The Moderate Resolution Imaging Spectroradiometer (MODIS) has provided a large number of high-quality remote sensing data for Earth observation since its launch. Although the reflectance data is calibrated by on-board calibrators, it also needs to be verified by other independent methods in order to ensure the accuracy and reliability of the data. Thus, the Rayleigh scattering method is used to evaluate the MODIS/Aqua reflectance data in our study. In order to obtain high-precision Rayleigh scattering calculation results, the atmospheric and oceanic parameters (AOPs) corresponding to the local time and place, such as wind speed, aerosol optical depth, ozone amount, chlorophyll concentration, and seawater salinity, are put into a radiative transfer model to calculate after a series of screening. The current research selects the pixels with strong Rayleigh scattering characteristics in four days from a global ocean scene. The simulated reflectance is compared with the MYD021KM reflectance product in five visible bands, which presents the total uncertainties as, respectively, 1.39% (412 nm), 0.14% (469 nm), −0.18 % (488 nm), −0.47 % (531 nm), −0.41 % (551 nm). The verification results prove that the MODIS reflectance product remains at a high level of precision without significant deviation after having operated in orbit for 16 years, and the MODIS product has high interband self-consistency. The sensitivity analysis shows that the wind speed and chlorophyll concentration perturbed more to the simulated reflectance than other AOPs of the selected samples. It is believed that the methodology can be applicable to other visible light sensors for validating their reflectance product accurately.
GaoFen-4 (GF-4) is China’s first optical remote sensing geostationary satellite, which observes the Earth’s surface every 20 s. GF-4 has a gaze camera with a ground resolution of 50 m in the visible spectral bands that are sensitive to aerosol optical depth (AOD). AOD retrieval was completed using initial prior surface reflectance in ground-atmosphere decoupling. Surface reflectance was then updated using satellite measurements. The algorithm used in this study was based on two time-adjacent images of GF-4 (which have a constant viewing angle in the same area) and on the following two assumptions: (1) AOD varies quickly with time, but slowly with location and (2) surface reflectance varies quickly with location, but slowly with time. AOD retrieval was then accomplished using a lookup table strategy. The data from June 2016, in the North China Plain were selected for the AOD retrieval test. GF-4-derived AOD was validated using ground measurements from the aerosol robotic network and Sun–Sky radiometer network with a correlation coefficient of R = 0.794. The derived results agreed reasonably well with the moderate resolution imaging spectroradiometer collection 6.0 aerosol product, with a correlation coefficient of R = 0.893. The atmospheric distribution and changes in some parts of the North China Plain were analyzed using the aerosol products of GF-4. The results showed that it is feasible to use the time-series imaging method to conduct high spatiotemporal resolution aerosol inversion using GF-4’s data, which can be used for detecting changes in air pollution.
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.
Water vapor and aerosol are two key atmospheric factors effecting the remote sensing image quality. As water vapor is responsible for most of the solar radiation absorption occurring in the cloudless atmosphere, accurate measurement of water content is important to not only atmospheric correction of remote sensing images, but also many other applications such as the study of energy balance and global climate change, land surface temperature retrieval in thermal remote sensing. A multi-spectral, single-angular, polarized radiometer called Polarized Scanning Atmospheric Corrector (PSAC) were developed in China, which are designed to mount on the same satellite platform with the principle payload and provide essential parameters for principle payload image atmospheric correction. PSAC detect water vapor content via measuring atmosphere reflectance at water vapor absorbing channels (i.e. 0.91 μm) and nearby atmospheric window channel (i.e. 0.865μm). A near-IR channel ratio method was implemented to retrieve column water vapor (CWV) amount from PSAC measurements. Field experiments were performed at Yantai, in Shandong province of China, PSAC aircraft observations were acquired. The comparison between PSAC retrievals and ground-based Sun-sky radiometer measurements of CWV during the experimental flights illustrates that this method retrieves CWV with relative deviations ranging from 4% ~ 13%. This method retrieve CWV more accurate over land than over ocean, as the water reflectance is low.
KEYWORDS: Solar radiation, Ultraviolet radiation, Ozone, Atmospheric modeling, Remote sensing, Aerospace engineering, Solar processes, Stratosphere, Data modeling, Solar radiation models
Aerospace activity becomes research hotspot for worldwide aviation big countries. Solar radiation study is the prerequisite for aerospace activity to carry out, but lack of observation in near space layer becomes the barrier. Based on reanalysis data, input key parameters are determined and simulation experiments are tried separately to simulate downward solar radiation and ultraviolet radiation transfer process of near space in China area. Results show that atmospheric influence on the solar radiation and ultraviolet radiation transfer process has regional characteristic. As key factors such as ozone are affected by atmospheric action both on its density, horizontal and vertical distribution, meteorological data of stratosphere needs to been considered and near space in China area is divided by its activity feature. Simulated results show that solar and ultraviolet radiation is time, latitude and ozone density-variant and has complicated variation characteristics.
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.
Information on the vertical distribution of aerosol is important for understanding its transport characteristics as well as aerosol retrieval uncertainty. In this paper, the believable lidar ratio under clear sky condition during December 2014 is determined from ground-based lidar and sun-photometer site in Beijing. Then two methods are adopted to derive typical aerosol extinction profiles by averaging attenuated backscatter and retrieved extinction profiles respectively. The results indicate that the former vertical gradient of dispersion (standard deviation) is smaller than the latter. Moreover, the comparison of the aerosol extinction coefficient profiles shows a good consistency above 2km but significant difference below that altitude.
A hyper spectral ground-based instrument named Atmosphere-Surface Radiation Automatic Instrument (ASRAI) has been developed for the purpose of in-situ calibration of satellites. The apparatus has both upward and downward looking views, and thus can observe both the atmosphere and land surface. The solar transmitted irradiance can be derived from the measured full spectral irradiance and diffused spectral irradiance of atmosphere within visible spectrum (0.4-1.0μm). A method similar to that of King et al. which originally intended to apply to multi-wavelength measurements, is adopted to determine absorptive gaseous columnar amount from hyper spectrum. The solar irradiance at top of atmosphere and absorption coefficients of water vapor (H2O), ozone (O3), oxygen (O2) and nitrogen dioxide (NO2) are recalculated at an instrumental spectral resolution by convolution method. Based on the gaseous characteristics of absorption, the total columnar amounts of water vapor and oxygen are first inferred from solar transmitted irradiance at strong absorption wavelength of 0.934μm and 0.763μm respectively. The total columnar amounts of ozone and nitrogen dioxide, together with aerosol optical depth, are determined by a nonlinear least distance fitting method which minimizes a χ2 statistic to obtain optimal solutions. ASRAI was deployed for observation in Dunhuang site in China in August of 2014. Our results demonstrate that the algorithm is reasonable. Although the validation is preliminary, the hyper spectrum measured by ASRAI exhibits good ability to retrieve the abundance of absorptive gases and aerosols.
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.
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.
The increasing developments in Unmanned Aerial Vehicles (UAVs) platforms and associated sensing technologies have
widely promoted UAVs remote sensing application. UAVs, especially low-cost UAVs, limit the sensor payload in
weight and dimension. Mostly, cameras on UAVs are panoramic, fisheye lens, small-format CCD planar array camera,
unknown intrinsic parameters and lens optical distortion will cause serious image aberrations, even leading a few meters
or tens of meters errors in ground per pixel. However, the characteristic of high spatial resolution make accurate geolocation
more critical to UAV quantitative remote sensing research. A method for MCC4-12F Multispectral Imager
designed to load on UAVs has been developed and implemented. Using multi-image space resection algorithm to assess
geometric calibration parameters of random position and different photogrammetric altitudes in 3D test field, which is
suitable for multispectral cameras. Both theoretical and practical accuracy assessments were selected. The results of
theoretical strategy, resolving object space and image point coordinate differences by space intersection, showed that
object space RMSE were 0.2 and 0.14 pixels in X direction and in Y direction, image space RMSE were superior to 0.5
pixels. In order to verify the accuracy and reliability of the calibration parameters,practical study was carried out in
Tianjin UAV flight experiments, the corrected accuracy validated by ground checkpoints was less than 0.3m. Typical
surface reflectance retrieved on the basis of geo-rectified data was compared with ground ASD measurement resulting 4%
discrepancy. Hence, the approach presented here was suitable for UAV multispectral imager.
In June 2008, Enteromorpha prolifra, a kind of green algae, widely distributed in the Surface Water of the Yellow Sea of
China and posed a threat to the 29th Olympic Sailing Games. An 11-channel scanner was used to monitoring the spatial
distribution situation. We will introduce the aerial remote sensing monitoring method in this paper. There are three
objectives. 1) Analyze the spectrum of Enteromorpha prolifra, ocean water and sun glitter in multispectral aerial images;
2) Based on the ground-based and aerial spectrum properties, chose the optimal recognition method and practiced with
software tools; 3) validate the results of aerial remote sensing with field survey. The validation results were preferably
well.
CBIR (Content-Based Image Retrieval), which includes feature selection, feature extraction, similarity measurement and
user feedback parts, often uses feedback to improve the retrieval accuracy. But there are two problems of Feedback: 1)
improving the retrieval accuracy, but also increasing the user's operation complexity; 2) it is not easy to confirm the
weight values of each feature in similarity measurement. In this paper, a feedforward idea from Control Theory was used
in CBIR system. The method is to select an obvious feature automatically from multi-features, and then give a higher
weight value to the obvious feature in the similarity measurement. Experiment results show that the method presented is
efficient in image retrieval based on feedforward idea.
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