Search Results (43)

The Multi-Scale Multi-Group Wide-Band (MSMGWB) model was used to calculate radiative transfer in strongly non-isothermal and inhomogeneous media such as the remote infrared sensing of aircraft exhaust system and jet plume scenario. In this work, the reference temperature was introduced into the model as an independent variable for each spectral subinterval group. Then, to deal with the exceedingly vast parameter sample space (i.e., the combination of spectral subinterval grouping results, reference temperatures and Gaussian quadrature schemes), an MSMGWB model’s parameter optimization process superior to the exhaustive approach employed in previous studies was established, which was consisted of the Non-dominated Sorting Genetic Algorithm II method (NSGA2) and an iterative scan method. Through a series of 0-D test cases and two real 3-D remote infrared imaging results of an aircraft exhaust system, it was observed that the MSMGWB model established and optimiazed in current work demonstrated notable improvements in both accuracy and computational efficiency. Full article

Visual object tracking, pivotal for applications like earth observation and environmental monitoring, encounters challenges under adverse conditions such as low light and complex backgrounds. Traditional tracking technologies often falter, especially when tracking dynamic objects like aircraft amidst rapid movements and environmental disturbances. This study introduces an innovative adaptive multimodal image object-tracking model that harnesses the capabilities of multispectral image sensors, combining infrared and visible light imagery to significantly enhance tracking accuracy and robustness. By employing the advanced vision transformer architecture and integrating token spatial filtering (TSF) and crossmodal compensation (CMC), our model dynamically adjusts to diverse tracking scenarios. Comprehensive experiments conducted on a private dataset and various public datasets demonstrate the model’s superior performance under extreme conditions, affirming its adaptability to rapid environmental changes and sensor limitations. This research not only advances visual tracking technology but also offers extensive insights into multisource image fusion and adaptive tracking strategies, establishing a robust foundation for future enhancements in sensor-based tracking systems. Full article

The sea ice albedo can amplify global climate change and affect the surface energy in the Arctic. In this paper, the data from Visible and Infra-Red Radiometer (VIRR) onboard Fengyun-3C satellite are applied to derive the Arctic sea ice albedo. Two radiative transfer models, namely, 6S and FluxNet, are used to simulate the reflectance and albedo in the shortwave band. Clear sky sea ice albedo in the Arctic region (60°~90°N) from 2016 to 2019 is derived through the physical process, including data preprocessing, narrowband to broadband conversion, anisotropy correction, and atmospheric correction. The results are compared with aircraft measurements and AVHRR Polar Pathfinder-Extended (APP-x) albedo product and OLCI MPF product. The bias and standard deviation of the difference between VIRR albedo and aircraft measurements are −0.040 and 0.071, respectively. Compared with APP-x product and OLCI MPF product, a good consistency of albedo is shown. And analyzed together with melt pond fraction, an obvious negative relationship can be seen. After processing the 4-year data, an obvious annual trend can be observed. Due to the influence of snow on the ice surface, the average surface albedo of the Arctic in March and April can reach more than 0.8. Starting in May, with the ice and snow melting and melt ponds forming, the albedo drops rapidly to 0.5–0.6. Into August, the melt ponds begin to freeze and the surface albedo increases. Full article

This study utilized an infrared spotlight Hyperspectral infrared Atmospheric Sounder (HIRAS) and the Medium Resolution Spectral Imager (MERSI) mounted on FY3D cloud products from the National Satellite Meteorological Center of China to obtain methane profile information. Methane inversion channels near 7.7 μm were selected based on the different distribution of methane weighting functions across different seasons and latitudes, and the selected retrieval channels had a great sensitivity to methane but not to other parameters. The optimization method was employed to retrieve methane profiles using these channels. The ozone profiles, temperature, and water vapor of the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation reanalysis data (ERA5) were applied to the retrieval process. After validating the methane profile concentrations retrieved by HIRAS, the following conclusions were drawn: (1) compared with Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container (CARIBIC) flight data, the average correlation coefficient, relative difference, and root mean square error were 0.73, 0.0491, and 18.9 ppbv, respectively, with lower relative differences and root mean square errors in low-latitude regions than in mid-latitude regions. (2) The methane profiles retrieved from May 2019 to September 2021 showed an average error within 60 ppbv compared with the Fourier transform infrared spectrometer (FTIR) station observations of the Infrared Working Group (IRWG) of the Network for the Detection of Atmospheric Composition Change (NDACC). The errors between the a priori and retrieved values, as well as between the retrieved and smoothed values, were larger by around 400–500 hPa. Apart from Toronto and Alzomoni, which had larger peak values in autumn and spring respectively, the mean column averaging kernels typically has a larger peak in summer. Full article

Aircraft and rockets entered the lower stratosphere on a regular basis during World War II and have done so in increasing numbers to the present. Atmospheric testing of nuclear weapons saw radioactive isotopes in the stratosphere. Rocket launches of orbiters are projected to increase substantially in the near future. The burnup of orbiters has left signatures in the aerosol. There are proposals to attenuate incoming solar radiation by deliberate injection of artificial aerosols into the stratosphere to “geoengineer” cooling trends in surface temperature, with the aim of countering the heating effects of infrared active gases. These gases are mainly carbon dioxide from fossil burning, with additional contributions from methane, chlorofluorocarbons, nitrous oxide and the accompanying positive feedback from increasing water vapor. Residence times as a function of altitude above the tropopause are critical. The analysis of in situ data is performed using statistical multifractal techniques and combined with remotely sensed and modeled results to examine the classical radiation–photochemistry–fluid mechanics interaction that determines the composition and dynamics of the lower stratosphere. It is critical in assessing anthropogenic effects. It is argued that progress in predictive ability is driven by the continued generation of new and quantitative observations in the laboratory and the atmosphere. Full article

High-resolution electronics on complex curved surfaces have wide applications in fields such as biometric health monitoring, intelligent aircraft skins, conformal displays, and biomimetics. However, current manufacturing processes can only adapt to limited curvature, posing a significant challenge for achieving high-resolution fabrication of electronics on complex curved surfaces. In this study, we propose a novel fabrication strategy that combines electric field-driven jetting and water-assisted transfer printing techniques to achieve the fabrication of high-resolution electronics on complex curved surfaces. The electric field-driven jetting enables the fabrication of high-resolution 2D electronics on sacrificial layer substrates. After dissolving the sacrificial layer, it is observed that the 2D electronics form a self-supporting structure with a certain rigidity and flexibility. During the water-assisted transfer printing process, this self-supporting structure undergoes stretching deformation with excellent conformity of the electronics to curved surfaces while effectively minimizing wrinkles. Finally, we successfully demonstrate the manufacture of 25 μm high-resolution electronics on highly curved surfaces (nautilus shell) and complex (scallop shell, stone) surfaces. The integrity of transferred circuit patterns and consistency of conductors are verified through infrared thermography analysis, confirming the feasibility of this manufacturing strategy. In addition, a protective film with strong adhesive properties is sprayed onto the transferred curved circuits to enhance their adhesion and resistance to extreme environments such as acids and alkalis. Our proposed technique provides a simple and effective new strategy for the fabrication of high-resolution electronics on complex curved surfaces. Full article

Infrared video target detection is a fundamental technology within infrared warning and tracking systems. In long-distance infrared remote sensing images, targets often manifest as circular spots or even single points. Due to the weak and similar characteristics of the target to the background noise, the intelligent detection of these targets is extremely complex. Existing deep learning-based methods are affected by the downsampling of image features by convolutional neural networks, causing the features of small targets to almost disappear. So, we propose a new infrared video weak-target detection network based on central point regression. We focus on suppressing the image background by fusing the different features between consecutive frames with the original image features to eliminate the background’s influence. We also employ high-resolution feature preservation and incorporate a spatial–temporal attention module into the network to capture as many target features as possible and improve detection accuracy. Our method achieves superior results on the infrared image weak aircraft target detection dataset proposed by the National University of Defense Technology, as well as on the simulated dataset generated based on real-world observation. This demonstrates the efficiency of our approach for detecting weak point targets in infrared continuous images. Full article

Surface suction provides an efficient way to delay boundary layer transitions. In order to verify the suction effects and determine the mechanism of suction control in transonic swept wing boundary layers, wind tunnel transition measurements in a hybrid laminar flow control (HLFC) wind tunnel model uses an infrared thermography technique in the Aircraft Research Association (ARA) 2.74 m × 2.44 m low turbulence level transonic wind tunnel. Based on the experimental data of stationary crossflow dominant transitions without and with surface suction in transonic swept wing boundary layers, in this paper, the effects on the receptivity and linear and nonlinear evolution of stationary crossflow vortices have been analyzed with the consideration of curvature. Theoretical analysis agreed with the experimental observations in regard to the transition delay caused by boundary layer suction near the leading-edge region. Full article

With the launch of Landsat-9 on 27 September 2021, Landsat continues its fifty-year continuity mission of providing users with calibrated Earth observations. It has become a requirement that an underflight experiment be performed during commissioning to support sensor cross-calibration. In this most recent experiment, Landsat-9 flew under Landsat-8 for nearly three days with over 50% ground overlap, from 13 to 15 November 2021. To address the scarcity of reference data that are available to support calibration and validation early-on in the mission, a ground campaign was planned and executed by the Rochester Institute of Technology (RIT) on 14 November 2021 to provide full spectrum measurements for early mission comparisons. The primary experiment was conducted in the Outer Banks, North Carolina at Jockey’s Ridge Sand Dunes. Full-spectrum ground-based measurements were acquired with calibrated reference equipment, while a novel Unmanned Aircraft System (UAS)-based platforms acquired hyperspectral visible and near-infrared (VNIR)/Short-wave infrared (SWIR) imagery data and coincident broadband cooled thermal infrared (TIR) imagery. Results of satellite/UAS/ground comparisons were an indicator, during the commissioning phase, that Landsat-9 is behaving consistently with Landsat-8, ground reference, and UAS measurements. In the thermal infrared, all measurements agree to be within 1 K over water and to within 2 K over sand, which represents the most challenging material for estimating surface temperature. For the surface reflectance product(s), Landsat-8 and -9 are in good agreement and only deviate slightly from ground reference in the SWIR bands; a deviation of 2% in the VNIR and 5–8% in the SWIR regime. Subsequent longer-term studies indicate that Landsat 9 continues to perform as expected. The behavior of Thermal Infrared Sensor-2 (TIRS-2) against reference is also shown for the first year of the mission to illustrate its consistent performance. Full article

Climate impact models of the non-${\mathrm{CO}}_2$ emissions of aviation are still subject to significant uncertainties. Condensation trails, or contrails, are one of these non-${\mathrm{CO}}_2$ effects. In order to validate the contrail simulation models, a dataset of observations covering the entire lifetime of the contrails will be required, as well as the characteristics of the aircraft which produced them. This study carries on the work on contrail observation from geostationary satellite by proposing a new way to track contrails and identify the flight that produced it using geostationary satellite infrared images, weather data as well as air traffic data. It solves the tracking and the identification problem as one, each process leveraging information from the other to achieve a better overall result. This study is a new step towards a consistent contrail dataset that could be used to validate contrail models. Full article

In recent years, UAV remote sensing has gradually attracted the attention of scientific researchers and industry, due to its broad application prospects. It has been widely used in agriculture, forestry, mining, and other industries. UAVs can be flexibly equipped with various sensors, such as optical, infrared, and LIDAR, and become an essential remote sensing observation platform. Based on UAV remote sensing, researchers can obtain many high-resolution images, with each pixel being a centimeter or millimeter. The purpose of this paper is to investigate the current applications of UAV remote sensing, as well as the aircraft platforms, data types, and elements used in each application category; the data processing methods, etc.; and to study the advantages of the current application of UAV remote sensing technology, the limitations, and promising directions that still lack applications. By reviewing the papers published in this field in recent years, we found that the current application research of UAV remote sensing research can be classified into four categories according to the application field: (1) Precision agriculture, including crop disease observation, crop yield estimation, and crop environmental observation; (2) Forestry remote sensing, including forest disease identification, forest disaster observation, etc.; (3) Remote sensing of power systems; (4) Artificial facilities and the natural environment. We found that in the papers published in recent years, image data (RGB, multi-spectral, hyper-spectral) processing mainly used neural network methods; in crop disease monitoring, multi-spectral data are the most studied type of data; for LIDAR data, current applications still lack an end-to-end neural network processing method; this review examines UAV platforms, sensors, and data processing methods, and according to the development process of certain application fields and current implementation limitations, some predictions are made about possible future development directions. Full article

The integration of active cooling systems in super or hypersonic aircraft using endothermic hydrocarbon fuels is considered an effective way to relieve the thermal management issues caused by overheating. When the temperature of aviation kerosene exceeds 150 °C, the oxidation reaction of fuel is accelerated, forming insoluble deposits that could cause safety hazards. This work investigates the deposition characteristic as well as the morphology of the deposits formed by thermal-stressed Chinese RP-3 aviation kerosene. A microchannel heat transfer simulation device is used to simulate the heat transfer process of aviation kerosene under various conditions. The temperature distribution of the reaction tube was monitored by an infrared thermal camera. The properties and morphology of the deposition were analyzed by scanning electron microscopy and Raman spectroscopy. The mass of the deposits was measured using the temperature-programmed oxidation method. It is observed that the deposition of RP-3 is highly related to dissolved oxygen content (DOC) and temperature. When the outlet temperature increased to 527 °C, the fuel underwent violent cracking reactions, and the structure and morphology of deposition were significantly different from those caused by oxidation. Specifically, this study reveals that the structure of the deposits caused by short-to-medium term oxidation are dense, which is different from long-term oxidative deposits. Full article

Observation images from hyperspectral (HS) sensors on satellites and aircraft can be used to map minerals in greater detail than those from multispectral (MS) sensors. However, the coverage of HS images is much less than that of MS images, so there are often cases where MS images cover the entire area of interest while HS images cover only a part of it. In this study, we propose a new method to more reasonably expand the mineral map of an HS image with an MS image in such cases. The method uses various mineral indices from the MS image and MS sensor’s band values as the input and HS image-based mineral classes as the output. Random forest (RF) two-class classification is then applied iteratively to determine the distribution of each mineral in turn, starting with the minerals that are most consistent with the HS image-based mineral map. The method also involves the correction of misalignment between HS and MS images and the selection of input variables by RF multiclass classification. The method was evaluated in comparison with other methods in the Cuprite area, Nevada, using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Hyperspectral Imager Suite (HISUI) as HS sensors and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) as MS sensors. As a result, all of the evaluated region-expansion methods with an HS–MS image pair, including the proposed method, showed better performance than the method using only an MS image. The proposed method had the highest performance, and the inter-mineral averages of the F1-scores for the overlap and non-overlap areas were 85.98% and 46.46% for the AVIRIS–ASTER image pair and 82.78% and 42.60% for the HISUI–ASTER image pair, respectively. Although the performance in the non-overlap region was lower than in the overlap region, the method showed high precision and high accuracy for almost all minerals, including minerals with only a few pixels. Misalignment between the HS–MS images is a factor that degrades accuracy and requires precise alignment, but the misalignment correction in the proposed method could suppress the effect of misalignment. Validation studies using different regions and different sensors will be carried out in the future. Full article

Small uncrewed aerial systems (sUASs) have the potential to serve as ideal platforms for high spatial and temporal resolution wildfire measurements to complement aircraft and satellite observations, but typically have very limited payload capacity. Recognizing the need for improved data from wildfire management and smoke forecasting communities and the potential advantages of sUAS platforms, the Nighttime Fire Observations eXperiment (NightFOX) project was funded by the US National Oceanic and Atmospheric Administration (NOAA) to develop a suite of miniaturized, relatively low-cost scientific instruments for wildfire-related measurements that would satisfy the size, weight and power constraints of a sUAS payload. Here we report on a remote sensing system developed under the NightFOX project that consists of three optical instruments with five individual sensors for wildfire mapping and fire radiative power measurement and a GPS-aided inertial navigation system module for aircraft position and attitude determination. The first instrument consists of two scanning telescopes with infrared (IR) channels using narrow wavelength bands near 1.6 and 4 µm to make fire radiative power measurements with a blackbody equivalent temperature range of 320–1500 °C. The second instrument is a broadband shortwave (0.95–1.7 µm) IR imager for high spatial resolution fire mapping. Both instruments are custom built. The third instrument is a commercial off-the-shelf visible/thermal IR dual camera. The entire system weighs about 1500 g and consumes approximately 15 W of power. The system has been successfully operated for fire observations using a Black Swift Technologies S2 small, fixed-wing UAS for flights over a prescribed grassland burn in Colorado and onboard an NOAA Twin Otter crewed aircraft over several western US wildfires during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field mission. Full article

The space-based infrared observatory of aircraft in the air has the advantages of wide-area, full-time, and passive detection. The optical design parameters for space-based infrared sensors strongly rely on target observed radiation, but there is still a lack of insight into the causes of aircraft observation properties and the impact of instrument performance. A simulation model of space-based observed aircraft infrared characteristics was constructed for this provision, coupling the aircraft radiance with background radiance and instrument performance effects. It was validated by comparing the model predictions to data from both space-based and ground-based measurements. The validation results reveal the alignment between measurements and model predictions and the dependence of overall model accuracy on the background. Based on simulations, the radiance contributions of aircraft and background are quantitatively evaluated, and the detection spectral window for flying aircraft and its causes are discussed in association with instrumental performance effects. The analysis results indicate that the target-background (T-B) contrast is higher in the spectral ranges where aircraft radiation makes an important contribution. The background radiance plays a significant role overall, while the observed radiance at 2.5–3μm is mainly from skin reflection and plume radiance. The skin-reflected radiation absence affects the model reliability, and its reduction at nighttime reduces the T-B contrast. The difference in T-B self-radiation and the stronger atmospheric attenuation for background contribute to the higher contrast at 2.7 μm compared to the other spectral bands. Full article