Radiance Values Research Articles

Quasi-one-dimensional non-equilibrium method for shock tube and stagnation line flows

Shock tube experiments are used to investigate non-equilibrium thermochemistry and radiative processes in reacting gas hypersonic flows. Boundary layer and shock structure are known to influence the spatial variation of the test slug state properties. This work derives and validates a novel method for viscous, quasi-one-dimensional, non-equilibrium flow in a shock tube assuming constant shock speed. The proposed method fully resolves the shock structure. Mirels' estimate for boundary layer growth around the test slug determines the dilation rate at the centerline. This, along with relevant boundary conditions, appropriately models core flow in a shock tube. The flow equations are discretized by finite differences on a staggered grid. The resulting highly non-linear set of algebraic equations is solved by Newton iterations. The Jacobian matrix is block tridiagonal with a Schur complement, allowing efficient inversion. This culminates in a unique and computationally efficient quasi-one-dimensional method offering improved modeling of the physical characteristics of shock tube experiments. Results of a 3 km/s, 66.6 Pa argon test case solved by a viscous, axisymmetric Navier–Stokes solution had agreement with the proposed method in temperature and pressure profiles to within 2% and post-shock velocity to within 15%. Reacting gas shock tube experiments in synthetic air and synthetic Titan atmospheres were analyzed. Radiance values in the non-equilibrium and equilibrium regions were compared under various assumptions for the shock structure and radial velocity distribution. These results highlight the necessity of a dedicated shock tube solver when analyzing shock tube thermochemistry, particularly when determining reaction rates and relaxation parameters.

Monitoring Turkey's nighttime light and environmental change.

Nighttime lighting (NTL), population growth, and climate change are critical concerns for Turkey. The intensity of nighttime lights in Turkey has significantly increased in recent years, closely associated with rapid population growth and urban expansion. Areas with higher population density exhibit greater nighttime light presence. Nighttime lighting is directly linked to energy consumption and greenhouse gas (GHG) emissions, contributing significantly to global climate change. The rise in nighttime lighting in Turkey exacerbates climate change effects. In this study, data on NTL were gathered from the NOAA/V21 satellite for 2013-2021, the NOAA/CMCFG satellite for average DMSP-OLS radiance values from 2013 to 2023, and the NOAA/VNP46A2 satellite for BRDF-corrected DMSP-OLS NTL data from 2013 to 2023. Night temperature values were extracted from NOAA and MODIS images, and their correlation with NTL data was analyzed. A moderate relationship was observed between NTL and night land surface temperature (LST) (R, 0.32; p-value < 0.05). Population and greenhouse gas emission data were sourced from the Turkish Statistical Institute (TurkStat). Carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and fluorinated gases (F-gases) are direct greenhouse gases. A strong correlation was found between NTL and greenhouse gases (R, 0.8; p-value < 0.05). Population density emerges as a significant determinant of nighttime light intensity. These findings underscore the substantial correlation between nighttime light intensity in Turkey, population dynamics, and GHG emissions. The study suggests that NTL data can inform the development of sustainable environmental policies. Mitigating greenhouse gas emissions necessitates controlling population growth and energy consumption, pivotal steps toward environmental sustainability.

Generation of monthly VIIRS nighttime lights time-series (1992–2013) images using deep learning (cGAN) technique

Satellite-based nighttime lights (NTL) are often used as indicators of the socioeconomic dynamics of an area. The Earth Observation Group at Colorado School of Mines provides monthly NTL products from the Day Night Band (DNB) sensor on board the Visible and Infrared Imaging Suite (VIIRS) satellite (April 2012 onwards) and from Operational Linescan System (OLS) sensor onboard the Defense Meteorological Satellite Program (DMSP) satellites (April 1992–December 2013). VIIRS-DNB (hereinafter referred to as VIIRS) and DMSP-OLS (hereinafter referred to as DMSP) NTL images have 15-arc second and 30-arc second spatial resolution, respectively. In the current study, an attempt has been made to generate synthetic (fine-resolution) monthly VIIRS-like products of 1992–2012 from (coarse-resolution) DMSP products, using a deep learning-based image translation network. Initially, the defects of the 216 monthly DMSP images (1992–2013) were corrected to remove geometric errors, background noise, and radiometric errors. Correction on monthly VIIRS imagery to remove background noise and ephemeral lights was done by thresholding. Improved monthly NTL images of DMSP-OLS and VIIRS from April 2012–December 2013 were used in a conditional generative adversarial network (cGAN) along with the land cover, as auxiliary input, to generate VIIRS-like monthly imagery from 1992 to 2012. The modelled imagery was aggregated annually, which showed an R2 of 0.94 with the results of other annual-scale VIIRS-like imagery products (2000–2020) over India; R2 of 0.85 w.r.t GDP; and R2 of 0.69 w.r.t population. Regression analysis of the generated VIIRS-like products with the actual VIIRS images for the years 2012 and 2013 over India indicated a good approximation with an R2 of 0.64 and 0.67 respectively, while the spatial density relation depicted an under-estimation of the brightness values by the model at extremely high radiance values with an R2 of 0.56 and 0.53 respectively. Qualitative analysis is also performed on both country and State scales. Visual analysis over 1992–2013 confirms a gradual increase in the brightness of the nighttime lights indicating that the cGAN model images closely represent the actual pattern followed by the nighttime lights. Finally, synthetically generated monthly VIIRS-like products are delivered to the research community which will be useful for studying the changes in socio-economic dynamics over time.

A 2‐Dimensional Data Detrending Technique for Equatorial Plasma Bubble Studies Using GOLD Far Ultraviolet Observations

AbstractWe formulate a numerical data detrending technique that can be used to help reveal large‐scale equatorial plasma bubble (EPB) structures in 2‐dimensional data from the Global‐scale Observations of the Limb and Disk (GOLD) mission. This GOLD data detrending technique is inspired by and is a generalization of a previous rolling‐barrel data detrending method for 1‐dimensional total electron content (TEC) observations on individual global positioning system (GPS) satellite passes. This 2‐dimensional GOLD data detrending technique treats the observed 135.6 nm radiance as a function of longitude and latitude as an uneven terrain, where EPBs appear as deep but narrow elongated valleys. The unperturbed background radiance is inferred by rolling a ball on the 2‐dimensional terrain to skip over the EPB valleys. The two degrees‐of‐freedom possessed by the rolling ball allow it to smoothly trace the edges of EPB depletions, without falling into the deep valleys. Surface interpolation of radiance values at the ball's contact points onto the whole domain produces the baseline radiance. Subtracting the baseline from the original radiance data yields the net detrended radiance. As a result of the detrending, sharper contrast is present between EPB depletions and the ambient surroundings. As such, this new 2‐dimensional GOLD data detrending may potentially open the door to the development of other more advanced techniques for automated EPB detection and tracking, or data assimilation into low‐latitude space domain awareness (SDA) information ecosystems.

Integrating Sigmoid Calibration Function into Entropy Thresholding Segmentation for Enhanced Recognition of Potholes Imaged Using a UAV Multispectral Sensor

This study was aimed at enhancing pothole detection by combining sigmoid calibration function and entropy thresholding segmentation on UAV multispectral imagery. UAV imagery was acquired via the flying of the DJI Matrice 600 (M600) UAV system, with the MicaSense RedEdge imaging sensor mounted on its fixed wing. An endmember spectral pixel denoting pothole feature was selected and used as the base from which spectral radiance patterns of a pothole were analyzed. A field survey was carried out to measure pothole diameters, which were used as the base on which the pothole area was determined. Entropy thresholding segmentation was employed to classify potholes. The sigmoid calibration function was used to reconfigure spectral radiance properties of the UAV spectral bands to pothole features. The descriptive statistics was computed to determine radiance threshold values to be used in demarcating potholes from the reconfigured or calibrated spectral bands. The performance of the sigmoid calibration function was evaluated by analyzing the area under curve (AUC) results generated using the Relative Operating Characteristic (ROC) technique. Spectral radiance pattern analysis of the pothole surface revealed high radiance values in the red channel and low radiance values in the near-infrared (NIR) channels of the spectrum. The sigmoid calibration function radiometrically reconfigured UAV spectral bands based on a total of 500 sampled pixels of pothole surface obtained from all the spectral channels. Upon successful calibration of UAV radiometric properties to pothole surface, the reconfigured mean radiance values for pothole surface were noted to be 0.868, 0.886, 0.944, 0.211 and 0.863 for blue, green, red, NIR and red edge, respectively. The area under curve (AUC) results revealed the r2 values of 0.53, 0.35, 0.71, 0.19 and 0.35 for blue, green, red, NIR and red edge spectral channels, respectively. Overestimation of pothole 1 by both original and calibrated spectral channels was noted and can be attributed to the presence of soils adjacent to the pothole. However, calibrated red channel estimated pothole 2 and pothole 3 accurately, with a slight area deviation from the measured potholes. The results of this study emphasize the significance of reconfiguring radiometric properties of the UAV imagery for improved recognition of potholes.

Abstract 45: Driving AMPK signaling in CD4+ CART cells enhances metabolic capacity, memory formation, and anti-leukemia activity

Abstract Background: While Chimeric Antigen Receptor (CAR)T cell therapy has seen great success in pediatric and young adult acute lymphoblastic leukemia, up to 50% of patients will relapse following treatment. Increased memory formation and mitochondrial capacity, particularly in the CD4+ subset, have been linked to improved CART cell function and enhanced in vivo persistence, leading to long-term relapse-free survival. AMP-activated protein kinase (AMPK) is a cellular energy sensor responsible for promoting metabolic efficiency and T cell memory formation. We have previously demonstrated AMPK activity can be increased in human T cells via overexpression of the AMPKγ2 domain. We hypothesized that overexpression of AMPKγ2 in CART cells would enhance their metabolic capacity and improve their anti-leukemia function. Methods: Human CART cells bearing a CD19-CAR utilizing a 41BB costimulatory domain were generated from healthy human donors via lentiviral transduction and co-transduced with AMPKγ2 (AMPK) or an empty vector (EV) control. Flow sorting for the co-transduced populations yielded &amp;gt;95% CD4+ CART cells. CARTs were expanded in IL-2 for approximately 2 weeks, followed by overnight stimulation and subsequent metabolic analysis using the Seahorse Metabolic Analyzer. Memory status was assessed by CD62L and CCR7 co-expression. In vitro CART function was assessed using Zs-green+ NALM6 targets, with loss of green fluorescence over time measured on the Incucyte analyzer. Where indicated, tumor conditioned media was harvested from 72-hour NALM6 cultures. For in vivo experiments, immunodeficient NOD-scid IL2Rγnull (NSG) mice were injected with luciferase+ NALM6 targets, followed one week later by AMPK- or EV-CARTs. Leukemia burden, via IVIS imaging, and survival were followed over time. Results: CD4+ CARTs co-transduced with AMPKγ2 (AMPK-CARTs) increased oxygen consumption, maximal respiration, and spare respiratory capacity following overnight stimulation by ~20% compared to CARTs co-transduced with the EV (EV-CARTs) (p&amp;lt;0.05). Following expansion, CD62L+CCR7+ central memory cells were 4.5-fold more abundant in the AMPK-CART group (2.4-6.2-fold, p&amp;lt;0.01). In vitro, while AMPK-CARTs demonstrated similar cytotoxicity against NALM6 targets as EV-CARTs in standard media, they mediated faster killing of NALM6 targets when challenged in tumor conditioned media (p&amp;lt;0.001). In vivo, recipients of AMPK-CARTs showed a consistent decrease in tumor burden as measured by median radiance values, translating to a significant survival advantage (p&amp;lt;0.05). Conclusions: Increasing AMPK signaling in CD4+ CARTs via overexpression of AMPKγ2 improved metabolic profile, increased memory generation, and enhanced toxicity against leukemia targets both in vitro and in vivo. Together, these features make elevating AMPK signaling an attractive method to increase the efficacy of CART therapy. Citation Format: Erica Braverman, Herbert Schuler, Mengtao Qin, Craig Byersdorfer. Driving AMPK signaling in CD4+ CART cells enhances metabolic capacity, memory formation, and anti-leukemia activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 45.

Verification of parameterizations for clear sky downwelling longwave irradiance in the Arctic

Abstract. Ground-based high resolution observations of downward longwave irradiance (DLI), surface air temperature, water vapor surface partial pressure and column amount, zenith sky infrared (IR) radiance in the atmospheric window, and all-sky camera images are regularly obtained at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5° N, 68.8° W), northwestern Greenland. The datasets for the years 2017 and 2018 have been used to assess the performance of different empirical formulas used to infer clear sky DLI. An algorithm to identify clear sky observations has been developed, based on value, variability, and persistence of zenith sky IR radiance. Seventeen different formulas to estimate DLI have been tested against the THAAO dataset, using the originally determined coefficients. The formulas that combine information on total column water vapor and surface air temperature appear to perform better than others, with a mean bias with respect to the measured DLI smaller than 1 W m−2 and a root mean squared error (RMSE) around 6 W m−2. Unexpectedly, some formulas specifically developed for the Arctic are found to produce poor statistical results. This is attributed partly to limitations in the originally used dataset, which does not cover a whole year or is relative to very specific condition (i.e., the presence of an ice sheet). As expected, the bias displays a significant improvement when the coefficients of the different formulas are calculated using the THAAO dataset. The presence of 2 full years of data allows the determination and the applicability of the coefficients for singular years and the evaluation of results. The smallest values of the bias and RMSE reach 0.1 and 5 W m−2, respectively. Overall, the best results are found for formulas that use both surface parameters and total water vapor column content, and have been developed from global datasets. Conversely, formulas that express the atmospheric emissivity as a linear function of the logarithm of the column integrated water vapor appear to reproduce poorly the observations at THAAO.

Low-latency equal optical path difference sampling for multi-field VLWIR interference signals

The spaceborne Fourier Transform Spectrometer has been utilized for vertical atmospheric soundings with a HgCdTe infrared focal plane arrays (FPAs) detector. However, the VLWIR FPA Fourier spectrometer system faces the difficulty of poor sensitivity due to the major contribution of the system sampling error. In this work, low-latency data acquisition of multi-field VLWIR interference signals based on VLWIR FPA Fourier spectrometer system is realized with an optimized field programmable gate array (FPGA) timing driver scheme and layout algorithm. This scheme can effectively reduce routing delay and constrain critical timing paths, and thus leads to a significant decrease in the deviation of equal optical path difference sampling time from 10.27μs to 0.10μs. Interferograms and spectrograms are efficiently obtained. Furthermore, the average value of noise equivalent spectral radiance (NESR) in VLWIR FPA Fourier spectrometer system, is reduced by 1.75% by timing optimization. In particular, the decay of the NESR can be as high as 15% for some of the pixels. These results illustrate that the proposed scheme will acquire hyperspectral data accurately with VLWIR FPA and meet the needs of rapid soundings development of the Geostationary Interferometric Infrared Sounder (GIIRS) availing a rapid prediction of the appearance of an extreme weather event.

A new method for voxel‐based modelling of three‐dimensional forest scenes with integration of terrestrial and airborne LiDAR data

Abstract Simulating realistic three‐dimensional (3D) forest scenes is useful in understanding the links between forest structure and ecosystem functions (e.g. radiative transfer). Light detection and ranging (LiDAR) technology provides useful 3D data for forest reconstructions since it can characterise 3D structures of individual trees and canopies. High‐density terrestrial LiDAR (terrestrial laser scanning, TLS) is suitable for fine‐scale reconstructions but is limited to smaller forest plots; low‐density airborne LiDAR (airborne laser scanning, ALS) can cover larger areas but is only suitable for coarse‐scale reconstructions. How to take advantage of TLS and ALS to enable fine‐scale forest simulations in large areas needs to be studied. We propose a new voxel‐based method for forest simulations using the integration of TLS and ALS data. TLS data of representative reference trees are used to approximate the detailed architectures of the whole forest scene, with structural information on each individual tree extracted from ALS data. The high‐density point cloud data derived from TLS and ALS data are voxelised using high resolution solid voxels for scene representation. We tested the proposed method using two virtual forests (108 m × 108 m) and a real forest (300 m × 300 m) with conifer and broadleaf species. The physically based ray tracer (PBRT) was used to visualise the true virtual forest scenes, whereas voxel‐based radiative transfer (VBRT) was used to visualise the modelled forest scenes from LiDAR data. For the real forest scene, simulated and real ALS data were compared. Our results demonstrate that the images simulated by VBRT and PBRT are similar in the virtual forest scenes, with average radiance values of 1.02 and 1.72, respectively. In the real forest scene, the distributions of points and individual tree attributes (tree height, crown radius, and tree volume) derived from real and simulated ALS also match well, with Kullback–Leibler divergence ranging from 0.006 to 0.06. We conclude that the new method is capable of modelling fine‐scale 3D forests in large areas (over 1 ha) when TLS and ALS data are available, and it has good potential in studying the process of radiative transfer in conifer and broadleaf forests.

Hazards associated with blue light emitted during gas metal arc welding of mild steel using various shielding gases and currents.

Blue light emitted during arc welding is known to potentially cause photoretinopathy. To help prevent retinal injury, it is important to identify the hazards associated with various welding conditions. The present work conducted experiments involving gas metal arc welding of mild steel under various conditions, and measured the spectral radiance of the arcs. The effective radiance values, as used by the American Conference of Governmental Industrial Hygienists (ACGIH) to quantify exposure level of blue light, were subsequently calculated from the data. The resulting values were in the range of 5.0-118 W/cm2/sr, corresponding to hazardous levels according to ACGIH guidelines. The effective radiance was increased at higher welding currents and when pulsed currents were used rather than steady currents. The blue light hazard was also affected by the type of shielding gas employed. These data confirm that it is very hazardous to stare at arcs during gas metal arc welding of mild steel. As such, appropriate eye protection is necessary during arc welding, and directly staring at the arc should be avoided.

Photometric correction of images obtained from Chandrayaan-2 Imaging Infra-Red Spectrometer (IIRS) data

India’s second mission to the Moon, Chandrayaan-2, carried one of the most advanced imaging spectrometers ever sent to image a planetary surface – the IIRS (Imaging Infra-Red Spectrometer) – a 250 band spectrometer developed at the Space Applications Centre (SAC), ISRO, India. In this study, IIRS data between 800 and 2000 nm have been used to derive photometrically corrected reflectance from calibrated radiance data supplied by ISRO’s online archive (Pradan) of Chandrayaan-2 data. Additionally, the photometric properties of three IIRS bands (950, 1500, and 1700 nm) have been studied in detail. Since the images obtained by IIRS are at different viewing geometry orientations, the purpose of performing a photometric correction on IIRS images is to re-project each pixel to a standard viewing geometry of incidence angle, i = 30°, emission angle, e = 0° and, phase angle, α = 30°. In order to correct the lunar limb darkening effect, a combination of the Lommel-Seeliger function and McEwen’s model was used. In addition, topographic data from the merged Digital Elevation Model of Lunar Reconnaissance Orbiter – Lunar Orbiter Laser Altimeter (LRO-LOLA) and SELENE Terrain Camera (TC) were utilized to remove effects from local topography. A photometric function was then applied on four images captured by IIRS which were included in the first public release of data in August 2021. Radiance and reflectance (obtained after implementing photometric correction on IIRS images) values were compared with L1 and L2 M3 (Moon Mineralogy Mapper) data from Chandrayaan-1. It was found that although IIRS images are much darker than M3, corrected IIRS reflectance images had a much smaller variation in terms of reflectance values with M3. Moreover, the associated spectral reddening and reflectance values are within range when compared with data from other lunar missions. In addition, the reflectance spectra derived from the corrected IIRS images have been plotted for each image. However, the spectra exhibit significantly deeper absorptions than their corresponding M3 data for the same pixel. Phase functions derived from three bands have a good correlation with the reflectance values and phase angles. Consequently, this function can be applied to all IIRS images as and when more data are released to the public.

Towards Accurate Radiometric Calibration of INSAT-3D and INSAT-3DR IMAGER: Addressing Uncertainty and Error Sources

ABSTRACT The proper radiometric calibration of the INSAT-3D and −3DR IMAGER is of utmost importance for effective weather forecasting and monitoring. Accurate and reliable images are crucial for predicting weather patterns, tracking storms, and assessing the impact of natural disasters. This research paper presents an evaluation of the radiometric calibration of the INSAT-3D and −3DR IMAGER using a reflectance-based method referenced to in-situ ground site measurements. Calibration campaigns were conducted at the Great Rann of Kutch (GROK) in Gujarat, India during February 2022 to ensure synchronous measurements of surface reflectance and atmospheric variables. In this study, the radiative transfer model called 6 SV (Second Simulation of a Satellite Signal in the Solar Spectrum Vector) was employed to simulate the Top-Of-Atmospheric (TOA) radiance. The calibration coefficients for the Visible (VIS) and Short Wave Infrared (SWIR) bands of the IMAGER were determined by comparing the TOA radiance obtained from the radiative transfer model with the Level 1B product of satellite data. The results convincingly demonstrate that the reflectance-based calibration method yields highly accurate and reliable radiometric calibration for both the VIS and SWIR bands of the INSAT-3D and −3DR IMAGER, with an uncertainty significantly smaller than the expected sensor degradation. Specifically, it was found that the VIS band of INSAT-3D underestimates the radiance value by 9.05%, while the VIS band of INSAT-3DR underestimates it by 4.88%. The study also discusses various sources of uncertainty and emphasizes the need for comprehensive uncertainty quantification to ensure the radiometric accuracy of the IMAGER data. Overall, the calibration results indicate that the absolute radiometric accuracy for the VIS and SWIR bands of the IMAGER on-board INSAT-3D and INSAT-3DR satellites is better than 4%. This research contributes to enhancing the reliability and usability of the INSAT-3D and −3DR IMAGER data for weather forecasting and monitoring applications.

Retrieval of aerosol properties from zenith sky radiance measurements

Abstract. This study explores the potential to retrieve aerosol properties with the GRASP algorithm (Generalized Retrieval of Atmosphere and Surface Properties) using as input measurements of zenith sky radiance (ZSR), which are sky radiance values measured in the zenith direction, recorded at four wavelengths by a ZEN-R52 radiometer. To this end, the ZSR measured at 440, 500, 675 and 870 nm by a ZEN-R52 (ZSRZEN), installed in Valladolid (Spain), is employed. This instrument is calibrated by intercomparing the signal of each channel with coincident ZSR values simulated (ZSRSIM) at the same wavelengths with a radiative transfer model (RTM). These simulations are carried out using the GRASP forward module as RTM and the aerosol information from a co-located CE318 photometer belonging to AERONET (AErosol RObotic NETwork) as input. The dark signal and the signal dependence on temperature are characterized and included in the calibration process. The uncertainties for each channel are quantified by an intercomparison with a co-located CE318 photometer, obtaining lower values for shorter wavelengths; they are between 3 % for 440 nm and 21 % for 870 nm. The proposed inversion strategy for the aerosol retrieval using the ZSRZEN measurements as input, i.e. so-called GRASP-ZEN, assumes the aerosol as an external mixture of five pre-calculated aerosol types. A sensitivity analysis is conducted using synthetic ZSRZEN measurements, pointing out that these measurements are sensitive to aerosol load and type. It also assesses that the retrieved aerosol optical depth (AOD) values in general overestimate the reference ones by 0.03, 0.02, 0.02 and 0.01 for 440, 500, 675 and 870 nm, respectively. The calibrated ZSRZEN measurements, recorded during 2.5 years at Valladolid, are inverted by the GRASP-ZEN strategy to retrieve some aerosol properties like AOD. The retrieved AOD shows a high correlation with respect to independent values obtained from a co-located AERONET CE318 photometer, with determination coefficients (r2) of 0.86, 0.85, 0.79 and 0.72 for 440, 500, 675 and 870 nm, respectively, and finding uncertainties between 0.02 and 0.03 with respect to the AERONET values. Finally, the retrieval of other aerosol properties, like aerosol volume concentration for total, fine and coarse modes (VCT, VCF and VCC, respectively), is also explored. The comparison against independent values from AERONET presents r2 values of 0.57, 0.56 and 0.66 and uncertainties of 0.009, 0.016 and 0.02 µm3 µm−2 for VCT, VCF and VCC, respectively.

Mapping urban living standards and economic activity in developing countries with energy data.

Urban data deficits in developing countries impede evidence-based planning and policy. Could energy data be used to overcome this challenge by serving as a local proxy for living standards or economic activity in large urban areas? To answer this question, we examine the potential of georeferenced residential electricity meter data and night-time lights (NTL) data in the megacity of Karachi, Pakistan. First, we use nationally representative survey data to establish a strong association between electricity consumption and household living standards. Second, we compare gridded radiance values from NTL data with a unique dataset containing georeferenced median monthly electricity consumption values for over 2 million individual households in the city. Finally, we develop a model to explain intra-urban variation in radiance values using proxy measures of economic activity from Open Street Map. Overall, we find that NTL data are a poor proxy for living standards but do capture spatial variation in population density and economic activity. By contrast, electricity data are an excellent proxy for living standards and could be used more widely to inform policy and support poverty research in cities in low- and middle-income countries.

Progressive photon mapping algorithm for digital imaging of a space target.

Space target imaging simulation holds great significance for the development of space-based imaging systems and the prediction of imaging tasks. Currently, commonly used rendering algorithms in space target imaging simulation suffer from issues such as radiance calculation results lacking actual physical significance and rendered images containing high-frequency noise. To address these issues, this study proposes a rendering algorithm based on progressive photon mapping in the context of space imaging scenarios, aiming to enhance the accuracy of energy calculations and image rendering for space targets. This algorithm generates multiple photon maps on the target surface through multiple iterations, retrieves photon information near the observation point based on these photon maps, and thus obtains the radiance of the observation direction vector. This study evaluates the quality of rendered images using no-reference image quality assessment algorithms. The results demonstrate that this algorithm can enhance image rendering quality in specific imaging scenarios, consequently improving the accuracy of space target recognition. By comparing the calculated values of this algorithm with the theoretical radiance values for diffuse material, the accuracy of the radiance calculation results of this algorithm is verified, which can provide significant reference values for the selection of backend detectors.

Exploring the Relationship between Temporal Fluctuations in Satellite Nightlight Imagery and Human Mobility across Africa

Mobile phone data have been increasingly used over the past decade or more as a pretty reliable indicator of human mobility to measure population movements and the associated changes in terms of population presence and density at multiple spatial and temporal scales. However, given the fact mobile phone data are not available everywhere and are generally difficult to access and share, mostly because of commercial restrictions and privacy concerns, more readily available data with global coverage, such as night-time light (NTL) imagery, have been alternatively used as a proxy for population density changes due to population movements. This study further explores the potential to use NTL brightness as a short-term mobility metric by analysing the relationship between NTL and smartphone-based Google Aggregated Mobility Research Dataset (GAMRD) data across twelve African countries over two periods: 2018–2019 and 2020. The data were stratified by a measure of the degree of urbanisation, whereby the administrative units of each country were assigned to one of eight classes ranging from low-density rural to high-density urban. Results from the correlation analysis, between the NTL Sum of Lights (SoL) radiance values and three different GAMRD-based flow metrics calculated at the administrative unit level, showed significant differences in NTL-GAMRD correlation values across the eight rural/urban classes. The highest correlations were typically found in predominantly rural areas, suggesting that the use of NTL data as a mobility metric may be less reliable in predominantly urban settings. This is likely due to the brightness saturation and higher brightness stability within the latter, showing less of an effect than in rural or peri-urban areas of changes in brightness due to people leaving or arriving. Human mobility in 2020 (during COVID-19-related restrictions) was observed to be significantly different than in 2018–2019, resulting in a reduced NTL-GAMRD correlation strength, especially in urban settings, most probably because of the monthly NTL SoL radiance values remaining relatively similar in 2018–2019 and 2020 and the human mobility, especially in urban settings, significantly decreasing in 2020 with respect to the previous considered period. The use of NTL data on its own to assess monthly mobility and the associated fluctuations in population density was therefore shown to be promising in rural and peri-urban areas but problematic in urban settings.

Radiometric Compensation for Occluded Crops Imaged Using High-Spatial-Resolution Unmanned Aerial Vehicle System

Crop characterization is considered a prerequisite to devising effective strategies for ensuring successful implementation of sustainable agricultural management strategies. As such, remote-sensing technology has opened an exciting horizon for crop characterization at reasonable spatial, spectral, and temporal scales. However, the presence of shadows on croplands tends to distort radiometric properties of the crops, subsequently limiting the retrieval of crop-related information. This study proposes a simple and reliable approach for radiometrically compensating crops under total occlusion using brightness-based compensation and thresholding approaches. Unmanned aerial vehicle (UAV) imagery was used to characterize crops at the experimental site. In this study, shadow was demarcated through the computation and use of mean spectral radiance values as the threshold across spectral channels of UAV imagery. Several image classifiers, viz., k-nearest neighbor (KNN), maximum likelihood, multilayer perceptron (MLP), and image segmentation, were used to categorize land features, with a view to determine the areal coverage of crops prior to the radiometric compensation process. Radiometric compensation was then performed to restore radiometric properties of land features under occlusion by performing brightness tuning on the RGB imagery. Radiometric compensation results revealed maize and soil as land features subjected to occlusion. The relative error of the mean results for radiance comparison between lit and occluded regions revealed 26.47% deviation of the restored radiance of occluded maize from that of lit maize. On the other hand, the reasonable REM value of soil was noted to be 50.92%, implying poor radiometric compensation results. Postradiometric compensation classification results revealed increases in the areal coverage of maize cultivars and soil by 40.56% and 12.37%, respectively, after being radiometrically compensated, as predicted by the KNN classifier. The maximum likelihood, MLP, and segmentation classifiers predicted increases in area covered with maize of 18.03%, 22.42%, and 30.64%, respectively. Moreover, these classifiers also predicted increases in the area covered with soil of 1.46%, 10.05%, and 14.29%, respectively. The results of this study highlight the significance of brightness tuning and thresholding approaches in radiometrically compensating occluded crops.

High Spatial Resolution Ozone Profiles Retrieved from the First Chinese Ultraviolet–Visible Hyperspectral Satellite Instrument

Understanding the vertical distribution of ozone is crucial when assessing both its horizontal and vertical transport, as well as when analyzing the physical and chemical properties of the atmosphere. One of the most effective ways to obtain high spatial resolution ozone profiles is through satellite observations. The Environmental Trace Gases Monitoring Instrument (EMI) deployed on the Gaofen-5 satellite is the first Chinese ultraviolet–visible hyperspectral spectrometer. However, retrieving ozone profiles using backscattered radiance values measured by the EMI is challenging due to unavailable measurement errors and a low signal-to-noise ratio. The algorithm developed for the Tropospheric Monitoring Instrument did not allow us to retrieve 87% of the EMI pixels. Therefore, we developed an algorithm specific to the characteristics of the EMI. The fitting residuals are smaller than 0.3% in most regions. The retrieved ozone profiles were in good agreement with ozonesonde data, with maximum mean biases of 20% at five latitude bands. By applying EMI averaging kernels to the ozonesonde profiles, the integrated stratospheric column ozone and tropospheric column ozone also showed excellent agreement with ozonesonde data. The lower layers (0–7.5 km) of the EMI ozone profiles reflected the seasonal variation in surface ozone derived from the China National Environmental Monitoring Center (CNEMC). However, the upper layers (9.7–16.7 km) of the ozone profiles show different trends, with the ozone peak occurring at an altitude of 9.7–16.7 km in March, 2019. A stratospheric intrusion event in central China from August 11 to 15, 2019, is captured using the EMI ozone profiles, potential vorticity data, and relative humidity data. The increase in the CNEMC ozone concentration showed that downward transport enhanced surface ozone pollution.

The radiometric environment for Mars limb observations by the Mars Sample Return Earth Return Orbiter

After launching from the martian surface via the Mars Ascent Vehicle (MAV), the MAV and the Orbiting Sample (OS) capsule containing the samples collected on Mars by the Perseverance rover are to be identified by the Narrow Angle Camera (NAC) on the Earth Return Orbiter (ERO) spacecraft in order to determine the exact orbit of the capsule before rendezvous. To ensure detection of the OS, noise and straylight contributions to the NAC must be well characterized. Here, we assess the radiometric environment at Mars likely to be encountered by the NAC—from the surface through the middle atmosphere—using the High Resolution Stereo Camera (HRSC) onboard Mars Express (MEx) and the Mars Climate Sounder (MCS) onboard the Mars Reconnaissance Orbiter (MRO). The results show that the radiance values in general tend to increase as phase angle increases, as the season progresses from Ls = 60° to Ls = 230°, and as altitude decreases. We compare HRSC and MCS profiles where observing conditions were similar and find good agreement. At specific latitudes, high-altitude aerosols are present in 1–5% of observations and significantly increase the worst-case radiance contribution above 50 km. We construct envelope profiles from the maximum radiances at 5 km intervals from 0 to 90 km that provide important input for straylight calculations of the NAC and for the validation of models that may be used as input for straylight calculations.

Bringing to Light the Potential of Angular Nighttime Composites for Monitoring Human Activities in the Brazilian Legal Amazon

The Brazilian Legal Amazon (BLA) is the largest administrative unit in Brazil. The region has undergone a series of territorial policies that have led to specific conditions of occupation of the land and particular urban environments. This plurality expresses specific physical relations with the environment and infrastructure, which require innovative methods for detecting and profiling human settlements in this region. The aim of this work is to demonstrate how angular composites of nighttime lights can be associated with specific profiles of urban infrastructure, sociodemographic parameters, and mining sites present in the BLA. We make use of sets of yearly VNP46A4 angular composites specifically associated with the narrowest ranges of observations across the year, i.e., observations right below the sensor’s pathway (near-nadir range) and observations in between the oblique range (off-nadir), to identify urban typologies that expose the presence of structures such as vertical buildings, industrial sites, and areas with different income levels. Through a non-parametric evaluation of the simple difference in radiance values ranging from 2012 to 2021, followed by an ordinary least squares regression (OLS), we find that off-nadir values are persistently higher than near-nadir values except in areas where obstructing structures and particular anisotropic characteristics are present, generally changing trends of the so-called angular effect. We advocate that relational metrics can be extracted from the angular annual composites to provide additional information on the current urban structural state. By calculating the simple difference (DIF), the relative difference (REL), and the residual values of the linear regression formula estimated for the off-nadir and near-nadir composites (RES), it is possible to differentiate urban environments by their physical aspects, such as high-mid income areas, low-income settlements with different levels of density, industrial sites, and verticalized areas. Moreover, pixels that were exclusively found in one of the angular composites could be spatially associated with phenomena such as the overglow effect for the exclusive off-nadir samples and with the wetlands of the northwest portion of the Amazon Forest for the near-nadir samples. This work deepens our current understanding of how to optimize the use of the VNP46A4 angular series for monitoring human activities in the Amazon biome and provides further directions on research possibilities concerning nighttime light angular composites.