scholarly journals HIGH RESOLUTION AEROSOL OPTICAL DEPTH MAPPING OF BEIJING USING LANSAT8 IMAGERY

2016 ◽  
Vol XLI-B8 ◽  
pp. 1309-1312
Author(s):  
Yan Li ◽  
Yuanliang Liu ◽  
Jianliang Wu
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Urban Areas ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Temporal Data ◽  
A Value ◽  
Innovative Method ◽  
Satellite Signal

Aerosol Optical Depth (AOD) is one of the most important parameters in the atmospheric correction of remote sensing images. We present a new method of per pixel AOD retrieval using the imagery of Landsat8. It is based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S). General dark target method takes dense vegetation pixels as dark targets and derives their 550nm AODs directly from the LUT, and interpolates the AODs of other pixels according to spatial neighbourhood using those of dark target pixels. This method will down estimate the AOD levels for urban areas. We propose an innovative method to retrieval the AODs using multiple temporal data. For a pixel which has nothing change between the associated time, there must exists an intersection of surface albedo. When there are enough data to find the intersection it ought to be a value that meet the error tolerance. In this paper, we present an example of using three temporal Landsat ETM+ image to retrieve AOD taking Beijing as the testing area. The result is compared to the commonly employed dark target algorithm to show the effectiveness of the methods.

scholarly journals HIGH RESOLUTION AEROSOL OPTICAL DEPTH MAPPING OF BEIJING USING LANSAT8 IMAGERY

2016 ◽  
Vol XLI-B8 ◽  
pp. 1309-1312
Author(s):  
Yan Li ◽  
Yuanliang Liu ◽  
Jianliang Wu
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Urban Areas ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Temporal Data ◽  
A Value ◽  
Innovative Method ◽  
Satellite Signal

Aerosol Optical Depth (AOD) is one of the most important parameters in the atmospheric correction of remote sensing images. We present a new method of per pixel AOD retrieval using the imagery of Landsat8. It is based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S). General dark target method takes dense vegetation pixels as dark targets and derives their 550nm AODs directly from the LUT, and interpolates the AODs of other pixels according to spatial neighbourhood using those of dark target pixels. This method will down estimate the AOD levels for urban areas. We propose an innovative method to retrieval the AODs using multiple temporal data. For a pixel which has nothing change between the associated time, there must exists an intersection of surface albedo. When there are enough data to find the intersection it ought to be a value that meet the error tolerance. In this paper, we present an example of using three temporal Landsat ETM+ image to retrieve AOD taking Beijing as the testing area. The result is compared to the commonly employed dark target algorithm to show the effectiveness of the methods.

scholarly journals Aerosol optical depth (AOD) retrieval for atmospheric correction in Landsat-8 imagery using second simulation of a satellite signal in the solar spectrum-vector (6SV)

2019 ◽  
Vol 4 (2) ◽  
pp. 68-73
Author(s):  
Abdul Basith ◽  
Muhammad Ulin Nuha ◽  
Ratna Prastyani ◽  
Gathot Winarso
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Landsat 8 ◽  
Observation Data ◽  
Surface Reflectance ◽  
Corrected Image ◽  
Satellite Signal ◽  
Level 2

Atmospheric correction has been challenging task in digital image processing. It requires several atmospheric parameters in order to obtain accurate surface reflectance of objects within the image scene. One of the most crucial parameters required for accurate atmospheric correction is aerosol optical depth (AOD). AOD can be obtained by in-situ measurement or estimated from remote sensing observation. In this experiment, atmospheric correction was performed using second simulation of a satellite signal in the solar spectrum-vector (6SV) algorithm on Landsat-8 imagery in which AOD parameter was retrieved from surface reflectance inversion involving daily-global surface reflectance product of moderate resolution imaging spectroradiometer (MODIS). Furthermore, AOD retrieved from surface reflectance inversion was also validated using ground-based sun photometer observation data from aerosol robotic network (AERONET) station in Bandung, Indonesia. Our experiment shows the consistency between AOD from surface reflectance inversion and AOD from ground-based observation. Finally, 6SV was performed on Landsat-8 imagery to obtain the surface reflectance. We further compared surface reflectance of 6SV atmospheric correction and surface reflectance of Landsat-8 Level 2 product. The atmospherically corrected image also shared agreeable result with Landsat 8 Level-2 product.

scholarly journals High resolution aerosol data from MODIS satellite for urban air quality studies

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
A. Chudnovsky ◽  
A. Lyapustin ◽  
Y. Wang ◽  
C. Tang ◽  
J. Schwartz ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Urban Areas ◽  
Atmospheric Correction ◽  
Ground Surface ◽  
Local Analysis ◽  
Boundary Layer Height ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Relationship

AbstractThe Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM2.5 as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R2 =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM2.5 ground concentrations. Finally, we studied the relationship between PM2.5 and AOD at the intra-urban scale (≤10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM2.5 relationship does not depend on relative humidity and air temperatures below ~7 °C. The correlation improves for temperatures above 7–16 °C. We found no dependence on the boundary layer height except when the former was in the range 250–500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM2.5 concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM2.5 relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM2.5 mass concentrations are highly correlated with the actual observations (out-of-sample R2 of 0.86). Therefore, adjustment for the daily variability in the AOD-PM2.5 relationship provides a means for obtaining spatially-resolved PM2.5 concentrations.

scholarly journals An Aerosol Optical Depth time series 1982–2014 for atmospheric correction based on OMI and TOMS Aerosol Index

2016 ◽  
Author(s):  
Emmihenna Jääskeläinen ◽  
Terhikki Manninen ◽  
Johanna Tamminen ◽  
Marko Laine
Keyword(s):  
Time Series ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
In Situ Measurements ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Aerosol Index

Abstract. The atmospheric correction of old optical satellite data is problematic, because corresponding Aerosol Optical Depth (AOD) measurements in the visible wavelength range do not exist. The construction of an AOD time series for atmospheric correction purposes to cover the period 1982–2014 is described in this paper. The AOD estimates are calculated from the Aerosol Index (AI) data from the Total Ozone Mapping Spectrometer (TOMS) and the Ozone Monitoring Instrument (OMI). We apply this time series to the generation of the surface albedo data set CLARA-A2-SAL (the Surface ALbedo from the CM SAF cLoud, Albedo and RAdiation data set, the second version). The constructed AOD time series is temporally homogeneous, and it has sufficient quality compared to the AOD from OMI observations and from in situ measurements. The simulated atmospheric correction calculations, where the constructed AOD data are used as an aerosol input, are similar to the simulations where the aerosol information from OMI and in situ measurements is used. Also, the simulations show that the use of the constructed AOD time series decreases the surface reflectance values (the output of the atmospheric correction) globally compared to the use of the constant AOD value 0.1.

scholarly journals Calibration of Satellite Low Radiance by AERONET-OC Products and 6SV Model

2021 ◽  
Vol 13 (4) ◽  
pp. 781
Author(s):  
Cristiana Bassani ◽  
Sindy Sterckx
Keyword(s):  
Optical Sensors ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Water Quality Monitoring ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Blue Band ◽  
Satellite Signal ◽  
Almost All ◽  
User Friendly

For water quality monitoring using satellite data, it is often required to optimize the low radiance signal through the application of radiometric gains. This work describes a procedure for the retrieval of radiometric gains to be applied to OLI/L8 and MSI/S2A data over coastal waters. The gains are defined by the ratio of the top of atmosphere (TOA) reflectance simulated using the Second Simulation of a Satellite Signal in the Solar Spectrum—vector (6SV) radiative transfer model, REF, and the TOA reflectance acquired by the sensor, MEAS, over AERONET-OC stations. The REF is simulated considering quasi-synchronous atmospheric and aquatic AERONET-OC products and the image acquisition geometry. Both for OLI/L8 and MSI/S2A the measured TOA reflectance was higher than the modeled signal in almost all bands resulting in radiometric gains less than 1. The use of retrieved gains showed an improvement of reflectance remote sensing, Rrs, when with ACOLITE atmospheric correction software. When the gains are applied an accuracy improvement of the Rrs in the 400–700 nm domain was observed except for the first blue band of both sensors. Furthermore, the developed procedure is quick, user-friendly, and easily transferable to other optical sensors.

High resolution aerosol optical depth retrieval over urban areas from Landsat-8 OLI images

2021 ◽  
pp. 118591
Author(s):  
Hao Lin ◽  
Siwei Li ◽  
Jia Xing ◽  
Tao He ◽  
Jie Yang ◽  
...  
Keyword(s):  
High Resolution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Urban Areas ◽  
Landsat 8 ◽  
Landsat 8 Oli

scholarly journals The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm

2017 ◽  
Vol 9 (11) ◽  
pp. 1095 ◽  
Author(s):  
Emmihenna Jääskeläinen ◽  
Terhikki Manninen ◽  
Johanna Tamminen ◽  
Marko Laine
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
Land Cover Class ◽  
Cover Class ◽  
Aerosol Index

scholarly journals Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading

2021 ◽  
Vol 13 (8) ◽  
pp. 1544
Author(s):  
Tang-Huang Lin ◽  
Si-Chee Tsay ◽  
Wei-Hung Lien ◽  
Neng-Huei Lin ◽  
Ta-Chih Hsiao
Keyword(s):  
Optical Depth ◽  
Complex Refractive Index ◽  
Solar Spectrum ◽  
Collective Models ◽  
Anthropogenic Pollutants ◽  
Satellite Signal ◽  
Aerosol Compositions ◽  
Theoretical Simulations ◽  
Derivatives Of ◽  
Aerosol Index

Quantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored to determine the partitions of the major components of aerosols based on the spectral dependence of their particle optical size and complex refractive index. With theoretical simulations from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) model, AOD spectral derivatives are characterized for collective models of aerosol types, such as mineral dust (DS) particles, biomass-burning (BB) aerosols and anthropogenic pollutants (AP), as well as stretching out to the mixtures among them. Based on the intrinsic values from normalized spectral derivatives, referenced as the Normalized Derivative Aerosol Index (NDAI), a unique pattern is clearly exhibited for bounding the major aerosol components; in turn, fractions of the total AOD (fAOD) for major aerosol components can be extracted. The subtlety of this NDAI method is examined by using measurements of typical aerosol cases identified carefully by the ground-based Aerosol Robotic Network (AERONET) sun–sky spectroradiometer. The results may be highly practicable for quantifying fAOD among mixed-type aerosols by means of the normalized AOD spectral derivatives.

Aerosol Optical Depth for Atmospheric Correction of AVHRR Composite Data

2000 ◽  
Vol 26 (4) ◽  
pp. 273-284 ◽  
Author(s):  
G. Fedosejevs ◽  
N.T. O'Neill ◽  
A. Royer ◽  
P.M. Teillet ◽  
A.I. Bokoye ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
Composite Data

scholarly journals Retrieval of Fine-Resolution Aerosol Optical Depth (AOD) in Semiarid Urban Areas Using Landsat Data: A Case Study in Urumqi, NW China

2020 ◽  
Vol 12 (3) ◽  
pp. 467 ◽  
Author(s):  
Xiangyue Chen ◽  
Jianli Ding ◽  
Jingzhe Wang ◽  
Xiangyu Ge ◽  
Mayira Raxidin ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Urban Areas ◽  
Lookup Table ◽  
Atmospheric Environment ◽  
Sustainable Urban Development ◽  
Long Distance ◽  
Hysplit Model ◽  
Variation Characteristics ◽  
Fine Resolution

The aerosol optical depth (AOD) represents the light attenuation by aerosols and is an important threat to urban air quality, production activities, human health, and sustainable urban development in arid and semiarid regions. To some extent, the AOD reflects the extent of regional air pollution and is often characterized by significant spatiotemporal dynamics. However, detailed local AOD information is ambiguous at best due to limited monitoring techniques. Currently, the availability of abundant satellite data and constantly updated AOD extraction algorithms offer unprecedented perspectives for high-resolution AOD extraction and long-time series analysis. This study, based on the long-term sequence MOD09A1 data from 2010 to 2018 and lookup table generation, uses the improved deep blue algorithm (DB) to conduct fine-resolution (500 m) AOD (at 550 nm wavelength) remote sensing (RS) estimation on Landsat TM/OLI data from the Urumqi region, analyzes the spatiotemporal AOD variation characteristics in Urumqi and combines gray relational analysis (GRA) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to analyze AOD influence factors and simulate pollutant propagation trajectories in representative periods. The results demonstrate that the improved DB algorithm has a high inversion accuracy for continuous AOD inversion at a high spatial resolution in urban areas. The spatial AOD distribution in Urumqi declines from urban to suburban areas, and higher AODs are concentrated in cities and along roads. Among these areas, Xinshi District has the highest AOD, and Urumqi County has the lowest AOD. The seasonal AOD variation characteristics are distinct, and the AOD order is spring (0.411) > summer (0.285) > autumn (0.203), with the largest variation in spring. The average AOD in Urumqi is 0.187, and the interannual variation generally shows an upward trend. However, from 2010 to 2018, AOD first declined gradually and then declined significantly. Thereafter, AOD reached its lowest value in 2015 (0.076), followed by a significant AOD increase, reaching a peak in 2016 (0.354). This shows that coal to natural gas (NG) project implementation in Urumqi promoted the improvement of Urumqi’s atmospheric environment. According to GRA, the temperature has the largest impact on the AOD in Urumqi (0.699). Combined with the HYSPLIT model, it was found that the aerosols observed over Urumqi were associated with long-range transport from Central Asia, and these aerosols can affect the entire northern part of China through long-distance transport.

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