scholarly journals Integration of Surface Reflectance and Aerosol Retrieval Algorithms for Multi-Resolution Aerosol Optical Depth Retrievals over Urban Areas

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.

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.


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.


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.


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.


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.


2021 ◽  
pp. 118591
Author(s):  
Hao Lin ◽  
Siwei Li ◽  
Jia Xing ◽  
Tao He ◽  
Jie Yang ◽  
...  

2018 ◽  
Vol 15 (7) ◽  
pp. 976-980 ◽  
Author(s):  
Xinpeng Tian ◽  
Qiang Liu ◽  
Zhenwei Song ◽  
Baocheng Dou ◽  
Xiuhong Li

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.


2013 ◽  
Vol 6 (1) ◽  
pp. 2227-2251 ◽  
Author(s):  
L. Mei ◽  
Y. Xue ◽  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
G. de Leeuw ◽  
...  

Abstract. The Advanced Very High Resolution Radiometer (AVHRR) radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surface albedo are challenging because of the information content of the measurement is limited and the inversion of these data products being ill defined. Solving the radiative transfer equations requires additional information and knowledge to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in Moderate Resolution Imaging Spectroradiometer (MODIS) data. Next, following the MODIS dark target approach, the surface reflectance at 0.64 μm was obtained. The comparison of the estimated surface reflectance at 0.64 μm with MODIS reflectance products (MOD09) shows a strong correlation (R = 0.7835). Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to Advanced Very High Resolution Radiometer (AVHRR) data. A simplified Look-Up Table (LUT) method, adopted from Bremen AErosol Retrieval (BAER) algorithm, was used in the retrieval. The Aerosol Optical Depth (AOD) values retrieved from AVHRR with this method compare favourably with ground-based measurements, with a correlation coefficient R = 0.861 and Root Mean Square Error (RMSE) = 0.17. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to geostationary satellites.


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