Search Results (181)

This study provides a comprehensive, long-term evaluation of inter-sensor radiometric calibration biases for the NOAA OMPS Nadir and CrIS instruments using four complementary validation methodologies implemented within the Inter-Sensor Radiometric Bias Assessment (iSensor-RCBA) portal, a component of the STAR Integrated Calibration/Validation System. Overall, SDR data quality from the three OMPS Nadir instruments and three CrIS instruments aboard SNPP, NOAA-20, and NOAA-21 remains stable. The iSensor-RCBA portal has also proven to be a powerful diagnostic resource, enabling the detection of both new and previously unrecognized calibration issues and anomalies. Using the 32-day averaged difference method, we were the first to discover and identify the root cause of an inconsistency near 280 nm in inter-sensor radiometric biases between the SNPP and NOAA-20 OMPS NP instruments. The same method also revealed an unusual radiometric feature in NOAA-21 CrIS SDRs over the southern high latitudes during spring and summer. In addition, we derived decade-long degradation rates at 11 Metop-B GOME-2 wavelengths using an independent dataset—Simultaneous Nadir Overpass observations between SNPP OMPS and Metop-B GOME-2. Furthermore, iSensor-RCBA monitoring confirmed two geolocation anomalies in SNPP CrIS through a new approach involving SNO-based inter-sensor biases between GOES-16 ABI and SNPP CrIS. These cases demonstrate that iSensor-RCBA is not only a monitoring visualization tool but also a diagnostic tool that delivers unique, complementary insight into instrument performance, enabling early identification of radiometric and geolocation issues across JPSS and other satellite missions. Importantly, the analysis methods used in this study are broadly applicable to current and future missions, including JPSS-03, JPSS-04, and non-NOAA satellite systems. Full article

This study analyzes the relationship between fires and climate extremes in the Caatinga biome from 2012 to 2023 by integrating Fire Radiative Power (FRP) from VIIRS (S-NPP and NOAA-20), Vapor Pressure Deficit (VPD) and air temperature from ERA5, drought indices (SPI-1 and SPI-6), and heatwave events from the Xavier database. Daily percentiles of maximum (CTX90pct) and minimum (CTN90pct) temperatures were used to characterize heatwaves. Spatial and temporal dynamics of fire patterns were identified using the HDBSCAN algorithm, an unsupervised Machine Learning clustering method applied in three-dimensional space (latitude, longitude, and time). A marked seasonality was observed, with fire activity peaking from August to November, especially in October, when FRP reached ~1000 MW/h. The years 2015, 2019, 2021, and 2023 exhibited the highest fire intensities. A statistically significant upward trend in cluster frequency was detected (+1094.96 events/year; p < 0.001). Cross-correlations revealed that precipitation deficits (SPI) preceded FRP peaks by about four months, while VPD and air temperature exerted immediate positive effects. FRP correlated positively with heatwave frequency (r = 0.62) and negatively with SPI (r = −0.69). These findings highlight the high vulnerability of the Caatinga to compound drought and heat events, indicating that fire management strategies should account for both antecedent drought conditions, monitored through SPI, and real-time atmospheric dryness, measured by VPD, to effectively mitigate fire risks. Full article

We present a gradient boosting framework for reconstructing hyperspectral signatures in the visible spectrum (400–700 nm) of satellite-based ocean scenes from limited multispectral inputs. Hyperspectral data is composed of many, typically greater than 100, narrow wavelength bands across the electromagnetic spectrum. While hyperspectral data can offer reflectance values at every nanometer, multispectral sensors typically provide only 3 to 11 discrete bands, undersampling the visible color space. Our approach is applied to remote sensing reflectance ($R_{rs}$) measurements from a set of ocean color sensors, including Suomi-National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), the Ocean and Land Colour Instrument (OLCI), Hyperspectral Imager for the Coastal Ocean (HICO), and NASA’s Plankton, Aerosol, Cloud, Ocean Ecosystem Ocean Color Instrument (PACE OCI), as well as in situ $R_{rs}$ data from National Oceanic and Atmospheric Administration (NOAA) calibration and validation cruises. By leveraging these datasets, we demonstrate the feasibility of transforming low-spectral-resolution imagery into high-fidelity hyperspectral products. This capability is particularly valuable given the increasing availability of low-cost platforms equipped with RGB or multispectral imaging systems. Our results underscore the potential of hyperspectral enhancement for advancing ocean color monitoring and enabling broader access to high-resolution spectral data for scientific and environmental applications. Full article

Accurate delineation of urban built-up areas is critical for urban monitoring and planning. We evaluated the performance and consistency of three widely used methods—thresholding, multi-temporal image fusion, and support vector machine (SVM)—across three major nighttime light (NTL) datasets (DMSP/OLS, SNPP/VIIRS, and Luojia-1). We developed a unified methodological framework and applied it to Wuhan, China, encompassing data preprocessing, feature construction, classification, and cross-dataset validation. The results show that SNPP/VIIRS combined with thresholding or SVM achieved highest accuracy (kappa coefficient = 0.70 and 0.61, respectively) and spatial consistency (intersection over union, IoU = 0.76), attributable to its high radiometric sensitivity and temporal stability. DMSP/OLS exhibited robust performance with SVM (kappa = 0.73), likely benefiting from its long historical coverage, while Luojia-1 was constrained by limited temporal availability, hindering its suitability for temporal fusion methods. This study highlights the critical influence of sensor characteristics and method–dataset compatibility on extraction outcomes. While traditional methods provide interpretability and computational efficiency, the findings suggest a need for integrating deep learning models and hybrid strategies in future work. These advancements could further improve accuracy, robustness, and transferability across diverse urban contexts. Full article

Monitoring chlorophyll-a concentration (Chl-a) is essential for assessing aquatic ecosystem health, yet its retrieval using remote sensing remains challenging in turbid coastal waters because of the intricate optical characteristics of these environments. Elevated levels of colored (chromophoric) dissolved organic matter (CDOM) and suspended sediments (aka total suspended solids, TSS) interfere with satellite-based Chl-a estimates, necessitating alternative approaches. One potential solution is machine learning, indirectly including non-Chl-a signals into the models. In this research, we develop machine learning models to predict Chl-a concentrations in the Chesapeake Bay, one of the largest estuaries on North America’s East Coast. Our approach leverages the Extra-Trees (ET) algorithm, a tree-based ensemble method that offers predictive accuracy comparable to that of other ensemble models, while significantly improving computational efficiency. Using the entire ocean color datasets acquired by the satellite sensors MODIS-Aqua (>20 years) and VIIRS-SNPP (>10 years), we generated long-term Chl-a estimates covering the entire Chesapeake Bay area. The models achieve a multiplicative absolute error of approximately 1.40, demonstrating reliable performance. The predicted spatiotemporal Chl-a patterns align with known ecological processes in the Chesapeake Bay, particularly those influenced by riverine inputs and seasonal variability. This research emphasizes the potential of machine learning to enhance satellite-based water quality monitoring in optically complex coastal waters, providing valuable insights for ecosystem management and conservation. Full article

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been continuously providing global environmental data records (EDRs) for more than one decade since its launch in 2011. Recently, the VIIRS EDRs of cloud features have been reprocessed using unified and consistent algorithm for selected periods to minimize or remove the inconsistencies due to different versions of retrieval algorithms as well as input VIIRS sensor data records (SDRs) adopted by different periods of operational EDRs. This study conducts the first simultaneous quality and accuracy assessment of reprocessed Cloud Top Height (CTH) and Cloud Base Height (CBH) products against both the operational VIIRS EDRs and corresponding cloud height measurements from the active sensors of NASA’s CloudSat-CALIPSO system. In general, the reprocessed CTH and CBH EDRs show strong similarities and correlations with CloudSat-CALIPSOs, with coefficients of determination (${\mathrm{R}}^2$) reaching 0.82 and 0.77, respectively. Additionally, the reprocessed VIIRS cloud height products demonstrate significant improvements in retrieving high-altitude clouds and in sensitivity to cloud height dynamics. It outperforms the operational product in capturing very high CTHs exceeding 15 km and exhibits CBH probability patterns more closely aligned with CloudSat-CALIPSO measurements. This preliminary assessment enhances data applicability of remote sensing products for atmospheric and climate research, allowing for more accurate cloud measurements and advancing environmental monitoring efforts. Full article

The Joint Polar Satellite System 3 (JPSS-3) and -4 (JPSS-4) Visible Infrared Imaging Radiometer Suite (VIIRS) instruments are the last in the series (S-NPP VIIRS launched in October 2011, JPSS-1 VIIRS launched in November 2017, and JPSS-2 VIIRS launched in November 2022) of highly advanced polar-orbiting environmental satellites. Both instruments underwent a comprehensive sensor-level thermal vacuum (TVAC) testing at the Raytheon Technologies El Segundo facility to characterize the spatial, spectral, and radiometric aspects of the VIIRS sensor performance. This paper focuses on the radiometric performance of the 14 reflective solar bands (RSBs) that cover the wavelength range from 0.41 to 2.3 µm. Key instrument calibration parameters such as instrument gain, signal-to-noise ratio (SNR), dynamic range, and radiometric calibration uncertainty were derived from the TVAC measurements for both the primary and redundant electronics at three instrument temperature plateaus: cold, nominal, and hot. This paper shows that all the JPSS-3 and -4 VIIRS RSB detectors have been well characterized, with key performance metrics comparable to the previous VIIRS instruments on-orbit. The radiometric calibration uncertainty of the RSBs is within the 2% requirement, except in the case of band M1 of JPSS-4. Comparison of the radiometric performance to sensor requirements, as well as a summary of key instrument testing and performance issues, is also presented. Full article

The Ozone Mapping and Profiler Suites (OMPS) Nadir Mapper (NM) is a grating spectrometer within the OMPS nadir instruments onboard the SNPP, NOAA-20, and NOAA-21 satellites. It is designed to measure Earth radiance and solar irradiance spectra in wavelengths from 300 nm to 380 nm for operational retrievals of the nadir total column ozone. This study presents calibration and validation analysis results for the NOAA-21 OMPS NM SDR data to meet the JPSS scientific requirements. The NOAA-21 OMPS SDR calibration derives updates of several previous OMPS algorithms, including the dark current correction algorithm, one-time wavelength registration from ground to on-orbit, daily intra-orbit wavelength shift correction, and stray light correction. Additionally, this study derives an empirical scale factor to remove 2.2% of systematic biases in solar flux data, which were caused by pre-launch solar calibration errors of the OMPS nadir instruments. The validation of the NOAA-21 OMPS SDR data is conducted using various methods. For example, the 32-day average method and radiative transfer model are employed to estimate inter-sensor radiometric calibration differences from either the SNPP or NOAA-20 data. The quality of the NOAA-21 OMPS NM SDR data is largely consistent with that of the SNPP and NOAA-20 OMPS data, with differences generally within ±2%. This meets the scientific requirements, except for some deviations mainly in the dichroic range between 300 nm and 303 nm. The deep convective cloud target approach is used to monitor the stability of NOAA-21 OMPS reflectance above 330 nm, showing a variation of 0.5% over the observed period. Data from the NOAA-21 VIIRS M1 band are used to estimate OMPS NM data geolocation errors, revealing that along-track errors can reach up to 3 km, while cross-track errors are generally within ±1 km. Full article

Polygonum aviculare L. (PAL), commonly known as knotgrass, has been utilized as a traditional folk medicine across Asian, African, Latin American and Middle Eastern countries to treat various inflammatory diseases, including arthritis and airway inflammation. Numerous medicinal herbs exert anti-inflammatory and antioxidative effects that are mediated through the activation of nuclear factor-erythroid 2-related factor 2 (Nrf2) and the inhibition of nuclear factor kappa B (NF-κB). However, the underlying molecular mechanisms linking the antioxidative and anti-inflammatory effects remain poorly understood. Heme oxygenase-1 (HO-1) is an antioxidant enzyme that catalyzes heme degradation, ultimately leading to the production of carbon monoxide (CO). Elevated levels of CO have been correlated with the decreased level of inducible nitric oxide synthase (iNOS). In this study, we examined whether HO-1 plays a key role in the relationship between the antioxidative and anti-inflammatory properties of PAL. The anti-inflammatory and antioxidative activities of PAL in an in vitro system were evaluated by determining NF-κB activity, antioxidant response element (ARE) activity, pro-inflammatory cytokine and protein levels, as well as antioxidant protein levels. To examine whether HO-1 inhibition interfered with the anti-inflammatory effect of PAL, we measured nitrite, reactive oxygen species, iNOS, and HO-1 levels in RAW 264.7 murine macrophages pre-treated with Tin protoporphyrin (SnPP, an HO-1 inhibitor). Our results demonstrated that PAL increased ARE activity and the Nrf2-regulated HO-1 level, exerting antioxidative activities in RAW 264.7 macrophages. Additionally, PAL reduced cyclooxygenase-2 (COX-2) and iNOS protein levels by inactivating NF-κB in lipopolysaccharide (LPS)-activated RAW 264.7 macrophages. Further investigation using the HO-1 inhibitor revealed that HO-1 inhibition promoted iNOS expression, subsequently elevating nitric oxide (NO) generation in LPS-activated RAW 264.7 macrophages treated with PAL compared to those in the macrophages without the HO-1 inhibitor. Overall, our findings suggest that HO-1 induction by PAL may exert anti-inflammatory effects through the reduction of the iNOS protein level. Hence, this study paves the way for further investigation to understand molecular mechanisms underlying the antioxidative and anti-inflammatory activities of medicinal herbs. Full article

The increasing frequency of low-temperature events in spring, driven by climate change, poses a serious threat to wheat production in Northern China. Understanding how low-temperature stress affects wheat yield and its components under varying moisture conditions, and exploring the role of irrigation before exposure to low temperatures, is crucial for food security and mitigating agricultural losses. In this study, four wheat cultivars—semi-spring (YZ4110, LK198) and semi-winter (ZM366, FDC21)—were tested across two years under different conditions of soil moisture (irrigation before low-temperature exposure (IBLT) and non-irrigation (NI)) and low temperatures (−2 °C, −4 °C, −6 °C, −8 °C, and −10 °C). The IBLT treatment effectively reduced leaf wilt, stem breakage, and spikelet desiccation. Low-temperature stress adversely impacted the yield per plant—including both original and regenerated yields—and yield components across all wheat varieties. Furthermore, a negative correlation was found between regenerated and original yields. Semi-spring varieties showed greater yield reduction than semi-winter varieties, with a more pronounced impact under NI compared to IBLT. This suggests that the compensatory regenerative yield is more significant in semi-spring varieties and under NI conditions. As low-temperature stress intensified, the primary determinant of yield loss shifted from grain number per spike (GNPS) to spike number per plant (SNPP) beyond a specific temperature threshold. Under NI, this threshold was −6 °C, while it was −8 °C under IBLT. Low-temperature stress led to variability in fruiting rate across different spike positions, with semi-spring varieties and NI conditions showing the most substantial reductions. Sensitivity to low temperatures varied across spikelet positions: Apical spikelets were the most sensitive, followed by basal, while central spikelets showed the largest reduction in grain number as stress levels increased, significantly contributing to reduced overall grain yield. Irrigation, variety, and low temperature had variable impacts on physiological indices in wheat. Structural equation modeling (SEM) analysis revealed that irrigation significantly enhanced wheat’s response to cold tolerance indicators—such as superoxide dismutase (SOD), proline (Pro), and peroxidase (POD)—while reducing malondialdehyde (MDA) levels. Irrigation also improved photosynthesis (Pn), chlorophyll fluorescence (Fv/Fm), and leaf water content (LWC), thereby mitigating the adverse effects of low-temperature stress and supporting grain development in the central spike positions. In summary, IBLT effectively mitigates yield losses due to low-temperature freeze injuries, with distinct yield component contributions under varying stress conditions. Furthermore, this study clarifies the spatial distribution of grain responses across different spike positions under low temperatures, providing insights into the physiological mechanisms by which irrigation mitigates grain loss. These findings provide a theoretical and scientific basis for effective agricultural practices to counter spring freeze damage and predict wheat yield under low-temperature stress. Full article

The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key instruments on the recently launched NOAA-21 (previously known as JPSS-2) satellite. The VIIRS, like its predecessors on the SNPP and NOAA-20 satellites, provides daily global coverage in 22 spectral bands from 412 nm to 12 μm. The geometrically and radiometrically calibrated observations are the basis for many operational applications and scientific research studies. A total of 14 of the 22 bands are reflective solar bands (RSBs), covering photon wavelengths from 412 nm to 2.25 μm. The RSBs were radiometrically calibrated prelaunch and have been regularly calibrated on orbit through the onboard solar diffuser (SD) and scheduled lunar observations. The on-orbit SD’s reflectance change is determined by the onboard solar diffuser stability monitor (SDSM). We review the calibration algorithms and present the early mission performance of the NASA N21 VIIRS RSBs. Using the calibration data collected at both the yaw maneuver and regular times, we derive the screen transmittance functions. The visible and near-infrared bands’ radiometric gains have been stable, nearly independent of time, and so were the radiometric gains of the shortwave-infrared bands after the second mid-mission outgassing. Further, we assess the Earth-view striping observed in the immediate prior collection (Collection 2.0) and apply a previously developed algorithm to mitigate the striping. The N21 VIIRS RSB detector signal-to-noise ratios are all above the design values with large margins. Finally, the uncertainties of the retrieved Earth-view top-of-the-atmosphere spectral reflectance factors at the respective typical spectral radiance levels are estimated to be less than 1.5% for all the RSBs, except band M11 whose reflectance factor uncertainty is 2.2%. Full article

The chickpea plays a significant role in global agriculture and occupies an increasing share in the human diet. The main aim of the research was to develop a model for the prediction of two chickpea productivity traits in the available dataset. Genomic data for accessions were encoded in Artificial Image Objects, and a model for the thousand-seed weight (TSW) and number of seeds per plant (SNpP) prediction was constructed using a Convolutional Neural Network, dictionary learning and sparse coding for feature extraction, and extreme gradient boosting for regression. The model was capable of predicting both traits with an acceptable accuracy of 84–85%. The most important factors for model solution were identified using the dense regression attention maps method. The SNPs important for the SNpP and TSW traits were found in 34 and 49 genes, respectively. Genomic prediction with a constructed model can help breeding programs harness genotypic and phenotypic diversity to more effectively produce varieties with a desired phenotype. Full article

It is still unclear whether or how quercetin influences the toxic events induced by acetaldehyde in hepatocytes, though quercetin has been reported to mitigate alcohol-induced mouse liver injury. In this study, we evaluated the modulating effect of quercetin on the cytotoxicity induced by acetaldehyde in mouse hepatoma Hepa1c1c7 cells, the frequently used cellular hepatocyte model. The pretreatment with quercetin significantly inhibited the cytotoxicity induced by acetaldehyde. The treatment with quercetin itself had an ability to enhance the total ALDH activity, as well as the ALDH1A1 and ALDH3A1 gene expressions. The acetaldehyde treatment significantly enhanced the intracellular reactive oxygen species (ROS) level, whereas the quercetin pretreatment dose-dependently inhibited it. Accordingly, the treatment with quercetin itself significantly up-regulated the representative intracellular antioxidant-related gene expressions, including heme oxygenase-1 (HO-1), glutamate-cysteine ligase, catalytic subunit (GCLC), and cystine/glutamate exchanger (xCT), that coincided with the enhancement of the total intracellular glutathione (GSH) level. Tin protoporphyrin IX (SNPP), a typical HO-1 inhibitor, restored the quercetin-induced reduction in the intracellular ROS level, whereas buthionine sulphoximine, a representative GSH biosynthesis inhibitor, did not. SNPP also cancelled the quercetin-induced cytoprotection against acetaldehyde. These results suggest that the low-molecular-weight antioxidants produced by the HO-1 enzymatic reaction are mainly attributable to quercetin-induced cytoprotection. Full article

(1) Background: The objective of this study was to evaluate the efficacy of the Rapid Maxillary Expander (RME) II System compared to a Herbst appliance and a control group in the treatment of class II skeletal malocclusions in growing patients. (2) Methods: A total of 30 class II patients treated using the RME II System (group R) were compared with 30 patients treated with a Herbst appliance (group H) and 30 untreated class II children (group C). Cephalograms were compared at the start (T0) and after 24 months (T1). Nine cephalometric parameters were analyzed: SN-MP, SN-PO, ANB, AR-GO-ME, AR-GO-N, N-GO-ME, SN-PP, LFH, CO-GN, 1+SN, IMPA, OVERJET, and OVERBITE. Since the variables failed the normality test, a Wilcoxon test was performed for a pairwise comparison of the cephalometric measurements taken at T0 (pre-treatment) and at T1 (post-treatment). ANOVA with Tukey post hoc correction was used to evaluate the differences among the groups. (3) Results: ANOVA showed a statistically significant difference for all analyzed variables except for AR-GO-ME, AR-GO-N, and N-GO-ME. Post hoc Tukey’s HSD test showed the following difference: the SN-PO angle in group H was 3.59° greater than in group R; the LFH in group H was 4.13 mm greater than in group R. The mandibular length (CO-GN) in group H was 3.94 mm greater than in group R; IMPA in group H was 6.4° greater than in group R; and the ANB angle in group H was 1.47° greater than in group R. (4) Conclusions: The RME II System is an effective therapeutic device for class II skeletal malocclusion treatment in growing patients. Full article

γ-Tocopherol (γT) is the major form of vitamin E contained in plants and seed oils. Although it is readily metabolized in the liver, the function of the metabolites is not fully understood. This study investigated the antioxidant activities of the γT metabolite 2,7,8-trimethyl-2-(2′-carboxyethyl)-6-hydroxychroman (γCEHC) in comparison to its parent compound. The pretreatment of mouse hepatoma Hepa1c1c7 cells with γCEHC showed a cytoprotective effect on the hydrogen peroxide-induced cytotoxicity to a lesser extent than that of γT. A mechanistic investigation revealed that both γ-CEHC and γT significantly up-regulated the gene and protein expressions of heme oxygenase-1 (HO-1) via the promotion of the nuclear translocation of nuclear factor erythroid 2-related factor 2 (Nrf2). Furthermore, the combination of γCEHC and γT significantly increased the gene and protein levels of HO-1 and the nuclear translocation of Nrf2, suggesting that it was an additive effect. Tin protoporphyrin IX (SnPP), a representative HO-1 inhibitor, significantly impaired the cytoprotection of γCEHC and γT against the hydrogen peroxide-induced cytotoxicity. These results suggested that not only γT but also its metabolite, γCEHC, are a promising cytoprotective factor against oxidative stress-induced cytotoxicity and that the cytoprotective effect is attributable to the cooperation of both compounds. Full article