scholarly journals Retrieving High-Resolution Aerosol Optical Depth from GF-4 PMS Imagery in Eastern China

2021 ◽  
Vol 13 (18) ◽  
pp. 3752
Author(s):  
Zhendong Sun ◽  
Jing Wei ◽  
Ning Zhang ◽  
Yulong He ◽  
Yu Sun ◽  
...  

Gaofen 4 (GF-4) is a geostationary satellite, with a panchromatic and multispectral sensor (PMS) onboard, and has great potential in observing atmospheric aerosols. In this study, we developed an aerosol optical depth (AOD) retrieval algorithm for the GF-4 satellite. AOD retrieval was realized based on the pre-calculated surface reflectance database and 6S radiative transfer model. We customized the unique aerosol type according to the long time series aerosol parameters provided by the Aerosol Robotic Network (AERONET) site. The solar zenith angle, relative azimuth angle, and satellite zenith angle of the GF-4 panchromatic multispectral sensor image were calculated pixel-by-pixel. Our 1 km AOD retrievals were validated against AERONET Version 3 measurements and compared with MOD04 C6 AOD products at different resolutions. The results showed that our GF-4 AOD algorithm had a good robustness in both bright urban areas and dark rural areas. A total of 71.33% of the AOD retrievals fell within the expected errors of ±(0.05% + 20%); root-mean-square error (RMSE) and mean absolute error (MAE) were 0.922 and 0.122, respectively. The accuracy of GF-4 AOD in rural areas was slightly higher than that in urban areas. In comparison with MOD04 products, the accuracy of GF-4 AOD was much higher than that of MOD04 3 km and 10 km dark target AOD, but slightly worse than that of MOD04 10 km deep blue AOD. For different values of land surface reflectance (LSR), the accuracy of GF-4 AOD gradually deteriorated with an increase in the LSR. These results have theoretical and practical significance for aerosol research and can improve retrieval algorithms using the GF-4 satellite.

2016 ◽  
Vol 9 (7) ◽  
pp. 3293-3308 ◽  
Author(s):  
Pawan Gupta ◽  
Robert C. Levy ◽  
Shana Mattoo ◽  
Lorraine A. Remer ◽  
Leigh A. Munchak

Abstract. The MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aboard the two Earth Observing System (EOS) satellites Terra and Aqua, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 and 3 km). Almost 15 years of aerosol data records are now available from MODIS that can be used for various climate and air-quality applications. However, the application of MODIS aerosol products for air-quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. This is largely because the urban surface reflectance behaves differently than that assumed for natural surfaces. In this study, we address the inaccuracies produced by the MODIS Dark Target (MDT) algorithm aerosol optical depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating MODIS Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the continental United States (CONUS). The new surface scheme takes into account the change in underlying surface type and is only applied for MODIS pixels with urban percentage (UP) larger than 20 %. Over the urban areas where the new scheme has been applied (UP > 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sun photometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation.


2022 ◽  
Vol 14 (2) ◽  
pp. 373
Author(s):  
Muhammad Bilal ◽  
Alaa Mhawish ◽  
Md. Arfan Ali ◽  
Janet E. Nichol ◽  
Gerrit de Leeuw ◽  
...  

The SEMARA approach, an integration of the Simplified and Robust Surface Reflectance Estimation (SREM) and Simplified Aerosol Retrieval Algorithm (SARA) methods, was used to retrieve aerosol optical depth (AOD) at 550 nm from a Landsat 8 Operational Land Imager (OLI) at 30 m spatial resolution, a Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) at 500 m resolution, and a Visible Infrared Imaging Radiometer Suite (VIIRS) at 750 m resolution over bright urban surfaces in Beijing. The SEMARA approach coupled (1) the SREM method that is used to estimate the surface reflectance, which does not require information about water vapor, ozone, and aerosol, and (2) the SARA algorithm, which uses the surface reflectance estimated by SREM and AOD measurements obtained from the Aerosol Robotic NETwork (AERONET) site (or other high-quality AOD) as the input to estimate AOD without prior information on the aerosol optical and microphysical properties usually obtained from a look-up table constructed from long-term AERONET data. In the present study, AOD measurements were obtained from the Beijing AERONET site. The SEMARA AOD retrievals were validated against AOD measurements obtained from two other AERONET sites located at urban locations in Beijing, i.e., Beijing_RADI and Beijing_CAMS, over bright surfaces. The accuracy and uncertainties/errors in the AOD retrievals were assessed using Pearson’s correlation coefficient (r), root mean squared error (RMSE), relative mean bias (RMB), and expected error (EE = ± 0.05 ± 20%). EE is the envelope encompassing both absolute and relative errors and contains 68% (±1σ) of the good quality retrievals based on global validation. Here, the EE of the MODIS Dark Target algorithm at 3 km resolution is used to report the good quality SEMARA AOD retrievals. The validation results show that AOD from SEMARA correlates well with AERONET AOD measurements with high correlation coefficients (r) of 0.988, 0.980, and 0.981; small RMSE of 0.08, 0.09, and 0.08; and small RMB of 4.33%, 1.28%, and -0.54%. High percentages of retrievals, i.e., 85.71%, 91.53%, and 90.16%, were within the EE for Landsat 8 OLI, MODIS, and VIIRS, respectively. The results suggest that the SEMARA approach is capable of retrieving AOD over urban areas with high accuracy and small errors using high to medium spatial resolution satellite remote sensing data. This approach can be used for aerosol monitoring over bright urban surfaces such as in Beijing, which is frequently affected by severe dust storms and haze pollution, to evaluate their effects on public health.


2016 ◽  
Author(s):  
P. Gupta ◽  
R. C. Levy ◽  
S. Mattoo ◽  
L. A. Remer ◽  
L. A. Munchak

Abstract. The MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aboard two Earth Observing Satellites (EOS) Terra and Aqua, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 km and 3 km). Almost 15 years of aerosol data records are now available from MODIS that can be used for various climate and air quality applications. However, the application of MODIS aerosol products for air quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. Here, in this study, we address the inaccuracies produced by the MODIS dark target algorithm (MDT) Aerosol Optical Depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating MODIS land surface reflectance and land cover type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the Continental United States (CONUS). The new surface scheme takes into account the change in under lying surface type and is only applied for MODIS pixels with urban percentage (UP) larger than 20%. Over the urban areas where the new scheme has been applied (UP > 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sunphotometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1, due to ultra sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation.


2011 ◽  
Vol 11 (4) ◽  
pp. 12519-12560
Author(s):  
H. Zhang ◽  
A. Lyapustin ◽  
Y. Wang ◽  
S. Kondragunta ◽  
I. Laszlo ◽  
...  

Abstract. Aerosol optical depth (AOD) retrieval from geostationary satellites has high temporal resolution compared to the polar orbiting satellites and thus enables us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosol and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified multi-angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) at channel 1 of GOES is proportional to seasonal average BRDF in the 2.1 μm channel from MODIS. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of the AOD and surface reflectance retrievals are evaluated through comparison against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US. They are comparable to the GASP retrievals in the eastern-central sites and are more accurate than GASP retrievals in the western sites. In the western US where surface reflectance is high, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.


2011 ◽  
Vol 11 (23) ◽  
pp. 11977-11991 ◽  
Author(s):  
H. Zhang ◽  
A. Lyapustin ◽  
Y. Wang ◽  
S. Kondragunta ◽  
I. Laszlo ◽  
...  

Abstract. Aerosol optical depth (AOD) retrievals from geostationary satellites have high temporal resolution compared to the polar orbiting satellites and thus enable us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosols and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) in the channel 1 of GOES is proportional to seasonal average MODIS BRDF in the 2.1 μm channel. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of AOD and surface reflectance retrievals are evaluated through comparisons against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US with correlation coefficients ranges from 0.71 to 0.85 at five out of six sites. At the two western sites Railroad Valley and UCSB, the MAIAC AOD retrievals have correlations of 0.8 and 0.85 with AERONET AOD, and are more accurate than GASP retrievals, which have correlations of 0.7 and 0.74 with AERONET AOD. At the three eastern sites, the correlations with AERONET AOD are from 0.71 to 0.81, comparable to the GASP retrievals. In the western US where surface reflectance is higher than 0.15, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.


2021 ◽  
Vol 13 (20) ◽  
pp. 4140
Author(s):  
Hao Lin ◽  
Siwei Li ◽  
Jia Xing ◽  
Jie Yang ◽  
Qingxin Wang ◽  
...  

Recent studies have shown that the high-resolution satellite Landsat-8 has the capability to retrieve aerosol optical depth (AOD) over urban areas at a 30 m spatial resolution. However, its long revisiting time and narrow swath limit the coverage and frequency of the high resolution AOD observations. With the increasing number of Earth observation satellites launched in recent years, combining the observations of multiple satellites can provide higher temporal-spatial coverage. In this study, a fusing retrieval algorithm is developed to retrieve high-resolution (30 m) aerosols over urban areas from Landsat-8 and Sentinel-2 A/B satellite measurements. The new fusing algorithm was tested and evaluated over Beijing city and its surrounding area in China. The validation results show that the retrieved AODs show a high level of agreement with the local urban ground-based Aerosol Robotic Network (AERONET) AOD measurements, with an overall high coefficient of determination (R2) of 0.905 and small root mean square error (RMSE) of 0.119. Compared with the operational AOD products processed by the Landsat-8 Surface Reflectance Code (LaSRC-AOD), Sentinel Radiative Transfer Atmospheric Correction code (SEN2COR-AOD), and MODIS Collection 6 AOD (MOD04) products, the AOD retrieved from the new fusing algorithm based on the Landsat-8 and Sentinel-2 A/B observations exhibits an overall higher accuracy and better performance in spatial continuity over the complex urban area. Moreover, the temporal resolution of the high spatial resolution AOD observations was greatly improved (from 16/10/10 days to about two to four days over globe land in theory under cloud-free conditions) and the daily spatial coverage was increased by two to three times compared to the coverage gained using a single sensor.


2007 ◽  
Vol 7 (20) ◽  
pp. 5467-5477 ◽  
Author(s):  
A. D. de Almeida Castanho ◽  
R. Prinn ◽  
V. Martins ◽  
M. Herold ◽  
C. Ichoku ◽  
...  

Abstract. The surface reflectance ratio between the visible (VIS) and shortwave infrared (SWIR) radiation is an important quantity for the retrieval of the aerosol optical depth (τa) from the MODIS sensor data. Based on empirically determined VIS/SWIR ratios, MODIS τa retrieval uses the surface reflectance in the SWIR band (2.1 µm), where the interaction between solar radiation and the aerosol layer is small, to predict the visible reflectances in the blue (0.47 µm) and red (0.66 µm) bands. Therefore, accurate knowledge of the VIS/SWIR ratio is essential for achieving accurate retrieval of aerosol optical depth from MODIS. We analyzed the surface reflectance over some distinct surface covers in and around the Mexico City metropolitan area (MCMA) using MODIS radiances at 0.66 µm and 2.1 µm. The analysis was performed at 1.5 km×1.5 km spatial resolution. Also, ground-based AERONET sun-photometer data acquired in Mexico City from 2002 to 2005 were analyzed for aerosol depth and other aerosol optical properties. In addition, a network of hand-held sun-photometers deployed in Mexico City, as part of the MCMA-2006 Study during the MILAGRO Campaign, provided an unprecedented measurement of τa in 5 different sites well distributed in the city. We found that the average RED/SWIR ratio representative of the urbanized sites analyzed is 0.73±0.06 for scattering angles <140° and goes up to 0.77±0.06 for higher ones. The average ratio for non-urban sites was significantly lower (approximately 0.55). In fact, this ratio strongly depends on differences in urbanization levels (i.e. relative urban to vegetation proportions and types of surface materials). The aerosol optical depth retrieved from MODIS radiances at a spatial resolution of 1.5 km×1.5 km and averaged within 10×10 km boxes were compared with collocated 1-h τa averaged from sun-photometer measurements. The use of the new RED/SWIR ratio of 0.73 in the MODIS retrieval over Mexico City led to a significant improvement in the agreement between the MODIS and sun-photometer AOD results; with the slope, offset, and the correlation coefficient of the linear regression changing from (τaMODIS=0.91τa sun-photometer+0.33, R2=0.66) to (τaMODIS=0.96 τa sun-photometer−0.006, R2=0.87). Indeed, an underestimation of this ratio in urban areas lead to a significant overestimation of the AOD retrieved from satellite. Therefore, we strongly encourage similar analyses in other urban areas to enhance the development of a parameterization of the surface ratios accounting for urban heterogeneities.


2021 ◽  
Vol 13 (3) ◽  
pp. 365
Author(s):  
Ying Wang ◽  
Xingfa Gu ◽  
Jian Li ◽  
Xiaofei Mi

A NOAA/AVHRR dual-channel method over land is proposed to simultaneously retrieve aerosol optical depth (AOD) at 0.55 μm, and surface reflectance at 0.63 and 0.85 μm. Compared with previous well-established one-channel retrieval algorithms, this algorithm takes advantage of the surface reflectance ratio between 0.63 and 0.85 μm in an attempt to account for the effect induced by the surface bidirectional reflectance distribution function (BRDF). This effect cannot be negligible due to the orbit drift and phasing running of NOAA satellites, both of which potentially cause large solar angular variation. Meanwhile, the observation posture change of AVHRR would cause large sensor angular variation in time series measurements. The used surface reflectance ratio based on dual channels at 0.63 and 0.85 μm is found more reasonable to be assumed as unchanged during a certain period of time, compared to the traditional ratio when addressing the BRDF issue. AOD retrievals have been carried out over Eastern Asia. Validation against aerosol robotic network (AERONET) measurements shows that up to 83% of AOD validation collocations are within error lines (±0.15 ± 0.15τ, τ is AOD) with an R of 0.88 and an root mean square error (RMSE) of 0.15. The dual-channel algorithm taking into account the surface BRDF effect is proved outperforming the conventional 0.63 μm-channel method. It indicates that our algorithm has the potential to be applied to the retrieval of long series of AOD, especially to the AOD retrieval of the sensors which lack a shortwave infrared channel required in the MODerate resolution Imaging Spectroradiometer (MODIS) dark target AOD algorithm.


2016 ◽  
Author(s):  
Yerong Wu ◽  
Martin de Graaf ◽  
Massimo Menenti

Abstract. Aerosol Optical Depth (AOD) retrieved from MOderate Resolution Imaging Spectroradiometer (MODIS) measurements over land, can be improved by taking into account the surface Bidirectional Reflectance Distribution Function (BRDF), as shown in a previous study (Wu et al., 2016). However, the relationship of the surface reflectance between visible and short wave Infrared band that applied in the previous study, can lead to an angular dependence of the AOD retrieval. This has at least two reasons. The relationship based on the assumption of isotropic reflection or Lambertian surface is not suitable for the surface directional-directional reflectance. On the other hand, although the relationship varies with the surface cover type by considering the vegetation index NDVI_SWIR, this index itself has a directional effect and affects the estimation of the surface reflection, and finally can lead to some errors in the AOD retrieval. To improve this situation, we derived a new relationship for the spectral surface directional-directional reflectance in this study, using 3 years of dataset from AERONET-based Surface Reflectance Validation Network (ASRVN). To test the performance of the new algorithm, three case studies were used: 2 years of data from Eastern China and North America, and 4 months of data from the global land. The results show that the angular effects of the AOD retrieval are largely reduced in most cases. Particularly, for the global land case, the AOD retrieval was improved by the new algorithm compared to the previous study and MODIS collection 6 dark target algorithm, with the increase of 2.5 % and 5 % AOD retrievals falling within the expected accuracy level ±(0.05 + 15 %), respectively.


2019 ◽  
Vol 18 (32) ◽  
pp. 4-17
Author(s):  
Le Thi Le ◽  
Lin Tang-Huang ◽  
Canh Van Le ◽  
Lan Thi Pham ◽  
Ha Thi Thu Le ◽  
...  

Aerosol optical depth (AOD) can be retrieved accurately with sequential ground-based measurements of direct and diffuse solar radiance. However, spatial coverage and location frequency cause certain limitations. Hence, satellite image data are a proper tool for obtaining aerosol optical depth products with more spatial information and patterns of aerosol distribution. Currently, aerosol remote sensing may enhance our understanding of the optimal approach to AOD retrieval over urban and rural areas, and how it differs due to the characteristics of surface reflectivity. The article deals with the concepts of contrast reduction, and dark target approaches are examined using Landsat imaging and the observation of a sun photometer for integrating aerosol optical depth distribution over the city of Taipei in Taiwan. For areas with bright surfaces, such as urban areas, the above concepts were applied using the dispersion coefficient method with a sun photometer, in order to reduce errors considerably in the product. In contrast, a dark target algorithm with a relationship of surface reflectance between the blue (0.49 μm), red (0.66 μm), and infrared (2.1 μm) spectral bands is suitable for moist soils and vegetation areas. The retrieval of AOD spatial distribution is compared with MODIS AOD products and AERONET to verify the accuracy of the results. The RMSE ranged from 0.2 to 0.4, and about 50% of the data were within expected error margins (EE=± (0.05+0.15 AODsunphotometer).


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