scholarly journals Retrieval of Urban Aerosol Optical Depth from Landsat 8 OLI in Nanjing, China

2021 ◽  
Vol 13 (3) ◽  
pp. 415
Author(s):  
Yangyang Jin ◽  
Zengzhou Hao ◽  
Jian Chen ◽  
Dong He ◽  
Qingjiu Tian ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Absolute Error ◽  
Meteorological Conditions ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Large Area ◽  
The North ◽  
Deep Blue ◽  
Seasonal Characteristics

Aerosol is an essential parameter for assessing the atmospheric environmental quality, and accurate monitoring of the aerosol optical depth (AOD) is of great significance in climate research and environmental protection. Based on Landsat 8 Operational Land Imager (OLI) images and MODIS09A1 surface reflectance products under clear skies with limited cloud cover, we retrieved the AODs in Nanjing City from 2017 to 2018 using the combined Dark Target (DT) and Deep Blue (DB) methods. The retrieval accuracy was validated by in-situ CE-318 measurements and MOD04_3K aerosol products. Furthermore, we analyzed the spatiotemporal distribution of the AODs and discussed a case of high AOD distribution. The results showed that: (1) Validated by CE-318 and MOD04_3K data, the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) of the retrieved AODs were 0.874 and 0.802, 0.134 and 0.188, and 0.099 and 0.138, respectively. Hence, the combined DT and DB algorithms used in this study exhibited a higher performance than the MOD04_3K-obtained aerosol products. (2) Under static and stable meteorological conditions, the average annual AOD in Nanjing was 0.47. At the spatial scale, the AODs showed relatively high values in the north and west, low in the south, and the lowest in the center. At the seasonal scale, the AODs were highest in the summer, followed by spring, winter, and autumn. Moreover, changes were significantly higher in the summer than in the other three seasons, with little differences among spring, autumn, and winter. (3) Based on the spatial and seasonal characteristics of the AOD distribution in Nanjing, a case of high AOD distribution caused by a large area of external pollution and local meteorological conditions was discussed, indicating that it could provide extra details of the AOD distribution to analyze air pollution sources using fine spatial resolution like in the Landsat 8 OLI.

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 Aerosol Optical Depth Retrieval From Landsat 8 OLI Images Over Urban Areas Supported by MODIS BRDF/Albedo Data

2018 ◽  
Vol 15 (7) ◽  
pp. 976-980 ◽  
Author(s):  
Xinpeng Tian ◽  
Qiang Liu ◽  
Zhenwei Song ◽  
Baocheng Dou ◽  
Xiuhong Li
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Urban Areas ◽  
Landsat 8 ◽  
Landsat 8 Oli

scholarly journals Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images

2015 ◽  
Vol 8 (1) ◽  
pp. 23 ◽  
Author(s):  
Lin Sun ◽  
Jing Wei ◽  
Muhammad Bilal ◽  
Xinpeng Tian ◽  
Chen Jia ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Landsat 8 ◽  
Landsat 8 Oli

scholarly journals Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

2018 ◽  
Vol 11 (4) ◽  
pp. 2279-2293 ◽  
Author(s):  
Juan Carlos Antuña-Marrero ◽  
Victoria Cachorro Revilla ◽  
Frank García Parrado ◽  
Ángel de Frutos Baraja ◽  
Albeth Rodríguez Vega ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Linear Regression Analysis ◽  
Absolute Error ◽  
Poor Correlation ◽  
The Sun ◽  
Mean Values ◽  
Deep Blue ◽  
Comparison Results ◽  
Sun Photometer

Abstract. In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AODt) and Aqua (AODa) satellites and those measured using a sun photometer (AODSP) at Camagüey, Cuba, for the period 2008 to 2014. The comparison of Terra and Aqua data includes AOD derived with both deep blue (DB) and dark target (DT) algorithms from MODIS Collection 6. Combined Terra and Aqua (AODta) data were also considered. Assuming an interval of ±30 min around the overpass time and an area of 25 km around the sun photometer site, two coincidence criteria were considered: individual pairs of observations and both spatial and temporal mean values, which we call collocated daily means. The usual statistics (root mean square error, RMSE; mean absolute error, MAE; median bias, BIAS), together with linear regression analysis, are used for this comparison. Results show very similar values for both coincidence criteria: the DT algorithm generally displays better statistics and higher homogeneity than the DB algorithm in the behaviour of AODt, AODa, AODta compared to AODSP. For collocated daily means, (a) RMSEs of 0.060 and 0.062 were obtained for Terra and Aqua with the DT algorithm and 0.084 and 0.065 for the DB algorithm, (b) MAE follows the same patterns, (c) BIAS for both Terra and Aqua presents positive and negative values but its absolute values are lower for the DT algorithm; (d) combined AODta data also give lower values of these three statistical indicators for the DT algorithm; (e) both algorithms present good correlations for comparing AODt, AODa, AODta vs. AODSP, with a slight overestimation of satellite data compared to AODSP, (f). The DT algorithm yields better figures with slopes of 0.96 (Terra), 0.96 (Aqua) and 0.96 (Terra + Aqua) compared to the DB algorithm (1.07, 0.90, 0.99), which displays greater variability. Multi-annual monthly means of AODta establish a first climatology that is more comparable to that given by the sun photometer and their statistical evaluation reveals better agreement with AODSP for the DT algorithm. Results of the AE comparison showed similar results to those reported in the literature concerning the two algorithms' capacity for retrieval. A comparison between broadband aerosol optical depth (BAOD), derived from broadband pyrheliometer observations at the Camagüey site and three other meteorological stations in Cuba, and AOD observations from MODIS on board Terra and Aqua show a poor correlation with slopes below 0.4 for both algorithms. Aqua (Terra) showed RMSE values of 0.073 (0.080) and 0.088 (0.087) for the DB and DT algorithms. As expected, RMSE values are higher than those from the MODIS–sun photometer comparison, but within the same order of magnitude. Results from the BAOD derived from solar radiation measurements demonstrate its reliability in describing climatological AOD series estimates.

scholarly journals Monitoring the Spatial Variation of Aerosol Optical Depth and Its Correlation with Land Use/Land Cover in Wuhan, China: A Perspective of Urban Planning

2021 ◽  
Vol 18 (3) ◽  
pp. 1132
Author(s):  
Qijiao Xie ◽  
Qi Sun
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Urban Planning ◽  
Land Cover ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Water Bodies ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
The Impact

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.

scholarly journals Aerosol optical properties at Lampedusa (Central Mediterranean). 1. Influence of transport and identification of different aerosol types

2006 ◽  
Vol 6 (3) ◽  
pp. 697-713 ◽  
Author(s):  
G. Pace ◽  
A. di Sarra ◽  
D. Meloni ◽  
S. Piacentino ◽  
P. Chamard
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Central Mediterranean ◽  
Desert Dust ◽  
Central Eastern Europe ◽  
Angstrom Exponent ◽  
The North ◽  
Ångström Exponent ◽  
Summer Maximum ◽  
Ångstrom Exponent

Abstract. Aerosol optical depth and Ångström exponent were obtained from multi filter rotating shadowband radiometer (MFRSR) observations carried out at the island of Lampedusa, in the Central Mediterranean, in the period July 2001–September 2003. The average aerosol optical depth at 495.7 nm, τ, is 0.24±0.14; the average Ångström exponent, α, is 0.86±0.63. The observed values of τ range from 0.03 to 1.13, and the values of α vary from −0.32 to 2.05, indicating a large variability in aerosol content and size. In cloud-free conditions, 36% of the airmasses come from Africa, 25% from Central-Eastern Europe, and 19% from Western France, Spain and the North Atlantic. In summer, 42% of the airmasses is of African origin. In almost all cases African aerosols display high values of τ and low values of α, typical of Saharan dust (average values of τ and α are 0.36 and 0.42, respectively). Particles originating from Central-Eastern Europe show relatively large average values of τ and α (0.23 and 1.5, respectively), while particles from Western France, Spain and the North Atlantic show the lowest average values of τ (0.15), and relatively small values of α (0.92). Intermediate values of α are often connected with relatively fast changes of the airmass originating sector, suggesting the contemporary presence of different types of particles in the air column. Clean marine conditions are rare at Lampedusa, and are generally associated with subsidence of the airmasses reaching the island. Average values of τ and α for clean marine conditions are 0.11 and 0.86, respectively. The largest values of α (about 2) were observed in August 2003, when large scale forest fires in Southern Europe produced consistent amounts of fine combustion particles, that were transported to the Central Mediterranean by a persistent high pressure system over Central Europe. Smoke particles in some cases mix with desert dust, producing intermediate values of α. The seasonal distribution of the meteorological patterns over the Mediterranean, the efficiency of the aerosol production mechanisms, and the variability of the particles' residence time produce a distinct seasonal cycle of aerosol optical depths and Ångström exponent values. Particles originating from all sectors show a summer maximum in aerosol optical depth. The summer increase in optical depth for European aerosols is linked with an increment in the values of α, that indicates an enhancement in the number of fine particles. The summer maximum of τ for African particles is associated with a weak reduction in the Ångström exponent, suggesting an increase in the total number of particles and a relatively more intense transport of large particles. The observations were classified according to the aerosol optical properties, and two main classes have been identified: desert dust and biomass burning/urban-industrial aerosols. Values of τ and α averaged over the whole observing period are 0.37 and 0.15 for desert dust, and 0.27 and 1.77 for urban-industrial/biomass burning aerosols.

scholarly journals Comparison of MODIS and AERONET derived aerosol optical depth over the Ganga Basin, India

2005 ◽  
Vol 23 (4) ◽  
pp. 1093-1101 ◽  
Author(s):  
S. N. Tripathi ◽  
Sagnik Dey ◽  
A. Chandel ◽  
S. Srivastava ◽  
Ramesh P. Singh ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Time Window ◽  
Absolute Error ◽  
Absolute Difference ◽  
Ganga Basin ◽  
Monsoon Period ◽  
Post Monsoon ◽  
Dust Loading ◽  
The Absolute

Abstract. The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS Terra measures global aerosol optical depth and optical properties since 2000. MODIS aerosol products are freely available and are being used for numerous studies. In this paper, we present a comparison of aerosol optical depth (AOD) retrieved from MODIS with Aerosol Robotic Network (AERONET) data for the year 2004 over Kanpur, an industrial city lying in the Ganga Basin in the northern part of India. AOD retrieved from MODIS (τaMODIS) at 0.55µm wavelength has been compared with the AERONET derived AOD (τaAERONET), within an optimum space-time window. Although the correlation between τaMODIS and τaAERONET during the post-monsoon and winter seasons (R2~0.71) is almost equal to that during the pre-monsoon and monsoon seasons (R2~0.72), MODIS is found to overestimate AOD during the pre-monsoon and monsoon period (characterized by severe dust loading) and underestimate during the post-monsoon and winter seasons. The absolute difference between τaMODIS and τaAERONET is found to be low (0.12±0.11) during the non-dust loading season and much higher (0.4±0.2) during dust-loading seasons. The absolute error in τaMODIS is found to be about ~25% of the absolute values of τaMODIS. Our comparison shows the importance of modifying the existing MODIS algorithm during the dust-loading seasons, especially in the Ganga Basin in northern part of India.

Sign in / Sign up

Export Citation Format

Share Document