellite.

A series of algorithms for satellite retrievals of sun-induced chlorophyll fluorescence (SIF) have been developed and applied to different sensors. However, research on SIF retrieval using hyperspectral data is performed in narrow spectral windows, assuming that SIF remains constant. In this paper, based on the singular vector decomposition (SVD) technique, we present an approach for retrieving SIF, which can be applied to remotely sensed data with ultra-high spectral resolution and in a broad spectral window without assuming that the SIF remains constant. The idea is to combine the first singular vector, the pivotal information of the non-fluorescence spectrum, with the low-frequency contribution of the atmosphere, plus a linear combination of the remaining singular vectors to express the non-fluorescence spectrum. Subject to instrument settings, the retrieval was performed within a spectral window of approximately 7 nm that contained only Fraunhofer lines. In our retrieval, hyperspectral data of the O2-A band from the first Chinese carbon dioxide observation satellite (TanSat) was used. The Bayesian Information Criterion (BIC) was introduced to self-adaptively determine the number of free parameters and reduce retrieval noise. SIF retrievals were compared with TanSat SIF and OCO-2 SIF. The results showed good consistency and rationality. A sensitivity analysis was also conducted to verify the performance of this approach. To summarize, the approach would provide more possibilities for retrieving SIF from hyperspectral data.

Small molecular modulators of JMJD1C preferentially inhibit growth of leukemia cells.

Histone demethylases are promising therapeutic targets as they play fundamental roles for survival of Mixed lineage leukemia rearranged acute leukemia (MLLr AL). Here we focused on the catalytic Jumonji domain of histone H3 lysine 9 (H3K9) demethylase JMJD1C to screen for potential small molecular modulators from 149,519 natural products and 33,765 Chinese medicine components via virtual screening. JMJD1C Jumonji domain inhibitor 4 (JDI-4) and JDI-12 that share a common structural backbone were detected within the top 15 compounds. Surface plasmon resonance analysis showed that JDI-4 and JDI-12 bind to JMJD1C and its family homolog KDM3B with modest affinity. In vitro demethylation assays showed that JDI-4 can reverse the H3K9 demethylation conferred by KDM3B. In vivo demethylation assays indicated that JDI-4 and JDI-12 could induce the global increase of H3K9 methylation. Cell proliferation and colony formation assays documented that JDI-4 and JDI-12 kill MLLr AL and other malignant hematopoietic cells, but not leukemia cells resistant to JMJD1C depletion or cord blood cells. Furthermore, JDI-16, among multiple compounds structurally akin to JDI-4/JDI-12, exhibits superior killing activities against malignant hematopoietic cells compared to JDI-4/JDI-12. Mechanistically, JDI-16 not only induces apoptosis but also differentiation of MLLr AL cells. RNA sequencing and quantitative PCR showed that JDI-16 induced gene expression associated with cell metabolism; targeted metabolomics revealed that JDI-16 downregulates lactic acids, NADP+ and other metabolites. Moreover, JDI-16 collaborates with all-trans retinoic acid to repress MLLr AML cells. In summary, we identified bona fide JMJD1C inhibitors that induce preferential death of MLLr AL cells.

An Improved Linear Spectral Emissivity Constraint Method for Temperature and Emissivity Separation Using Hyperspectral Thermal Infrared Data.

The linear spectral emissivity constraint (LSEC) method has been proposed to separate temperature and emissivity in hyperspectral thermal infrared data with an assumption that land surface emissivity (LSE) can be described by an equal interval piecewise linear function. This paper combines a pre-estimate shape method with the LSEC method to provide an initial-shape estimation of LSE which will create a new piecewise scheme for land surface temperature (LST) and LSE separation. This new scheme is designated as the pre-estimate shape (PES)-LSEC method. Comparisons with the LSEC method using simulated data sets show that the PES-LSEC method has better performance in terms of accuracy for both LSE and LST. With an at-ground error of 0.5 K, the root-mean-square errors (RMSEs) of LST and LSE are 0.07 K and 0.0045, respectively, and with the scale factor of moisture profile 0.8 and 1.2, the RMSEs of LST are 1.11 K and 1.14 K, respectively. The RMSEs of LSE in each channel are mostly below 0.02 and 0.04, respectively, which are better than for the LSEC method. In situ experimental data are adopted to validate our method: The results show that RMSE of LST is 0.9 K and the mean value of LSE accuracy is 0.01. The PES-LSEC method with fewer segments achieves better accuracy than that of LSEC and preserves most of the crest and trough information of emissivity.

Deep Learning Convolutional Neural Network for the Retrieval of Land Surface Temperature from AMSR2 Data in China.

A convolutional neural network (CNN) algorithm was developed to retrieve the land surface temperature (LST) from Advanced Microwave Scanning Radiometer 2 (AMSR2) data in China. Reference data were selected using the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product to overcome the problem related to the need for synchronous ground observation data. The AMSR2 brightness temperature (TB) data and MODIS surface temperature data were randomly divided into training and test datasets, and a CNN was constructed to simulate passive microwave radiation transmission to invert the surface temperature. The twelve V/H channel combinations (7.3, 10.65, 18.7, 23.8, 36.5, 89 GHz) resulted in the most stable and accurate CNN retrieval model. Vertical polarizations performed better than horizontal polarizations; however, because CNNs rely heavily on large amounts of data, the combination of vertical and horizontal polarizations performed better than a single polarization. The retrievals in different regions indicated that the CNN accuracy was highest over large bare land areas. A comparison of the retrieval results with ground measurement data from meteorological stations yielded R2 = 0.987, RMSE = 2.69 K, and an average relative error of 2.57 K, which indicated that the accuracy of the CNN LST retrieval algorithm was high and the retrieval results can be applied to long-term LST sequence analysis in China.

Efficacy and safety of Helicobacter pylori eradication therapy immediately after endoscopic submucosal dissection.

BACKGROUND AND AIMS: In the treatment of patients after endoscopic submucosal dissection (ESD), there is no consensus on the optimum time to start Helicobacter pylori eradication therapy or on whether eradication therapy improves ulcer healing rate after ESD. The aim of this study was to examine the effect of immediate eradication of H. pylori on ulcer healing after ESD in patients with early gastric neoplasms. METHODS: A total of 330 patients who underwent ESD for early gastric neoplasms were enrolled. Patients were assigned to either H. pylori eradication group (Group A: H. pylori eradication + proton pump inhibitor 7 weeks) or non-eradication group (Group B: proton pump inhibitor 8 weeks). The primary end point was gastric ulcer healing rate (Group A vs Group B) determined on week 8 after ESD. RESULTS: Patients in Group A failed to meet non-inferiority criteria for ulcer scarring rate after ESD compared with that in Group B (83.0% vs 86.5%, P for non-inferiority = 0.0599, 95% confidence interval: -11.7% to 4.7%). There were, however, neither large differences between the two groups in the ulcer scarring rate nor the safety profile. CONCLUSIONS: This study failed to demonstrate the non-inferiority of immediate H. pylori eradication therapy after ESD to the non-eradication therapy in the healing rate of ESD-caused ulcers. However, because the failure is likely to attribute to small number of patients enrolled, immediate eradication therapy may be a treatment option for patients after ESD without adverse effects on eradication therapy in comparison with the standard therapy.

Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach.

Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty.

Intercomparison on Four Irrigated Cropland Maps in Mainland China.

Wide-coverage spatial information on irrigated croplands is a vital foundation for food security and water resources studies at the regional level. Several global irrigated-cropland maps have been released to the public over the past decade due to the efforts of the remote sensing community. However, the consistency and discrepancy between these maps is largely unknown because of a lack of comparative studies, limiting their use and improvement. To close this knowledge gap, we compared the latest four irrigated-cropland datasets (GMIA, GRIPC, GlobCover, and GFSAD) in mainland China. First, the four maps were compared quantitatively and neutral regional- and provincial-level statistics of the relative proportions of irrigated land were obtained through regression analysis. Second, we compared the similarities and discrepancies of the datasets on spatial grids. Furthermore, the contributions of mosaic cropland pixels in GlobCover and GFSAD were also analyzed because of their extensive distribution and ambiguous content. Results showed that GMIA has the lowest dispersion and best statistical correlation followed by GRIPC, while the corresponding features of GlobCover and GFSAD are approximately equal. Spatial agreement of the four maps is higher in eastern than western China, and disagreement is contributed mostly by GlobCover and GFSAD. However, divergence exists in the ratios of the different agreement levels, as well as their sources, on a regional scale. Mosaic pixels provide more than half of the irrigated areas for GlobCover and GFSAD, and they include both correct and incorrect information. Our results indicate a need for a uniform quantitative classification system and for greater focus on heterogeneous regions. Furthermore, the results demonstrate the advantage of numerical restriction in the calculations. Therefore, special attention should be paid to integrating databases and to exploring remote sensing features and methods for spatial reconstruction and identification of untypical irrigation areas.

[A new aurone with anti-inflammatory activity from Cleistocalyx operculatus flower buds].

A new compound(Z)-6-hydroxy-4-methoxy-5,7-dimethylaurone was isolated from Cleistocalyx operculatus flower buds. Its structure was identified by spectroscopic data including MS, ¹H-NMR, ¹³C-NMR HSQC and HMBC. A known compound, 2',4'-dihydroxy-6'-methoxy-3'5'-dimethylchalcone (DMC), was also isolated and identified,and used as material to synthesize (Z)-6-hydroxy-4-methoxy-5,7-dimethylaurone.Anti-inflammatory activities of the two compounds were tested in vitro. The results showed that (Z)-6-hydroxy-4-methoxy-5,7-dimethylaurone possesses much stronger PGE2 inhibitory activity (IC50 6.12 nmol·L⁻¹) than the positive control ibuprofen （68.66 nmol·L⁻¹ï¼‰.

Atmospheric correction for retrieving ground brightness temperature at commonly-used passive microwave frequencies.

An analysis of the atmospheric impact on ground brightness temperature (Tg) is performed for numerous land surface types at commonly-used frequencies (i.e., 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz and 89.0 GHz). The results indicate that the atmosphere has a negligible impact on Tg at 1.4 GHz for land surfaces with emissivities greater than 0.7, at 6.93 GHz for land surfaces with emissivities greater than 0.8, and at 10.65 GHz for land surfaces with emissivities greater than 0.9 if a root mean square error (RMSE) less than 1 K is desired. To remove the atmospheric effect on Tg, a generalized atmospheric correction method is proposed by parameterizing the atmospheric transmittance τ and upwelling atmospheric brightness temperature Tba↑. Better accuracies with Tg RMSEs less than 1 K are achieved at 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz and 36.5 GHz, and worse accuracies with RMSEs of 1.34 K and 4.35 K are obtained at 23.8 GHz and 89.0 GHz, respectively. Additionally, a simplified atmospheric correction method is developed when lacking sufficient input data to perform the generalized atmospheric correction method, and an emissivity-based atmospheric correction method is presented when the emissivity is known. Consequently, an appropriate atmospheric correction method can be selected based on the available data, frequency and required accuracy. Furthermore, this study provides a method to estimate τ and Tba↑ of different frequencies using the atmospheric parameters (total water vapor content in observation direction Lwv, total cloud liquid water content Lclw and mean temperature of cloud Tclw), which is important for simultaneously determining the land surface parameters using multi-frequency passive microwave satellite data.

New method to estimate surface upwelling long-wave radiation from MODIS cloud-free data.

As an important component in the surface radiation budget, surface upwelling longwave radiation (SULR) is an outcome of the land surface energy exchange and mainly represents the capability of thermal radiation from the surface of the Earth. Existing satellite-derived SULR products are too coarse to support high-resolution numerical models, and their accuracy needs to be improved. In this study, an equivalent temperature is introduced through which a "split-window" atmospheric correction algorithm is developed for MODIS data to estimate the instantaneous clear-sky SULR. It is a simple and feasible method that is particularly applicable to MODIS data to acquire relatively high precision SULR under clear skies from which qualified water vapor contents (WVC) and thermal channel brightness temperatures are available. The root mean square errors (RMSEs) are less than 13 W/m2 for all WVC sub-ranges with the viewing zenith angle (VZA) less than 30°, or for all sub-ranges with the VZA less than 60° and the WVC less than 3.5 g/cm2. Also, applications and comparisons with the LST-emissivity method are made by using ground measurements which are collected from the network of surface radiation budget network data (SURFRAD) at the moment of MODIS overpass. Results show that the proposed model has high computational efficiency to estimate SULR from MODIS cloud-free data.

Discovery of acylguanidine oseltamivir carboxylate derivatives as potent neuraminidase inhibitors.

In search of novel anti-influenza agents with higher potency, a series of acylguanidine oseltamivir carboxylate analogues were synthesized and evaluated against influenza viruses (H1N1 and H3N2) in vitro. The representative compounds with strong inhibitory activities (IC50 <40nM) against neuraminidase (NA) were further tested against the NA from oseltamivir-resistant strain (H259Y). Among them, compounds 9 and 17 were potent NA inhibitors that exhibited a 5 and 11-fold increase in activity comparing with oseltamivir carboxylate (2, OC) against the H259Y mutant, respectively. Furthermore, the effect against influenza virus H259Y mutant (H1N1) replication and cytotoxicity assays indicated that compounds 9 and 17 exhibited a 20 and 6-fold increase than the parent compound 2, and had no obvious cytotoxicity in vitro. Moreover, the molecular docking studies revealed that the docking modes of compounds 9 and 17 were different from that of oseltamivir, and the new hydrogen bonds and hydrophobic interaction were formed in this case. This work provided unique insights in the discovery of potent inhibitors against NAs from wild-type and oseltamivir-resistant strains.

Domain-specific c-Myc ubiquitylation controls c-Myc transcriptional and apoptotic activity.

The oncogenic transcription factor c-Myc causes transformation and tumorigenesis, but it can also induce apoptotic cell death. Although tumor suppressors are necessary for c-Myc to induce apoptosis, the pathways and mechanisms are unclear. To further understand how c-Myc switches from an oncogenic protein to an apoptotic protein, we examined the mechanism of p53-independent c-Myc-induced apoptosis. We show that the tumor suppressor protein ARF mediates this switch by inhibiting ubiquitylation of the c-Myc transcriptional domain (TD). Whereas TD ubiquitylation is critical for c-Myc canonical transcriptional activity and transformation, inhibition of ubiquitylation leads to the induction of the noncanonical c-Myc target gene, Egr1, which is essential for efficient c-Myc-induced p53-independent apoptosis. ARF inhibits the interaction of c-Myc with the E3 ubiquitin ligase Skp2. Overexpression of Skp2, which occurs in many human tumors, inhibits the recruitment of ARF to the Egr1 promoter, leading to inhibition of c-Myc-induced apoptosis. Therapeutic strategies could be developed to activate this intrinsic apoptotic activity of c-Myc to inhibit tumorigenesis.

Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method.

Land Surface Temperature (LST) is a key parameter in climate systems. The methods for retrieving LST from hyperspectral thermal infrared data either require accurate atmospheric profile data or require thousands of continuous channels. We aim to retrieve LST for natural land surfaces from hyperspectral thermal infrared data using an adapted multi-channel method taking Land Surface Emissivity (LSE) properly into consideration. In the adapted method, LST can be retrieved by a linear function of 36 brightness temperatures at Top of Atmosphere (TOA) using channels where LSE has high values. We evaluated the adapted method using simulation data at nadir and satellite data near nadir. The Root Mean Square Error (RMSE) of the LST retrieved from the simulation data is 0.90 K. Compared with an LST product from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat, the error in the LST retrieved from the Infared Atmospheric Sounding Interferometer (IASI) is approximately 1.6 K. The adapted method can be used for the near-real-time production of an LST product and to provide the physical method to simultaneously retrieve atmospheric profiles, LST, and LSE with a first-guess LST value. The limitations of the adapted method are that it requires the minimum LSE in the spectral interval of 800-950 cm(-1) larger than 0.95 and it has not been extended for off-nadir measurements.

Investigation of Atmospheric Effects on Retrieval of Sun-Induced Fluorescence Using Hyperspectral Imagery.

Significant research progress has recently been made in estimating fluorescence in the oxygen absorption bands, however, quantitative retrieval of fluorescence data is still affected by factors such as atmospheric effects. In this paper, top-of-atmosphere (TOA) radiance is generated by the MODTRAN 4 and SCOPE models. Based on simulated data, sensitivity analysis is conducted to assess the sensitivities of four indicators-depth_absorption_band, depth_nofs-depth_withfs, radiance and Fs/radiance-to atmospheric parameters (sun zenith angle (SZA), sensor height, elevation, visibility (VIS) and water content) in the oxygen absorption bands. The results indicate that the SZA and sensor height are the most sensitive parameters and that variations in these two parameters result in large variations calculated as the variation value/the base value in the oxygen absorption depth in the O2-A and O2-B bands (111.4% and 77.1% in the O2-A band; and 27.5% and 32.6% in the O2-B band, respectively). A comparison of fluorescence retrieval using three methods (Damm method, Braun method and DOAS) and SCOPE Fs indicates that the Damm method yields good results and that atmospheric correction can improve the accuracy of fluorescence retrieval. Damm method is the improved 3FLD method but considering atmospheric effects. Finally, hyperspectral airborne images combined with other parameters (SZA, VIS and water content) are exploited to estimate fluorescence using the Damm method and 3FLD method. The retrieval fluorescence is compared with the field measured fluorescence, yielding good results (R² = 0.91 for Damm vs. SCOPE SIF; R² = 0.65 for 3FLD vs. SCOPE SIF). Five types of vegetation, including ailanthus, elm, mountain peach, willow and Chinese ash, exhibit consistent associations between the retrieved fluorescence and field measured fluorescence.

Non-Contact Measurement of the Spectral Emissivity through Active/Passive Synergy of CO2 Laser at 10.6 µm and 102F FTIR (Fourier Transform Infrared) Spectrometer.

In the inversion of land surface temperature (LST) from satellite data, obtaining the information on land surface emissivity is most challenging. How to solve both the emissivity and the LST from the underdetermined equations for thermal infrared radiation is a hot research topic related to quantitative thermal infrared remote sensing. The academic research and practical applications based on the temperature-emissivity retrieval algorithms show that directly measuring the emissivity of objects at a fixed thermal infrared waveband is an important way to close the underdetermined equations for thermal infrared radiation. Based on the prior research results of both the authors and others, this paper proposes a new approach of obtaining the spectral emissivity of the object at 8-14 µm with a single-band CO2 laser at 10.6 µm and a 102F FTIR spectrometer. Through experiments, the spectral emissivity of several key samples, including aluminum plate, iron plate, copper plate, marble plate, rubber sheet, and paper board, at 8-14 µm is obtained, and the measured data are basically consistent with the hemispherical emissivity measurement by a Nicolet iS10 FTIR spectrometer for the same objects. For the rough surface of materials, such as marble and rusty iron, the RMSE of emissivity is below 0.05. The differences in the field of view angle and in the measuring direction between the Nicolet FTIR method and the method proposed in the paper, and the heterogeneity in the degree of oxidation, polishing and composition of the samples, are the main reasons for the differences of the emissivities between the two methods.

Performance evaluation of four directional emissivity analytical models with thermal SAIL model and airborne images.

Land surface emissivity is a crucial parameter in the surface status monitoring. This study aims at the evaluation of four directional emissivity models, including two bi-directional reflectance distribution function (BRDF) models and two gap-frequency-based models. Results showed that the kernel-driven BRDF model could well represent directional emissivity with an error less than 0.002, and was consequently used to retrieve emissivity with an accuracy of about 0.012 from an airborne multi-angular thermal infrared data set. Furthermore, we updated the cavity effect factor relating to multiple scattering inside canopy, which improved the performance of the gap-frequency-based models.

Circulating irisin is lower in gestational diabetes mellitus.

Irisin is a newly identified myokine. Several studies have reported irisin concentrations in patients with gestational diabetes mellitus (GDM), but because of smaller sample sizes, the data from previous reports showed a wide range in serum/plasma irisin. Therefore, the present investigation is designed to summarize a precise confidence interval of circulating irisin in participants with GDM from a cross-sectional study in Chinese population and a meta-analysis for validation. Serum irisin was tested in patients with GDM and healthy controls (newly diagnosed cases: 61 and matched controls: 61) in the cross-sectional study. The two groups of participants were matched for age and pregnancy duration. Furthermore, we did a comprehensive meta-analysis to confirm whether serum/plasma irisin differs between participants with GDM and controls. Articles reported "circulating irisin and GDM" in Medline, PubMed, and EMBase were obtained, with the key word "myokine" or "irisin". The comparison was analyzed by Review Manager 5.2. In the cross-sectional investigation, serum irisin showed a significant lower level in the GDM patients, compared with that in the control group. In the meta-analysis study, the summarized results of the present 5 studies in which 632 participants were included indicated that there was a lower level irisin of -58.68 ng/mL [95% confidence interval (CI)](-113.42, -3.93, P=0.04) in GDM patients than in the control group. The present cross-sectional investigation and meta-analysis is the first to show significant lower circulating irisin in subjects with GDM.

Daytime Land Surface Temperature Extraction from MODIS Thermal Infrared Data under Cirrus Clouds.

Simulated data showed that cirrus clouds could lead to a maximum land surface temperature (LST) retrieval error of 11.0 K when using the generalized split-window (GSW) algorithm with a cirrus optical depth (COD) at 0.55 µm of 0.4 and in nadir view. A correction term in the COD linear function was added to the GSW algorithm to extend the GSW algorithm to cirrus cloudy conditions. The COD was acquired by a look up table of the isolated cirrus bidirectional reflectance at 0.55 µm. Additionally, the slope k of the linear function was expressed as a multiple linear model of the top of the atmospheric brightness temperatures of MODIS channels 31-34 and as the difference between split-window channel emissivities. The simulated data showed that the LST error could be reduced from 11.0 to 2.2 K. The sensitivity analysis indicated that the total errors from all the uncertainties of input parameters, extension algorithm accuracy, and GSW algorithm accuracy were less than 2.5 K in nadir view. Finally, the Great Lakes surface water temperatures measured by buoys showed that the retrieval accuracy of the GSW algorithm was improved by at least 1.5 K using the proposed extension algorithm for cirrus skies.

A Multi-Channel Method for Retrieving Surface Temperature for High-Emissivity Surfaces from Hyperspectral Thermal Infrared Images.

The surface temperature (ST) of high-emissivity surfaces is an important parameter in climate systems. The empirical methods for retrieving ST for high-emissivity surfaces from hyperspectral thermal infrared (HypTIR) images require spectrally continuous channel data. This paper aims to develop a multi-channel method for retrieving ST for high-emissivity surfaces from space-borne HypTIR data. With an assumption of land surface emissivity (LSE) of 1, ST is proposed as a function of 10 brightness temperatures measured at the top of atmosphere by a radiometer having a spectral interval of 800-1200 cm(-1) and a spectral sampling frequency of 0.25 cm(-1). We have analyzed the sensitivity of the proposed method to spectral sampling frequency and instrumental noise, and evaluated the proposed method using satellite data. The results indicated that the parameters in the developed function are dependent on the spectral sampling frequency and that ST of high-emissivity surfaces can be accurately retrieved by the proposed method if appropriate values are used for each spectral sampling frequency. The results also showed that the accuracy of the retrieved ST is of the order of magnitude of the instrumental noise and that the root mean square error (RMSE) of the ST retrieved from satellite data is 0.43 K in comparison with the AVHRR SST product.

Determination of optimum viewing angles for the angular normalization of land surface temperature over vegetated surface.

Multi-angular observation of land surface thermal radiation is considered to be a promising method of performing the angular normalization of land surface temperature (LST) retrieved from remote sensing data. This paper focuses on an investigation of the minimum requirements of viewing angles to perform such normalizations on LST. The normally kernel-driven bi-directional reflectance distribution function (BRDF) is first extended to the thermal infrared (TIR) domain as TIR-BRDF model, and its uncertainty is shown to be less than 0.3 K when used to fit the hemispheric directional thermal radiation. A local optimum three-angle combination is found and verified using the TIR-BRDF model based on two patterns: the single-point pattern and the linear-array pattern. The TIR-BRDF is applied to an airborne multi-angular dataset to retrieve LST at nadir (Te-nadir) from different viewing directions, and the results show that this model can obtain reliable Te-nadir from 3 to 4 directional observations with large angle intervals, thus corresponding to large temperature angular variations. The Te-nadir is generally larger than temperature of the slant direction, with a difference of approximately 0.5~2.0 K for vegetated pixels and up to several Kelvins for non-vegetated pixels. The findings of this paper will facilitate the future development of multi-angular thermal infrared sensors.