Atmospheric Transmission Model Research Articles

Polarization-Based Two-Stage Image Dehazing in a Low-Light Environment

Fog, as a common weather condition, severely affects the visual quality of images. Polarization-based dehazing techniques can effectively produce clear results by utilizing the atmospheric polarization transmission model. However, current polarization-based dehazing methods are only suitable for scenes with strong illumination, such as daytime scenes, and cannot be applied to low-light scenes. Due to the insufficient illumination at night and the differences in polarization characteristics between it and sunlight, polarization images captured in a low-light environment can suffer from loss of polarization and intensity information. Therefore, this paper proposes a two-stage low-light image dehazing method based on polarization. We firstly construct a polarization-based low-light enhancement module to remove noise interference in polarization images and improve image brightness. Then, we design a low-light polarization dehazing module, which combines the polarization characteristics of the scene and objects to remove fog, thereby restoring the intensity and polarization information of the scene and improving image contrast. For network training, we generate a simulation dataset for low-light polarization dehazing. We also collect a low-light polarization hazy dataset to test the performance of our method. Experimental results indicate that our proposed method can achieve the best dehazing effect.

X-ray pulsar observation signals simulation method at the spacecraft in near-Earth space

The near-Earth space holds significant strategic value, and X-ray pulsar-based navigation in this region can diversify navigation methods, enhancing the safety and autonomy of spacecraft. Due to the challenges and high costs associated with obtaining actual measurements of pulsars in near-Earth space, the simulation technology for X-ray pulsar signals in this region can provide input for demonstrating the feasibility of technical solutions and experiments related to the application of X-ray pulsar-based navigation in near-Earth space. Therefore, this paper proposes a method for simulating X-ray signals in near-Earth space. Firstly, a scale transforming method is employed to generate a photon arrival time sequence at the spacecraft that includes energy information. Subsequently, the atmospheric transmittance model is utilized for photon selection, obtaining a sequence of photons that have passed through the atmosphere after absorption. Finally, experimental validation of the proposed algorithm is conducted using Crab pulsar data measured by the Insight-HXMT. The similarity between the simulated data and the measured data is evaluated in terms of profiles, phases, and energy spectra. Simulation experiments demonstrate that the time delay estimation error caused by the simulation algorithm is less than 17.17 us. When the observation tangent point altitude is in the range of 160 km to 180 km, the Pearson correlation coefficient of the profiles between simulated and measured data is 73.74 %. The Pearson residuals of the energy spectra are evenly distributed between −0.2 and 0.2, indicating a good level of similarity between the two.

UNCERTAINTY MODELING AND ANALYSIS OF SPACEBORNE INFRARED HYPERSPECTRAL IMAGES OVER RUGGED LAND SURFACE

Abstract. Infrared hyperspectral imaging is an important technical means to obtain the emissivity spectra and temperature of land surface target, and is an important development direction of spaceborne optical remote sensing in the future. Under the natural rugged land surface condition, the quality of infrared hyperspectral imaging data is affected by terrain condition, atmospheric condition and instrument performance. Therefore, the instrument signal-to-noise ratio and the calibration accuracy could not directly describe the measurement accuracy of the hyperspectral characteristics of target. An uncertainty prediction model of spaceborne infrared hyperspectral images over rugged land surface is established, in this paper. This model could simulate the surface scene, the atmospheric radiation transfer over rugged land surface, and the imaging process of the spaceborne spectrometer. At the same time, the uncertainty transfer from the surface signal to the restored radiance data product could be realized. The generated uncertainty results include the fluctuation of the surface signal, the error of the atmospheric transmission model, the influence of topographic relief, the response characteristics of the imaging spectrometer and the calibration uncertainty. Based on this model, we can also realize the ranking of the uncertainty contribution of the above links, which could help to identify the weak link in the remote sensing measurement chain. The random simulation experiments over a rugged desert scene were conducted to verified the model. It is indicated that more than 99.9% of the stochastic simulation radiance spectra are in the range of the predicted uncertainty.

Vicarious Radiometric Calibration of the Multispectral Imager Onboard SDGSAT-1 over the Dunhuang Calibration Site, China

The multispectral imager (MII), onboard the Sustainable Development Science Satellite 1 (SDGSAT-1), performs detailed terrestrial change detection and coastal monitoring. SDGSAT-1 was launched at 2:19 UTC on 5 November 2021, as the world’s first Earth science satellite to serve the United Nations 2030 Sustainable Development Agenda. A vicarious radiometric calibration experiment was conducted at the Dunhuang calibration site (Gobi Desert, China) on 14 December 2021. In-situ measurements of ground reflectance, aerosol optical depth (AOD), total columnar water vapor, radiosonde data, and diffuse-to-global irradiance (DG) ratio were performed to predict the top-of-atmosphere radiance by the reflectance-, irradiance-, and improved irradiance-based methods using the moderate resolution atmospheric transmission model. The MII calibration coefficients were calculated by dividing the top-of-atmosphere radiance by the average digital number value of the image. The radiometric calibration coefficients calculated by the three calibration methods were reliable (average relative differences: 2.20% (reflectance-based vs. irradiance-based method) and 1.43% (reflectance-based vs. improved irradiance-based method)). The total calibration uncertainties of the reflectance-, irradiance-, and improved irradiance-based methods were 2.77–5.23%, 3.62–5.79%, and 3.50–5.23%, respectively. The extra DG ratio measurements in the latter two methods did not improve the calibration accuracy for AODs ≤ 0.1. The calibrated MII images were verified using Landsat-8 Operational Land Imager (OLI) and Sentinel-2A MultiSpectral Instrument (MSI) images. The retrieved ground reflectances of the MII over different surface types were cross-compared with those of OLI and MSI using the FAST Line-of-sight Atmospheric Analysis of Hypercubes software. The MII retrievals differed by <0.0075 (7.13%) from OLI retrievals and <0.0084 (7.47%) from MSI retrievals for calibration coefficients from the reflectance-based method; <0.0089 (7.57%) from OLI retrievals and <0.0111 (8.65%) from MSI retrievals for the irradiance-based method; and <0.0082 (7.33%) from OLI retrievals and <0.0101 (8.59%) from MSI retrievals for the improved irradiance-based method. Thus, our findings support the application of SDGSAT-1 data.

Infrared linear polarization small target enhancement algorithm in the cloudy background.

With the development of infrared polarization sensors, image enhancement algorithms have been developed. Although using polarization information quickly distinguishes man-made objects from natural backgrounds, cumulus clouds would become detection noise because of their similar characteristics to targets in the sky scene. In this paper, we propose an image enhancement algorithm based on polarization characteristics and the atmospheric transmission model. The algorithm utilizes the principle of polarization imaging and atmospheric transmission theory to enhance the target in the image while suppressing the interference of clutter. We compare with other algorithms through the data we collected. The experimental results show that our algorithm significantly improves the target brightness and reduces clutter at the same time with real-time performance.

Defogging Algorithm Based on Polarization Characteristics and Atmospheric Transmission Model.

We propose a polarized image defogging algorithm according to the sky segmentation results and transmission map optimization. Firstly, we propose a joint sky segmentation method based on scene polarization information, gradient information and light intensity information. This method can effectively segment the sky region and accurately estimate the global parameters such as atmospheric polarization degree and atmospheric light intensity at infinite distance. Then, the Gaussian filter is used to solve the light intensity map of the target, and the information of the polarization degree of the target is solved. Finally, based on the segmented sky region, a three-step transmission optimization method is proposed, which can effectively suppress the halo effect in the reconstructed image of large area sky region. Experimental results shows that defogging has a big improvement in the average gradient of the image and the grayscale standard deviation. Therefore, the proposed algorithm provides strong defogging and can improve the optical imaging quality in foggy scenes by restoring fog-free images.

HST/WFC3 transmission spectroscopy of the cold rocky planet TRAPPIST-1h

Aims. TRAPPIST-1 is a nearby ultra-cool dwarf star transited by seven rocky planets. We observed three transits of its outermost planet, TRAPPIST-1h, using the G141 grism of the Wide Field Camera 3 instrument aboard the Hubble Space Telescope to place constraints on its potentially cold atmosphere. Methods. In order to deal with the effect of stellar contamination, we model TRAPPIST-1 active regions as portions of a cooler and a hotter photosphere, and generate multi-temperature models that we compare to the out-of-transit spectrum of the star. Using the inferred spot parameters, we produce corrected transmission spectra for planet h under five transit configurations and compare these data to planetary atmospheric transmission models using the forward model CHIMERA. Results. Our analysis reveals that TRAPPIST-1h is unlikely to host an aerosol-free H/He-dominated atmosphere. While the current data precision limits the constraints we can put on the planetary atmosphere, we find that the likeliest scenario is that of a flat, featureless transmission spectrum in the WFC3/G141 bandpass due to a high mean molecular weight atmosphere (≥1000 × solar), no atmosphere, or an opaque aerosol layer, all in absence of stellar contamination. This work outlines the limitations of modeling active photospheric regions with theoretical stellar spectra, and those brought by our lack of knowledge of the photospheric structure of ultracool dwarf stars. Further characterization of the planetary atmosphere of TRAPPIST-1h would require higher precision measurements over wider wavelengths, which will be possible with the James Webb Space Telescope.

Research on a Measurement Method for Middle-Infrared Radiation Characteristics of Aircraft

Aiming at the problem wherein temperature inversion accuracy is unstable due to the major differences in atmospheric transmittance under various observation paths, a method for measuring radiation characteristics of an aircraft engine’s hot parts and skin using a cooled middle-wave infrared camera is proposed. Based on the analysis of the aircraft’s infrared radiation characteristics, the atmospheric transmission model of any observation path was revised, the absolute radiation correction model was established, and the temperature inversion equation was calculated. Then, we used the quasi-Newton method to calculate the skin temperature and discussed uncertainty sources. After the theoretical study, an outfield test was carried out. A middle-wave infrared camera with a wavelength of 3.7–4.8 μm was applied to the actual experimental observation of the turbofan civil aviation aircraft. The ground observation distance was 15 km, and the flying height was 3 km. When implementing temperature inversion with the method presented in this paper, the surface temperature of the aircraft engine hot parts was 381 K, the correction uncertainty was ±10 K, the surface temperature of the skin was 296 K, and the correction uncertainty was ±6 K. As the experiment showed, the method in this paper can effectively implement infrared target temperature inversion and provide a reference for the quantification of infrared data.

Polarization-Based Haze Removal Using Self-Supervised Network

Atmospheric scattering caused by suspended particles in the air severely degrades the scene radiance. This paper proposes a method to remove haze by using a neural network that combines scene polarization information. The neural network is self-supervised and online globally optimization can be achieved by using the atmospheric transmission model and gradient descent. Therefore, the proposed method does not require any haze-free image as the constraint for neural network training. The proposed approach is far superior to supervised algorithms in the performance of dehazing and is highly robust to the scene. It is proved that this method can significantly improve the contrast of the original image, and the detailed information of the scene can be effectively enhanced.

Retrieval of Sea Surface Temperature From HY-1B COCTS

The Chinese Ocean Color and Temperature Scanner (COCTS) on board HY-1 series satellites has two thermal infrared channels with the spectrum range of 10.30-11.40 μm and 11.40-12.50 μm for sea surface temperature (SST) observations. To reprocess the Haiyang-1B (HY-1B) COCTS SST, the Bayesian cloud detection and optimal estimation (OE) SST retrieval were applied to COCTS data in this study. The Bayesian cloud detection algorithm that has been developed is based on the Bayes’ theorem and uses simulation of COCTS observations. The MODerate resolution atmospheric TRANsmission (MODTRAN) model was used for simulation of COCTS brightness temperatures. SSTs were retrieved from COCTS by OE from 2009 to 2011 in the northwest Pacific. Comparison of COCTS OE SST with in situ SST showed that the COCTS SSTs are cooler than buoy measurements by –0.23 °C on average, and the standard deviation (SD) of differences was 0.51 °C. A large component of the mean difference is attributable to the cool skin effect at the ocean surface (typically –0.15 to –0.2 °C), the remainder being attributable to simulation and calibration biases. The mean difference of COCTS OE SST with matched skin temperatures from the Advanced Along Track Scanning Radiometer (AATSR) is closer to zero, being –0.09 °C, with a SD of 0.49 °C. These validation results of COCTS OE SST demonstrate that Bayesian cloud detection and OE SST retrieval algorithm work well for improving COCTS SST accuracy, and show the potential of these methods to help develop SST products for operational HY-1 satellites, HY-1C and HY-1D.

Parameter Simulation and Design of an Airborne Hyperspectral Imaging LiDAR System

With continuous technological development, the future development trend of LiDAR in the field of remote sensing and mapping is to obtain the elevation and spectral information of ground targets simultaneously. Airborne hyperspectral imaging LiDAR inherits the advantages of active and passive remote sensing detection. This paper presents a simulation method to determine the design parameters of an airborne hyperspectral imaging LiDAR system. In accordance with the hyperspectral imaging LiDAR equation and optical design principles, the atmospheric transmission model and the reflectance spectrum of specific ground targets are utilized. The design parameters and laser emission spectrum of the hyperspectral LiDAR system are considered, and the signal-to-noise ratio of the system is obtained through simulation. Without considering the effect of detector gain and electronic amplification on the signal-to-noise ratio, three optical fibers are coupled into a detection channel, and the power spectral density emitted by the supercontinuum laser is simulated by assuming that the signal-to-noise ratio is equal to 1. The power spectral density emitted by the laser must not be less than 15 mW/nm in the shortwave direction. During the simulation process, the design parameters of the hyperspectral LiDAR system are preliminarily demonstrated, and the feasibility of the hyperspectral imaging LiDAR system design is theoretically guaranteed in combination with the design requirements of the supercontinuum laser. The spectral resolution of a single optical fiber of the hyperspectral LiDAR system is set to 2.5 nm. In the actual prototype system, multiple optical fibers can be coupled into a detection channel in accordance with application needs to further improve the signal-to-noise ratio of hyperspectral LiDAR system detection.

Retraction Note: Mountain air pollution evaluation and tourism brand building based on remote sensing image processing

In recent 20 years, China has made a lot of efforts and achieved some results in air governance. However, it is not ideal from the result. Some areas of pollution also affect the daily life and physical and mental health of the people, which is an important environmental problem that China needs to solve. This paper presents a double star cooperative AOT inversion algorithm with complex background in urban area. Aiming at the difficulty of AOT inversion on urban area highlighted surface, the paper uses the double satellite remote sensing data and the atmospheric radiation transmission model to realize the inverse reflection of AOT parameters in urban area by using satellite remote sensing image processing. With the development of society, the progress of the times, and the rapid development of urbanization, the environmental pollution problems in some areas also follow. However, this problem is more difficult, because it involves many factors. At present, there is no comprehensive evaluation model to comprehensively evaluate various pollution situations. In this paper, we have carried out a detailed study on the typical model of mountain air pollution and the evaluation method of mountain air pollution. This work provides a practical solution for simulating the air pollution in mountain areas and analyzing environmental data. With the development of economy, people pay more attention to tourism, and the construction of tourism brand has become a trend. Higher and better service has become a new pursuit of consumers in the process of tourism, which makes more rural people get rid of poverty, and further improves the attention and protection of ecological environment. Therefore, this paper studies the assessment of mountain air pollution and the construction of tourism brand by using remote sensing image processing technology, which promotes pollution prevention and tourism industry development.

Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model

This work gives a first insight into the potential of the Weather Research and Forecasting (WRF) model to provide high-resolution vertical profiles for land surface temperature (LST) retrieval from thermal infrared (TIR) remote sensing. WRF numerical simulations were conducted to downscale NCEP Climate Forecast System Version 2 (CFSv2) reanalysis profiles, using two nested grids with horizontal resolutions of 12 km (G12) and 3 km (G03). We investigated the utility of these profiles for the atmospheric correction of TIR data and LST estimation, using the moderate resolution atmospheric transmission (MODTRAN) model and the Landsat 8 TIRS10 band. The accuracy evaluation was performed using 27 clear-sky cases over a radiosonde station in Southern Brazil. We included in the comparative analysis NASA’s Atmospheric Correction Parameter Calculator (ACPC) web-tool and profiles obtained directly from the NCEP CFSv2 reanalysis. The atmospheric parameters from ACPC, followed by those from CFSv2, were in better agreement with parameters calculated using in situ radiosondes. When applied into the radiative transfer equation (RTE) to retrieve LST, the best results (RMSE) were, in descending order: CFSv2 (0.55 K), ACPC (0.56 K), WRF G12 (0.79 K), and WRF G03 (0.82 K). Our findings suggest that there is no special need to increase the horizontal resolution of reanalysis profiles aiming at RTE-based LST retrieval. However, the WRF results were still satisfactory and promising, encouraging further assessments. We endorse the use of the well-known ACPC and recommend the NCEP CFSv2 profiles for TIR atmospheric correction and LST single-channel retrieval.

RETRACTED ARTICLE: Mountain air pollution evaluation and tourism brand building based on remote sensing image processing

In recent 20 years, China has made a lot of efforts and achieved some results in air governance. However, it is not ideal from the result. Some areas of pollution also affect the daily life and physical and mental health of the people, which is an important environmental problem that China needs to solve. This paper presents a double star cooperative AOT inversion algorithm with complex background in urban area. Aiming at the difficulty of AOT inversion on urban area highlighted surface, the paper uses the double satellite remote sensing data and the atmospheric radiation transmission model to realize the inverse reflection of AOT parameters in urban area by using satellite remote sensing image processing. With the development of society, the progress of the times, and the rapid development of urbanization, the environmental pollution problems in some areas also follow. However, this problem is more difficult, because it involves many factors. At present, there is no comprehensive evaluation model to comprehensively evaluate various pollution situations. In this paper, we have carried out a detailed study on the typical model of mountain air pollution and the evaluation method of mountain air pollution. This work provides a practical solution for simulating the air pollution in mountain areas and analyzing environmental data. With the development of economy, people pay more attention to tourism, and the construction of tourism brand has become a trend. Higher and better service has become a new pursuit of consumers in the process of tourism, which makes more rural people get rid of poverty, and further improves the attention and protection of ecological environment. Therefore, this paper studies the assessment of mountain air pollution and the construction of tourism brand by using remote sensing image processing technology, which promotes pollution prevention and tourism industry development.

Intelligent Recognition Method of Low-Altitude Squint Optical Ship Target Fused with Simulation Samples

To address the problem of intelligent recognition of optical ship targets under low-altitude squint detection, we propose an intelligent recognition method based on simulation samples. This method comprehensively considers geometric and spectral characteristics of ship targets and ocean background and performs full link modeling combined with the squint detection atmospheric transmission model. It also generates and expands squint multi-angle imaging simulation samples of ship targets in the visible light band using the expanded sample type to perform feature analysis and modification on SqueezeNet. Shallow and deeper features are combined to improve the accuracy of feature recognition. The experimental results demonstrate that using simulation samples to expand the training set can improve the performance of the traditional k-nearest neighbors algorithm and modified SqueezeNet. For the classification of specific ship target types, a mixed-scene dataset expanded with simulation samples was used for training. The classification accuracy of the modified SqueezeNet was 91.85%. These results verify the effectiveness of the proposed method.

Retrieving Land Surface Temperature From Chinese FY-3D MERSI-2 Data Using an Operational Split Window Algorithm

Medium resolution spectral imager II (MERSI-2) is a payload for the Chinese meteorological satellite Feng Yun 3 (FY-3). China's satellite remote sensing observation capabilities such as climate change research can be improved during MERSI-2's operation in orbit, and the sensor is the world's first imaging instrument that can obtain a global infrared split-window data with a spatial resolution of 250 m. We developed an operational spilt-window (SW) algorithm to retrieve land surface temperature (LST) accurately from the MERSI-2 data. The SW algorithm coefficients were derived from a simulation dataset that was established with the Moderate spectral resolution atmospheric Transmittance model version 5.2 and the thermodynamic initial guess retrieval dataset. In the practical retrieval, the precise algorithm coefficients were determined by view zenith angle and atmospheric water vapor content (WVC), the atmospheric WVC were obtained from the ERA5 dataset, and the land surface emissivity was dynamically estimated using the advanced spaceborne thermal emission and reflection radiometer global emissivity dataset, considering the fractional of vegetation cover and snow cover. The retrieved LST compared with in situ LST, which was highly consistent with the in situ LST and that the root-mean-square error of the two is within 3 K. The retrieved LST was compared with the MYD11_L2 and MYD21_L2 LST products, and the results indicated that MERSI-2 LST was more consistent with the MYD21 LST. The operational SW algorithm for FY-3D MERSI-2 developed in this study could retrieve LST accurately and has a wide range of popularization and application values.

Vicarious Calibration for the AHSI Instrument of Gaofen-5 With Reference to the CRCS Dunhuang Test Site

The visible-shortwave infrared Advanced Hyperspectral Imager (AHSI) is a payload onboard the Gaofen-5 satellite, which is China’s first hyperspectral satellite and is part of the Chinese High-Resolution Earth Observation System. As a supplement to the onboard radiometric calibration of the AHSI instrument, vicarious calibration is also required, which is independent of the instrument-based calibration. In this article, a reflectance-based vicarious calibration approach is presented, which takes surface reflectance data, aerosol data, and atmospheric water vapor data into account. The Dunhuang test site, which is one of the China Radiometric Calibration Sites (CRCS) for the vicarious calibration of spaceborne sensors, possesses stable, uniform, and measurable surface objects, so it was chosen as the radiation source to replace the laboratory and onboard calibrators. A Spectra Vista Corporation (SVC) spectral radiometer and a CE318 sun photometer were utilized for the measurement of the surface reflectance and the condition of the aerosol, respectively. The radiance at the entrance pupil at the top of atmosphere was then obtained through the MODerate resolution atmospheric TRANsmission (MODTRAN) atmospheric transmission model. The surface reflectance was obtained using the Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) atmospheric model for validation. The results show that, with regard to the calibration coefficients, the calibrated AHSI instrument presents a stable radiometric performance among different land-cover types. The ratios on all the bands are between 0.8 and 1.2 and are consistent with the reflectance data from the Dunhuang test site. The <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${R} ^{{2}}$ </tex-math></inline-formula> values are all greater than 0.95 and the spectral angle is all less than 2°. The standard deviations of the ratios are less than 3% for each chosen band, which proves that the calibrated data have a high consistency with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> measurements. When compared with Landsat 8 and Sentinel-2, the mean errors of the surface reflectance are all under 0.06, which further demonstrates that the calibrated reflectance has a high accuracy.

Detection of Fe I and Fe II in the atmosphere of MASCARA-2b using a cross-correlation method

Ultra-hot Jupiters are gas giants planets whose dayside temperature is greater than 2200 K as a consequence of the strong irradiation received from the host star. These kinds of objects are perfect laboratories to study the chemistry of exoplanetary upper atmospheres via transmission spectroscopy. Exo-atmospheric absorption features are buried in the noise of the in-transit residual spectra. However we can retrieve information of hundreds of atmospheric absorption lines by performing a cross-correlation with an atmospheric transmission model, which allows us to greatly increase the exo-atmospheric signal. The Rossiter–McLaughlin effect and centre-to-limb variation contribute strongly at the high spectral resolution of our data. We present the first detection of Fe I and confirmation of absorption features of Fe II in the atmosphere of the ultra-hot Jupiter MASCARA-2b/KELT-20b, by using three transit observations with HARPS-N. After combining all transit observations we find a high cross-correlation signal of Fe I and Fe II with signal-to-noise ratios of 10.5 ± 0.4 and 8.6 ± 0.5, respectively. The peak absorption for both species appear to be blue-shifted with velocities of − 6.3 ± 0.8 km s−1 for Fe I and − 2.8 ± 0.8 km s−1 for Fe II, suggesting the presence of winds from the day- to night-side of the atmosphere of the planet. These results confirm previous studies of this planet and add a new atomic species (Fe I) to the long list of detected species in the atmosphere of MASCARA-2b, making it, together with KELT-9b, the most feature-rich ultra-hot Jupiter to date.

Research on Quantitative Remote Sensing Monitoring Algorithm of Air Pollution Based on Artificial Intelligence

When the current algorithm is used for quantitative remote sensing monitoring of air pollution, it takes a long time to monitor the air pollution data, and the obtained range coefficient is small. The error between the monitoring result and the actual result is large, and the monitoring efficiency is low, the monitoring range is small, and the monitoring accuracy rate is low. An artificial intelligence-based quantitative monitoring algorithm for air pollution is proposed. The basic theory of atmospheric radiation transmission is analyzed by atmospheric radiation transfer equation, Beer–Bouguer–Lambert law, parallel plane atmospheric radiation theory, atmospheric radiation transmission model, and electromagnetic radiation transmission model. Quantitative remote sensing monitoring of air pollution provides relevant information. The simultaneous equations are constructed on the basis of multiband satellite remote sensing data through pixel information, and the aerosol turbidity of the atmosphere is calculated by the equation decomposition of the pixel information. The quantitative remote sensing monitoring of air pollution is realized according to the calculated aerosol turbidity. The experimental results show that the proposed algorithm has high monitoring efficiency, wide monitoring range, and high monitoring accuracy.

DESHIMA on ASTE: On-Sky Responsivity Calibration of the Integrated Superconducting Spectrometer

We are developing an ultra-wideband spectroscopic instrument, DESHIMA (DEep Spectroscopic HIgh-redshift MApper), based on the technologies of an on-chip filter-bank and Microwave Kinetic Inductance Detector (MKID) to investigate dusty star-burst galaxies in the distant universe at millimeter and submillimeter wavelength. An on-site experiment of DESHIMA was performed using the ASTE 10-m telescope. We established a responsivity model that converts frequency responses of the MKIDs to line-of-sight brightness temperature. We estimated two parameters of the responsivity model using a set of skydip data taken under various precipitable water vapor (PWV, 0.4-3.0 mm) conditions for each MKID. The line-of-sight brightness temperature of sky is estimated using an atmospheric transmission model and the PWVs. As a result, we obtain an average temperature calibration uncertainty of $1\sigma=4$%, which is smaller than other photometric biases. In addition, the average forward efficiency of 0.88 in our responsivity model is consistent with the value expected from the geometrical support structure of the telescope. We also estimate line-of-sight PWVs of each skydip observation using the frequency response of MKIDs, and confirm the consistency with PWVs reported by the Atacama Large Millimeter/submillimeter Array.