The high-resolution multi-mode imaging satellite called GFDM (Gao Fen Duo Mo) has been successful launched in July 3 of 2020, which was integrated with 1 panchromatic and 8 multispectral bands with the spatial resolution of 0.42 m and 1.6 m, respectively. The Synchronization Monitoring Atmospheric Corrector (SMAC) instrument was also on board GFDM satellite, aiming for offering time synchronized and field of view overlapped atmospheric measurements to improve the atmospheric correction of the GFDM main sensor image. As the first civilian atmospheric corrector onboard high spatial resolution satellite with polarization detection, SMAC has 8 wavelength bands from visible to short-wave infrared with the spatial resolution about 6.7 km. In order take full advantage of the multispectral measurements of SMAC, we investigate to retrieve the aerosol optical depth (AOD) by using the intensity measurements in this study. To decouple the surface-atmosphere contribution from SAMC measurements, the corresponding surface reflectance over land is derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) surface bi-directional reflectance climatology. Based on the principal component analysis method and the dataset from spectral libraries, the surface reflectance ratios are further obtained by spectral conversion with the spectral response function from MODIS to SAMC for aerosol retrieval. With the aerosol look-up table (LUT) established by the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiation transmission model, the multispectral inversions are carried out and the AODs are retrieved. In addition, the AOD data from Aerosol Robotic Network are used to validate the retrieved results from SAMC by the spatial-temporal matching, the statistical parameters including the root mean square error (RMSE) and the correlation coefficient (R) are employed together. By this means, the retrieved AODs from the intensity measurements of SAMC are preliminary investigated.
Data preprocessing of the Polarized Scanning Atmospheric Corrector (PSAC) onboard HuanjingJianzai-2(HJ-2)A/B satellites is a key step for further applications. Based on the principles and characteristics of PSAC sensor, this paper elaborates on the methods and procedures of its data preprocessing including parameters quality supervision, data precorrection, calibration implementation and geolocation, etc. The results show that the data preprocessing from the original data to the L1 product is accurate and effective after preliminary analysis and evaluation, which can be used for subsequent atmospheric parameters retrieval and atmospheric correction applications.
Different from the principal component analysis (PCA), non-negative matrix factorization (NMF) can provide more direct interpretation owning to the non-subtractive combinations of non-negative basis vectors, and many practical problems also require non-negative basis vectors rather than the orthogonal vectors with alternating positive and negative. In this study, we develop a hyperspectral surface reflectance reconstruction method based on NMF and multispectral results in several wavelength bands. In order to test our spectral reconstruction method, the spectral datasets of typical surface types are extracted from the spectral library of John Hopkins University (JHU), which include the soil, vegetation, manmade materials, sedimentary fine and coarse rock. The prior surface reflectance or emissivity results are selected from only four wavelength bands (2.13, 3.75, 3.96, 4.05 μm) from shortwave infrared to Mid-infrared, which can be easily obtained from the surface product of Moderate-resolution Imaging Spectroradiometer (MODIS). Based on the JHU spectral dataset and NMF, the hyperspectral surface reflectance in the spectral range of 2-5μm with the step of 25 nm can be reconstructed consistently. In addition, the hyperspectral reconstruction effects by NMF are quantitatively investigated, in which the root mean square error and the mean absolute error is about 0.016 and 0.01, respectively.
A series of studies of hyperspectral remote sensing had been carried out to develop a hyperspectral remote sensing technique for aerosol retrieval in the previous works, including the theoretical framework, information content analysis and application to the real data, in which a hyperspectral inversion algorithm was developed to simultaneously retrieved the aerosol and surface properties, and the surface reflectance spectra were decomposed into different principal components, thus only several weighting coefficients of principal components (PCs) were needed to be retrieved. In this study, based on the optimal estimation (OE) framework, we extend the OE-based hyperspectral inversion algorithm to multispectral remote sensing, and the synthetic multispectral intensities of Polarized Scanning Atmospheric Corrector (PSAC) centered in 410, 443, 555, 670, 865, 1610 and 2250 nm are used to test the inversion framework. Principal component analysis (PCA) has been conducted for the spectral dataset of 4 typical surface types with 7 channels of PSAC, in which the PC’s contribution and spectra, the spectral reconstruction results and constraints of PC’s weighting coeffects are discussed. Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) is used as the forward model, and 1% Gaussian distribution errors has been added to the simulated radiance at the top of the atmosphere for multispectral inversion test. The iterative process of multispectral normalized intensities and the reconstructed surface reflectance during the OE iteration are investigated, and the normalized cost function values are well convergent. This study can provide key support to the development of OE-based inversion algorithms for multispectral remote sensing
The bidirectional reflectance distribution function (BRDF) is a physical quantity that represents the change of surface reflection with the Sun and the direction of observation, which is of great significance to the study of surface anisotropic reflection characteristics. In this paper, based on MODIS (Moderate Resolution Imaging Spectroradiometer) BRDF model parameters products (MCD43A1), we utilize the Ross-Li model to simulate the surface reflectance of the four land surface types in North China: vegetation, bare soil, cropland, and urban, and comparatively analyze the seasonal variation of their surface anisotropic reflection characteristics. Therefore, this study can provide reliable scientific basis for improving land surface process model, promoting surface-atmosphere interaction and global climate change research. The results show that: (1) The backscattering of the four land surface types is greater than the forward scattering, and the larger the scattering angle is, the larger the bidirectional reflectance will be. The distribution trend of bidirectional reflectance of different surface types is quite different in different bands and seasons. (2) The bidirectional reflectance of the four land surface types varies with the wavelength roughly the same in spring, summer, and autumn. In winter, due to snow covering the ground, the bidirectional reflectance of vegetation, cropland, and urban is higher in visible and near-infrared bands. Due to the fixed simulation angle, the distribution trend of the bidirectional reflectance of bare soil in four seasons is multipeak in the multi-band range.
Environment-2 (HJ-2) A/B satellites will be launched in 2020, which are expected to work as the successors of Environment-1 (HJ-1) satellites in Chinese Environment and Disaster Monitoring and Prediction Satellite Constellation. A new space-borne instrument called Polarized Scanning Atmospheric Corrector (PSAC) also will be onboard HJ-2 satellites, aiming to provide the atmospheric properties for synchronous atmospheric correction of the main sensors, such as the charge-coupled device cameras onboard the same satellite. PSAC is a cross-track scanning polarimeter with polarized channels from near-ultraviolet to shortwave infrared, centered in 410, 443, 555, 670, 865, 910, 1380, 1610 and 2250 nm. In order to test the performance of inversion algorithms and software modules, synthetic data simulated by the vector radiative transfer is indispensable. In this paper, the regional simulation of PSAC multispectral measurements are preliminarily studied, and the Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) has been used as the forward model. For the observation geometries, the viewing zenith angles are calculated by the linear interpolation over the cross-track scanning angle range from west to east, while the viewing azimuth angle are simulated by following the azimuth angle distribution of other corresponding satellite. By taking the vegetated surface type as an example, the multispectral Lambertian surface reflectance and wavelength-independent BPDF model are used in the forward simulation, and different aerosol optical depth with fine-dominated and coarse-dominated aerosols are considered. In this way, the multispectral measurements can be obtained by the forward simulations over a regional grid with the predefined latitude and longitude, and further analysis are carried out based on the synthetic data. Thus, this study can provide key support to the testbed of inversion algorithms and software modules before and after the satellite launch.
Aerosol fine mode fraction (FMF) is an important parameter in associating aerosol loading with fine particle matter (PM2.5) pollution in the atmosphere. Previous studies have retrieved FMF from scalar measurements (centered at 490, 550, 670, 870, 1610 nm) from Synchronization Monitoring Atmospheric Corrector (SMAC) sensor. As a polarimetric instrument, SMAC also provides degree of linear polarization (DOLP) measurements (centered at 490, 670, 870, 1610 nm). In this paper, we try to evaluate the capabilities of both scalar and polarimetric measurements for aerosol retrieval. For the purpose, the analyses of information content and errors propagation are performed based on synthesized SMAC data. The Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) is adopted as the forward model, and the ground-based skylight measurements on the solar principal plane are simulated. Additionally, the analytic formula used to calculate Jacobians of DOLP with regard to FMF is verified by the finite difference method. Secondly, based on the information content analysis theory, the degree of freedom for signal (DFS) of FMF contained in polarimetric observations are calculated. Meanwhile, the a posteriori error of FMF are also calculated for the error propagation analysis. We found the mean DFS of FMF is greater than 0.8, which indicates that the FMF can be well retrieved from both intensity and polarization measurements. Compared to scalar measurements, the DOLP measurements can provide extra 0.14 and 0.08 DFS for fine- and coarse-dominated aerosols, respectively. As for the inversion errors, the uncertainties of both AOD and FMF decrease apparently. The a posteriori error of AOD decreases from 23.33% to 11.6%, and the a posteriori error of FMF decreases from 33.8% to 26.5%.
For the satellite remote sensing of aerosols in Ultraviolet (UV) wavelength bands, the atmospheric widow in UVA spectral bands from 315nm to 400nm are usually used. To derive the aerosols and surface reflectance from satellite UV measurements, a suitable radiative transfer model is indispensable for designed retrieval algorithms. In this study, we focus on the sensitivity study of polarization measurements in the UV wavelength bands, and Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) is used as the forward model for the simulation of the synthetic data. The hyperspectral surface reflectance of green vegetation and man-made materialsin UV have been extracted from the spectral library of John Hopkins University (JHU), and the polarized surface reflectance is also integrated in forward simulations. Both the fine-mode and coarse mode dominated aerosols are selected to investigate the influence on the measurements at the top of the atmosphere (TOA). For the separate contributions of Rayleigh scattering, aerosols scattering/absorption and surface-atmosphere coupled results, different input options are set in the UNL-VRTM. With the combination of gas absorption in forward simulation, the Rayleigh contribution, atmospheric path radiance and coupled contribution with surface are obtained, and the corresponding sensitivities are investigated and discussed. The results in this study can provide important support for the design of retrieval algorithms in UV.
Based on the optimal estimation (OE) theory, an inversion framework for aerosol retrieval from multiviewing polarimetric satellite measurements, is presented. The retrieved parameters include the wavelength-independent volume concentration and spectral aerosol optical depth (AOD). An OE-iteration approach is proposed to implement the framework. Polarization data from the polarization and directionality of the Earth’s reflectance sensor over the Chinese Beijing–Tianjin–Hebei region are selected to test the proposed algorithm. The validation against aerosol robotic network products produces high correlation coefficients (R) of 0.85, 0.9, and 0.86 for the fine-mode volume concentration, fine-mode AOD, and total AOD at 500 nm, respectively. These results indicate that the OE retrieval framework is practical and useful in the quantitative retrieval of AOD and fine-mode volume concentration from the multiangle polarization data.
Normalized Differential Vegetation Index (NDVI), usually calculated by surface reflectance at red and near-infrared bands (NDVI_Surf), which is an essential index in remote sensing. NDVI_Surf is generally used to discriminate different surface cover types and adopted in many surface models as a vital adjustable parameter to estimate the surface reflectance in remote sensing aerosol retrieval. However, NDVI_Surf is challenging to obtained directly and usually calculated by the red and near-infrared reflectance at the top of atmosphere (NDVI_TOA). NDVI_TOA is very susceptible to the atmosphere with different angles. If NDVI_Surf is replaced by the NDVI_TOA, it will cause an error of surface reflectance estimation and then make the wrong aerosol retrieval. In this study, Second Simulation of a Satellite Signal in the Solar Spectrum, Vector version (6SV) radiative transfer code was used to analyze the effects of NDVI_TOA on a surface Bidirectional Polarization Distribution Function (BPDF) model under different atmosphere and multi-angles conditions. The results display that the NDVI_TOA decreases with the rise of AOD. Within scattering angle (SA) of 60° to 115°, the influences of NDVI_TOA on BPDF are great and increases with the AOD reduces. Within the SA between 115° to 180°, the effects of NDVI_TOA on BPDF are small and remain unchanged with the AOD decreases. The simulation and analysis results have a great significance for polarized aerosol retrieval.
Environment-2 (HJ-2) satellites will be launched after 2019, which are designed as the successor of Environment-1 (HJ- 1) satellites in Chinese Environment and Disaster Monitoring and Prediction Satellite Constellation. Different from HJ-1 satellites, a new multispectral single-viewing polarimetric instrument called Polarized Scanning Atmospheric Corrector (PSAC) will be onboard on HJ-2 satellites, and further provide the aerosol properties for synchronous atmospheric correction of the main sensors, such as the multispectral charge-coupled device (CCD) cameras onboard the same satellite. In this way, the multispectral surface reflectance could be further obtained from the remote sensing measurements of CCD cameras by the atmospheric correction with the retrieved aerosol properties from PSAC. In this paper, based on the optimal estimation (OE) theory and information content analysis method, we have a preliminary study on the propagation errors from the retrieved aerosol properties to multispectral surface reflectance in the process of synchronous atmospheric correction. The priori information and errors for the analysis are assumed based on the measurement noise of CCD cameras and a priori error of retrieved aerosol optical depth (AOD), as well as typical multispectral reflectance from USGS and ASTER spectral library. For the simulation of synthetic measurements of CCD cameras, Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) has been used as the forward model. By this means, the posterior errors of multispectral surface reflectance are calculated, and the errors propagations can be evaluated theoretically, which can further provide key support for the study of synchronous atmospheric correction in HJ-2 satellites.
To meet the demanding of spectral reconstruction in the visible and near-infrared wavelength, the spectral reconstruction method for typical surface types is discussed based on the USGS/ASTER spectral library and principal component analysis (PCA). A new spectral reconstructed model is proposed by the information of several typical bands instead of all of the wavelength bands, and a linear combination spectral reconstruction model is also discussed. By selecting 4 typical spectral datasets including green vegetation, bare soil, rangeland and concrete in the spectral range of 400−900 nm, the PCA results show that 6 principal components could characterized the spectral dataset, and the relative reconstructed errors are smaller than 2%. If only 6−7 selected typical bands are employed to spectral reconstruction for all the surface reflectance in 400−900 nm, except that the reconstructed error of green vegetation is about 3.3%, the relative errors of other 3 datasets are all smaller than 1.6%. The correlation coefficients of those 4 datasets are all larger than 0.99, which can effectively satisfy the needs of spectral reconstruction. In addition, based on the spectral library and the linear combination model of 4 common used bands of satellite remote sensing such as 490, 555, 670 and 865 nm, the reconstructed errors are smaller than 8.5% in high reflectance region and smaller than 1.5% in low reflectance region respectively, which basically meet the needs of spectral reconstruction. This study can provide a reference value for the surface reflectance processing and spectral reconstruction in satellite remote sensing research.
The remote sensing image is usually polluted by atmosphere components especially like aerosol particles. For the quantitative remote sensing applications, the radiative transfer model based atmospheric correction is used to get the reflectance with decoupling the atmosphere and surface by consuming a long computational time. The parallel computing is a solution method for the temporal acceleration. The parallel strategy which uses multi-CPU to work simultaneously is designed to do atmospheric correction for a multispectral remote sensing image. The parallel framework’s flow and the main parallel body of atmospheric correction are described. Then, the multispectral remote sensing image of the Chinese Gaofen-2 satellite is used to test the acceleration efficiency. When the CPU number is increasing from 1 to 8, the computational speed is also increasing. The biggest acceleration rate is 6.5. Under the 8 CPU working mode, the whole image atmospheric correction costs 4 minutes.
Because of the special geographical location and meteorology conditions, Beijing is a dust-prone city for a long history especially in the spring season. But these years, the most common air pollution in Beijing is haze which is mainly composed of fine particles. The dust is transported from north (Inner Mongolia province and Mongolia country), and the haze is transported from south (Hebei, Shandong and other provinces). Generally, the severities of dust and haze are opposite for the different weather causes. On March 28, 2015, the spring coming earlier for the relatively high temperature, a severe dust weather process happened suddenly in the long-term hazy days. In this dust process, the PM10 concentration was more than 1000μg/m3; the visibility was no more than 3km; and the aerosol optical depth was more than 2, which reached a severe pollution level. We used ground-based remote sensing instruments to observing the heavy dust episode. The data of two conditions were analyzed optical and microphysical parameters contrastively including the Aerosol Optical Depth, Single Scattering Albedo, Size distribution, Complex refractive index, Fine-mode Fraction. The vertical distribution characteristics were also analyzed by the lidar measurements. The results show that big differences between the dust and haze aerosol properties. But we found that fine mode particle pollution was assignable in the dust pollution weather in 2015 spring in Beijing. Our preliminary inference is that this dust episode was not only caused by transportation, but also contributed by the local raise dust.
As an active remote sensing technique, ground-based lidar can detect the backscattered signals of atmospheric cloud and aerosol layers. The measured signals can be used to obtain the vertical profile information of aerosol extinction coefficients. The atmospheric aerosol is measured in Beijing during Asia-Pacific Economic Cooperation (APEC) conference in early November 2014. Fernald method is chosen as the inversion method, and a comparison is made by using Klett’s method. Using the aerosol optical depth(AOD) measured by sunphotometer as a constraint data. The results are used for the analysis of the vertical distribution of aerosol extinction coefficients, three periods are considered, which including several days before, during and after the APEC conference. From the retrieved results of lidar measurement, it was found that the maximum value of extinction coefficients at vertical height in the beginning period reached beyond 2, but it decreased to the range of 0.05 during the conference. Then it gradually increased to more than 2 after the APEC conference. The results show that vertical distribution range of aerosol extinction coefficients decreased to 1km with increasing of AOD. The retrieved AOD results illustrate the extinction characteristics of aerosol,and it relates with the concentration distribution of atmospheric particles. According to the relationship between extinction coefficients and atmospheric visibility, the weather condition can be analyzed.
The reflected Solar radiance at top of atmosphere (TOA) are, to some degree, sensitive to the vertical distribution of absorbing aerosols, especially at short wavelengths (i.e. blue and UV bands). If properly exploited, it may enable the extraction of basic information on aerosol vertical distribution. In recent years, rapid development of the advanced spectral multi-angle polarimetric satellite observation technology and aerosol inversion algorithm makes the extraction of more aerosol information possible. In this study, we perform a sensitivity analysis of the reflection function at TOA to the aerosol layer height, to explore the potential for aerosol height retrievals by using multi-angle total and polarized reflectance passive observations at short wavelength. Employing a vector doubling-adding method radiative transfer code RT3, a series of numerical experiments were conducted considering different aerosol model, optical depth (AOD), single-scattering albedo (SSA), and scale height (H), also the wavelength, solar-viewing geometry, etc. The sensitivity of both intensity and polarization signals to the aerosol layer height as well as the interacted impactions with SSA and AOD are analyzed. It’s found that the sensitivity of the atmospheric reflection function to aerosol scale height increase with aerosol loading (i.e. AOD) and aerosol absorption (i.e. SSA), and decrease with wavelength. The scalar reflectance is sensitive to aerosol absorption while the polarized reflectance is more influenced by the altitude. Then the aerosol H and SSA may be derived simultaneously assuming that the total and polarized radiances in UV bands deconvolve the relative influences of height and absorption. Aerosol layer height, Atmospheric reflection function, Sensitivity, Ultraviolet (UV) band.
For the along-track scanning mode, the same place along the ground track could be detected by the Advanced Multi-angular Polarized Radiometer (AMPR) with several different scanning angles from -55 to 55 degree, which provides a possible means to get the multi-angular detection for some nearby pixels. However, due to the ground sample spacing and spatial footprint of the detection, the different sizes of footprints cannot guarantee the spatial matching of some partly overlap pixels, which turn into a bottleneck for the effective use of the multi-angular detected information of AMPR to study the aerosol and surface polarized properties. Based on our definition and calculation of t he pixel coincidence rate for the multi-angular detection, an effective multi-angle observation’s pixel matching method is presented to solve the spatial matching problem for airborne AMPR. Assuming the shape of AMPR’s each pixel is an ellipse, and the major axis and minor axis depends on the flying attitude and each scanning angle. By the definition of coordinate system and origin of coordinate, the latitude and longitude could be transformed into the Euclidian distance, and the pixel coincidence rate of two nearby ellipses could be calculated. Via the traversal of each ground pixel, those pixels with high coincidence rate could be selected and merged, and with the further quality control of observation data, thus the ground pixels dataset with multi-angular detection could be obtained and analyzed, providing the support for the multi-angular and polarized retrieval algorithm research in t he next study.
With the polynomial fitting of source function in each order of scattering calculation and the effective process of aerosol forward scattering peak, a polarized radiative transfer (RT) model based on the improved successive order of scattering (SOS) method has been developed to solve the vector radiative transfer equation. By our RT model, not only the total Stokes parameters [I, Q, U] measured by the satellite (aircraft) and ground-based sensors with linear polarization could be approximately simulated, but also the results of parameters for each scattering order event could conveniently calculated, which are very helpful to study the polarization properties for the atmospheric aerosol multiple scattering. In this study, the synchronous measured aerosol results including aerosol optical depth, complex refractive index and particle size distribution from AERONET under different air conditions, are considered as the input parameters for the successive scattering simulations. With our polarized RT model and the Mie code combined, the Stokes parameters as well as the degree of polarization for each scattering order are simulated and presented; meanwhile, the polarization (depolarization) properties of multiply scattering are preliminary analyzed and compared with different air quality (clear and pollution). Those results could provide a significant support for the further research of polarized aerosol remote sensing and inversion. Polarization properties of aerosol, successive order of scattering, vector radiative transfer equation, polynomial fitting of source function , multiply scattering
The Geostationary Ocean Color Imager (GOCI) provides multispectral imagery of the East Asia region hourly from 9:00 to 16:00 local time (GMT+9) and collects multispectral imagery at eight spectral channels (412, 443, 490, 555, 660, 680, 745, and 865 nm) with a spatial resolution of 500 m. Thus, this technology brings significant advantages to high temporal resolution environmental monitoring. We present the retrieval of aerosol optical depth (AOD) in northern China based on GOCI data. Cross-calibration was performed against Moderate Resolution Imaging Spectrometer (MODIS) data in order to correct the land calibration bias of the GOCI sensor. AOD retrievals were then accomplished using a look-up table (LUT) strategy with assumptions of a quickly varying aerosol and a slowly varying surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of a series of observations in a short period of time, such as several days. The monitoring of hourly AOD variations was implemented, and the retrieved AOD agreed well with AErosol RObotic NETwork (AERONET) ground-based measurements with a good R2 of approximately 0.74 at validation sites at the cities of Beijing and Xianghe, although intercept bias may be high in specific cases. The comparisons with MODIS products also show a good agreement in AOD spatial distribution. This work suggests that GOCI imagery can provide high temporal resolution monitoring of atmospheric aerosols over land, which is of great interest in climate change studies and environmental monitoring.
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