Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images
Conventional methods for Aerosol Optical Depth (AOD) retrieval are limited to areas with low reflectance such as water or vegetated areas because the satellite signals from the aerosols in these areas are more obvious than those in areas with higher reflectance such as urban and sandy areas. Land Su...
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ftdoajarticles:oai:doaj.org/article:aef2f36dbfd1438f8daae49d1da73ef1 2023-05-15T13:06:25+02:00 Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images Lin Sun Jing Wei Muhammad Bilal Xinpeng Tian Chen Jia Yamin Guo Xueting Mi 2015-12-01T00:00:00Z https://doi.org/10.3390/rs8010023 https://doaj.org/article/aef2f36dbfd1438f8daae49d1da73ef1 EN eng MDPI AG http://www.mdpi.com/2072-4292/8/1/23 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs8010023 https://doaj.org/article/aef2f36dbfd1438f8daae49d1da73ef1 Remote Sensing, Vol 8, Iss 1, p 23 (2015) AOD bright surfaces Landsat 8 OLI AERONET MOD04 Science Q article 2015 ftdoajarticles https://doi.org/10.3390/rs8010023 2022-12-31T16:10:43Z Conventional methods for Aerosol Optical Depth (AOD) retrieval are limited to areas with low reflectance such as water or vegetated areas because the satellite signals from the aerosols in these areas are more obvious than those in areas with higher reflectance such as urban and sandy areas. Land Surface Reflectance (LSR) is the key parameter that must be estimated accurately. Most current methods used to estimate AOD are applicable only in areas with low reflectance. It has historically been difficult to estimate the LSR for bright surfaces because of their complex structure and high reflectance. This paper provides a method for estimating LSR for AOD retrieval in bright areas, and the method is applied to AOD retrieval for Landsat 8 Operational Land Imager (OLI) images at 500 m spatial resolution. A LSR database was constructed with the MODerate-resolution Imaging Spectroradiometer (MODIS) surface reflectance product (MOD09A1), and this database was also used to estimate the LSR of Landsat 8 OLI images. The AOD retrieved from the Landsat 8 OLI images was validated using the AOD measurements from four AErosol RObotic NETwork (AERONET) stations located in areas with bright surfaces. The MODIS AOD product (MOD04) was also compared with the retrieved AOD. The results demonstrate that the AOD retrieved with the new algorithm is highly consistent with the AOD derived from ground measurements, and its precision is better than that of MOD04 AOD products over bright areas. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Remote Sensing 8 1 23 |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
AOD bright surfaces Landsat 8 OLI AERONET MOD04 Science Q |
spellingShingle |
AOD bright surfaces Landsat 8 OLI AERONET MOD04 Science Q Lin Sun Jing Wei Muhammad Bilal Xinpeng Tian Chen Jia Yamin Guo Xueting Mi Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images |
topic_facet |
AOD bright surfaces Landsat 8 OLI AERONET MOD04 Science Q |
description |
Conventional methods for Aerosol Optical Depth (AOD) retrieval are limited to areas with low reflectance such as water or vegetated areas because the satellite signals from the aerosols in these areas are more obvious than those in areas with higher reflectance such as urban and sandy areas. Land Surface Reflectance (LSR) is the key parameter that must be estimated accurately. Most current methods used to estimate AOD are applicable only in areas with low reflectance. It has historically been difficult to estimate the LSR for bright surfaces because of their complex structure and high reflectance. This paper provides a method for estimating LSR for AOD retrieval in bright areas, and the method is applied to AOD retrieval for Landsat 8 Operational Land Imager (OLI) images at 500 m spatial resolution. A LSR database was constructed with the MODerate-resolution Imaging Spectroradiometer (MODIS) surface reflectance product (MOD09A1), and this database was also used to estimate the LSR of Landsat 8 OLI images. The AOD retrieved from the Landsat 8 OLI images was validated using the AOD measurements from four AErosol RObotic NETwork (AERONET) stations located in areas with bright surfaces. The MODIS AOD product (MOD04) was also compared with the retrieved AOD. The results demonstrate that the AOD retrieved with the new algorithm is highly consistent with the AOD derived from ground measurements, and its precision is better than that of MOD04 AOD products over bright areas. |
format |
Article in Journal/Newspaper |
author |
Lin Sun Jing Wei Muhammad Bilal Xinpeng Tian Chen Jia Yamin Guo Xueting Mi |
author_facet |
Lin Sun Jing Wei Muhammad Bilal Xinpeng Tian Chen Jia Yamin Guo Xueting Mi |
author_sort |
Lin Sun |
title |
Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images |
title_short |
Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images |
title_full |
Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images |
title_fullStr |
Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images |
title_full_unstemmed |
Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images |
title_sort |
aerosol optical depth retrieval over bright areas using landsat 8 oli images |
publisher |
MDPI AG |
publishDate |
2015 |
url |
https://doi.org/10.3390/rs8010023 https://doaj.org/article/aef2f36dbfd1438f8daae49d1da73ef1 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing, Vol 8, Iss 1, p 23 (2015) |
op_relation |
http://www.mdpi.com/2072-4292/8/1/23 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs8010023 https://doaj.org/article/aef2f36dbfd1438f8daae49d1da73ef1 |
op_doi |
https://doi.org/10.3390/rs8010023 |
container_title |
Remote Sensing |
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8 |
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1 |
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23 |
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1766004733728784384 |