1,360 research outputs found

    FORUM Earth Explorer 9: Characteristics of Level 2 Products and Synergies with IASI-NG

    Get PDF
    open10siFunding: The work presented was supported by the ESA–ESTEC Contract No. 4000124803/18/NL/CT, FORUM: consolidation of requirements and reference scenariosFORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) has been approved to be the ninth Earth Explorer mission of the European Space Agency. The mission is scheduled for launch on a Polar satellite in the 2025–2026 time frame. The core FORUM instrument is a Fourier Transform Spectrometer measuring, with very high accuracy, the upwelling spectral radiance, from 100 to 1600 cm^-1 (from 100 to 6.25 microns in wavelength), thus covering the Far-Infrared (FIR), and a Mid-Infrared (MIR) portion of the spectrum emitted by the Earth. FORUM will fly in loose formation with the MetOp-SG-1A satellite, hosting the Infrared Atmospheric Sounding Interferometer – New Generation (IASI-NG). IASI-NG will measure only the MIR part of the upwelling atmospheric spectrum, from 645 to 2760 cm^-1 (from 15.5 to 3.62 microns in wavelength), thus, the matching FORUM measurements will supply the missing FIR complement. Together, the two missions will provide, for the first time, a spectrally resolved measurement of the full Earth emitted thermal spectrum. The calibrated spectral radiance will be, on its own, the main product of the FORUM mission, however, the radiances will also be processed up to Level 2, to determine the vertical profile of water vapour, surface spectral emissivity and cloud parameters in the case of cloudy atmospheres. In this paper we assess the performance of the FORUM Level 2 products based on clear-sky simulated retrievals and we study how the FORUM and IASI-NG matching measurements can be fused in a synergistic retrieval scheme, to provide improved Level 2 products. Considering only the measurement noise and the systematic calibration error components, we find the following figures for the synergistic FORUM and IASI-NG retrieval products. In the upper troposphere/lower stratosphere region, individual water vapour profiles can be retrieved with 1 km vertical sampling and an error ranging from 10% to 15%. In the range from 300 to 600 cm^-1 , surface spectral emissivity can be retrieved with an absolute error as small as 0.001 in dry Polar atmospheres. Ice cloud parameters such as ice water path and cloud top height can be retrieved with errors smaller than 10% and 1 km, respectively, for ice water path values ranging from 0.2 to 60 g/m^2openRidolfi, Marco; Del Bianco, Samuele; Di Roma, Alessio; Castelli, Elisa; Belotti, Claudio; Dandini, Paolo; Di Natale, Gianluca; Dinelli, Bianca Maria; C.-Labonnote, Laurent; Palchetti, LucaRidolfi, Marco; Del Bianco, Samuele; Di Roma, Alessio; Castelli, Elisa; Belotti, Claudio; Dandini, Paolo; Di Natale, Gianluca; Dinelli, Bianca Maria; C.-Labonnote, Laurent; Palchetti, Luc

    Evaluation of inversion algorithms on DIRSIG generated plume model simulations

    Get PDF
    Remote sensing of factory stack and cooling tower plumes has the potential to reveal information about the constituents of the plumes. In the case of factory stacks, the determination of the chemical makeup and concentration of the plume may help determine the products produced by the factory. In the case of cooling towers, the temperature and water droplet characteristics may reveal information about the power output of the station. Synthetically generated images will help in the investigation of plume phenomenology and further help in the understanding of remote sensing of plumes. Using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) ray tracing code, these synthetic images can be used to predict sensor performance under various conditions and provide a way to test remote sensing algorithms. DIRSIG is a radiometrically correct ray-tracer which was developed at Rochester Institute of Technology by Digital Imaging and Remote Sensing (DIRS) laboratory. With this tool synthetic scenes can be rendered to test sensor performance under various conditions. Algorithms designed to determine effluent concentrations can be tested on these images to determine their accuracy and robustness. Synthetic plume imagery also reveals how plumes interact with the background and surrounding atmosphere. Sensitivity studies using passive remote sensing can provide information on plumes over a wide spectral band and with the use of multispectral image fusion additional information may be gathered. These studies are done on the plume-background contrast based on changes in the plume characteristic. Using inverse algorithms with DIRSIG, plume characteristics, such as species and concentrations, can be determined

    An Analysis of multimodal sensor fusion for target detection in an urban environment

    Get PDF
    This work makes a compelling case for simulation as an attractive tool in designing cutting-edge remote sensing systems to generate the sheer volume of data required for a reasonable trade study. The generalized approach presented here allows multimodal system designers to tailor target and sensor parameters for their particular scenarios of interest via synthetic image generation tools, ensuring that resources are best allocated while sensors are still in the design phase. Additionally, sensor operators can use the customizable process showcased here to optimize image collection parameters for existing sensors. In the remote sensing community, polarimetric capabilities are often seen as a tool without a widely accepted mission. This study proposes incorporating a polarimetric and spectral sensor in a multimodal architecture to improve target detection performance in an urban environment. Two novel multimodal fusion algorithms are proposed--one for the pixel level, and another for the decision level. A synthetic urban scene is rendered for 355 unique combinations of illumination condition and sensor viewing geometry with the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model, and then validated to ensure the presence of enough background clutter. The utility of polarimetric information is shown to vary with the sun-target-sensor geometry, and the decision fusion algorithm is shown to generally outperform the pixel fusion algorithm. The results essentially suggest that polarimetric information may be leveraged to restore the capabilities of a spectral sensor if forced to image under less than ideal circumstances

    Satellite-based Cloud Remote Sensing: Fast Radiative Transfer Modeling and Inter-Comparison of Single-/Multi-Layer Cloud Retrievals with VIIRS

    Get PDF
    This dissertation consists of three parts, each of them, progressively, contributing to the problem of great importance that satellite-based remote sensing of clouds. In the first section, we develop a fast radiative transfer model specialized for Visible Infrared Imaging Radiometer Suite (VIIRS), based on the band-average technique. VIIRS, is a passive sensor flying aboard the NOAA’s Suomi National Polar-orbiting Partnership (NPP) spacecraft. This model successfully simulates VIIRS solar and infrared bands, in both moderate (M-bands) and imagery (I-bands) spatial resolutions. Besides, the model is two orders of magnitude faster than Line-by-line & discrete ordinate transfer (DISORT) method with a great accuracy. The second and third parts are going to investigate the retrieval of single-/multi- layer cloud optical properties, especially, cloud optical thickness (τ) and cloud effective particle size (De) with different methods. By presenting the comparison between results derived from VIIRS measurements and benchmark products, potential applications of Bayesian and OE retrieval methods for cloud property retrieval are discussed. It has proved that Bayesian method is more suitable for single-layer scenarios with fewer variables with fast speed, while Optimal Estimation method is superior to Bayesian method for more complicated multi-layer scenarios

    Modeling wildland fire radiance in synthetic remote sensing scenes

    Get PDF
    This thesis develops a framework for implementing radiometric modeling and visualization of wildland fire. The ability to accurately model physical and op- tical properties of wildfire and burn area in an infrared remote sensing system will assist efforts in phenomenology studies, algorithm development, and sensor evaluation. Synthetic scenes are also needed for a Wildland Fire Dynamic Data Driven Applications Systems (DDDAS) for model feedback and update. A fast approach is presented to predict 3D flame geometry based on real time measured heat flux, fuel loading, and wind speed. 3D flame geometry could realize more realistic radiometry simulation. A Coupled Atmosphere-Fire Model is used to de- rive the parameters of the motion field and simulate fire dynamics and evolution. Broad band target (fire, smoke, and burn scar) spectra are synthesized based on ground measurements and MODTRAN runs. Combining the temporal and spa- tial distribution of fire parameters, along with the target spectra, a physics based model is used to generate radiance scenes depicting what the target might look like as seen by the airborne sensor. Radiance scene rendering of the 3D flame includes 2D hot ground and burn scar cooling, 3D flame direct radiation, and 3D indirect reflected radiation. Fire Radiative Energy (FRE) is a parameter defined from infrared remote sensing data that is applied to determine the radiative energy released during a wildland fire. FRE derived with the Bi-spectral method and the MIR radiance method are applied to verify the fire radiance scene synthesized in this research. The results for the synthetic scenes agree well with published values derived from wildland fire images

    3-D longwave infrared synthetic scene simulation

    Get PDF
    A technique for thermal infrared (8-14 micrometers) synthetic image generation (SIG) was demonstrated that yields improved radiometric accuracy. This process utilizes the LOWTRAN 6 atmospheric propagation model and computer graphics ray-tracing techniques. A scene is created by placing faceted objects into world coordinates with rotation, translation, and scaling parameters. Each facet is assigned a material index and temperature. This index points to angular emissivity data for that material. LOWTRAN 6 can incorporate a sensor response function when calculating data files for the atmospheric transmission, upwelled and downwelled radiances, and temperature-to-radiance conversions. Ray-traced imagery is generated and discussed. The image is then further processed using convolution to represent the modulation transfer function of the imaging system. The final infrared synthetic image is then compared to an actual thermal image. An average apparent temperature difference of 2.50C is reported with a 1.52C standard deviation. These temperatures fall within predicted error analysis limits

    Cirrus cloud identification from airborne far-infrared and mid-infrared spectra

    Get PDF
    Airborne interferometric data, obtained from the Cirrus Coupled Cloud-Radiation Experiment (CIRCCREX) and from the PiknMix-F field campaign, are used to test the ability of a machine learning cloud identification and classification algorithm (CIC). Data comprise a set of spectral radiances measured by the Tropospheric Airborne Fourier Transform Spectrometer (TAFTS) and the Airborne Research Interferometer Evaluation System (ARIES). Co-located measurements of the two sensors allow observations of the upwelling radiance for clear and cloudy conditions across the far-and mid-infrared part of the spectrum. Theoretical sensitivity studies show that the performance of the CIC algorithm improves with cloud altitude. These tests also suggest that, for conditions encompassing those sampled by the flight campaigns, the additional information contained within the far-infrared improves the algorithm's performance compared to using mid-infrared data only. When the CIC is applied to the airborne radiance measurements, the classification performance of the algorithm is very high. However, in this case, the limited temporal and spatial variability in the measured spectra results in a less obvious advantage being apparent when using both mid-and far-infrared radiances compared to using mid-infrared information only. These results suggest that the CIC algorithm will be a useful addition to existing cloud classification tools but that further analyses of nadir radiance observations spanning the infrared and sampling a wider range of atmospheric and cloud conditions are required to fully probe its capabilities. This will be realised with the launch of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission, ESA's 9th Earth Explorer

    Infrared based monocular relative navigation for active debris removal

    No full text
    In space, visual based relative navigation systems suffer from the harsh illumination conditions of the target (e.g. eclipse conditions, solar glare, etc.). In current Rendezvous and Docking (RvD) missions, most of these issues are addressed by advanced mission planning techniques (e.g strict manoeuvre timings). However, such planning would not always be feasible for Active Debris Removal (ADR) missions which have more unknowns. Fortunately, thermal infrared technology can operate under any lighting conditions and therefore has the potential to be exploited in the ADR scenario. In this context, this study investigates the benefits and the challenges of infrared based relative navigation. The infrared environment of ADR is very much different to that of terrestrial applications. This study proposes a methodology of modelling this environment in a computationally cost effective way to create a simulation environment in which the navigation solution can be tested. Through an intelligent classification of possible target surface coatings, the study is generalised to simulate the thermal environment of space debris in different orbit profiles. Through modelling various scenarios, the study also discusses the possible challenges of the infrared technology. In laboratory conditions, providing the thermal-vacuum environment of ADR, these theoretical findings were replicated. By use of this novel space debris set-up, the study investigates the behaviour of infrared cues extracted by different techniques and identifies the issue of short-lifespan features in the ADR scenarios. Based on these findings, the study suggests two different relative navigation methods based on the degree of target cooperativeness: partially cooperative targets, and uncooperative targets. Both algorithms provide the navigation solution with respect to an online reconstruction of the target. The method for partially cooperative targets provides a solution for smooth trajectories by exploiting the subsequent image tracks of features extracted from the first frame. The second algorithm is for uncooperative targets and exploits the target motion (e.g. tumbling) by formulating the problem in terms of a static target and a moving map (i.e. target structure) within a filtering framework. The optical flow information is related to the target motion derivatives and the target structure. A novel technique that uses the quality of the infrared cues to improve the algorithm performance is introduced. The problem of short measurement duration due to target tumbling motion is addressed by an innovative smart initialisation procedure. Both navigation solutions were tested in a number of different scenarios by using computer simulations and a specific laboratory set-up with real infrared camera. It is shown that these methods can perform well as the infrared-based navigation solutions using monocular cameras where knowledge relating to the infrared appearance of the target is limited
    • …
    corecore