Retrieval of aerosol optical depth and surface reflectance over land from NOAA AVHRR data

Author(s): Li, YJ (Li, Yingjie)[ 1,2,9,10 ] ; Xue, Y (Xue, Yong)[ 1,2,3 ] ; de Leeuw, G (de Leeuw, Gerrit)[ 4,5,6 ] ; Li, C (Li, Chi)[ 7,9 ] ; Yang, LK (Yang, Leiku)[ 8 ] ; Hou, TT (Hou, Tingting)[ 7,9 ] ; Marir, F (Marir, Farhi)[ 3 ]

Source: REMOTE SENSING OF ENVIRONMENT  Volume: 133   Pages: 1-20   DOI: 10.1016/j.rse.2013.01.020   Published: JUN 15 2013

Times Cited: 0 (from Web of Science)

Cited References: 67      [ view related records ]     Citation Map    

Abstract: An algorithm for the land aerosol and bidirectional reflectance inversion by times series technique (LABITS) is proposed and applied to data from the National Oceanic and Atmospheric Administration (NOAA) advanced very high resolution radiometer (AVHRR). The surface reflectance and aerosol optical depth are inverted from AVHRR Channel 1 data using a model for the earth-atmosphere system which couples an atmospheric radiative transfer model with the Ross-Thick-Li-sparse bidirectional reflectance factor (BRF) model. Basic assumptions are that the surface bidirectional reflective property does not vary over a 2-4 day periods and that the aerosol characteristics are uniform within a 0.1 degrees x 0.1 degrees window (approximately 10 km x 10 km). The LABITS algorithm is applied to data from AVHRR on the NOAA-15, NOAA-16, and NOAA-18 satellites over four distinct areas, namely, North America, Europe, the Sahara and India, to simultaneously retrieve the aerosol optical depth (AOD), BRF parameters and surface albedo. Preliminary results show that AOD and reflectance retrieved from the three different instruments are in good agreement and that LABITS provides good results over both bright surfaces, e.g. the Sahara, and dark surfaces, e.g. Europe. Evaluation of the AOD versus data from the Aerosol Robotic Network (AERONET) provides a correlation coefficient R-2 of 0.88 and a root-mean-square error (RMSE) of approximately 0.07; and the uncertainty is approximately Delta tau= +/- 0.05 +/- 0.20 tau. Comparing our results with the moderate resolution imaging spectroradiometer (MODIS) AOD products, over many areas, provides biases in the range of +/- 0.05. The surface albedo values calculated from the retrieved BRF parameters are similar to those provided by the MODIS albedo product (MCD43). The robustness and applicability of the LABITS algorithm are demonstrated with the retrieval of AOD over China during August 2008. Daily and monthly averaged results show good agreement with collocated AERONET observations and AQUA MODIS products (MYD04 and MYD08). The AOD uncertainty is estimated as Delta tau = +/- 10.05 +/- 030 tau. The preliminary analysis of time series over selected AERONET sites shows that the temporal variations of the AOD values retrieved by application of LABITS to AVHRR data are overall similar to temporal variations of AOD provided by the MODIS and AERONET. The algorithm has the potential to retrieve global AOD over land for long time series of NOAA AVHRR data going back to the 1980s, which are urgently needed for studies on aerosol climatology and global climate change. (c) 2013 Elsevier Inc. All rights reserved.

Accession Number: WOS:000317942100001

Document Type: Article

Language: English

Author Keywords: AVHRR; Aerosol; Optical depth; Bidirectional reflectance; Albedo; Time series

KeyWords Plus: HIGH-RESOLUTION RADIOMETER; BIDIRECTIONAL REFLECTANCE; RADIATIVE-TRANSFER; ATMOSPHERIC CORRECTION; SOLAR-RADIATION; EARTHS SURFACE; MODEL; ALGORITHM; THICKNESS; MODIS

Reprint Address: Xue, Y (reprint author)

         London Metropolitan Univ, Fac Life Sci & Comp, London N7 8DB, England.

Addresses:

         [ 1 ] Chinese Acad Sci, Inst Remote Sensing Applicat, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

         [ 2 ] Beijing Normal Univ, Beijing 100101, Peoples R China

         [ 3 ] London Metropolitan Univ, Fac Life Sci & Comp, London N7 8DB, England

         [ 4 ] Univ Helsinki, Dept Phys, Helsinki, Finland

          [ 5 ] Finnish Meteorol Inst, Climate Change Unit, FIN-00101 Helsinki, Finland

          [ 6 ] Netherlands Org Appl Sci Res TNO, Utrecht, Netherlands

         [ 7 ] Chinese Acad Sci, Ctr Earth Observat & Digital Earth, Beijing 100094, Peoples R China

         [ 8 ] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China

          [ 9 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

         [ 10 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China

E-mail Addresses: y.xue@londonmet.ac.uk