Long-time series aerosol optical depth retrieval from AVHRR data over land in North China and Central Europe

Xue, Yong; He, Xingwei; Leeuw, G. de; Mei, Linlu; Che, Yahui; Rippin, Wayne; Jin, Guang; Hu, Yincui

doi:10.1016/j.rse.2017.06.036

Cited by 32 publications

(31 citation statements)

References 45 publications

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“…Combined with MYD13, some areas with a high AOD have a small NDVI. These findings are similar to those obtained by previous studies (Xue et al, 2017). In addition, AVHRR AOD and MYD04 AOD apply different cloud detection algorithms, while the AVHRR data lack mature algorithms and products.…”

Section: Validation With the Modis Aerosol Productsupporting

confidence: 91%

A New Algorithm for the Aod Inversion From Noaa/Avhrr Data

Sun

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The advanced very high resolution radiometer (AVHRR) data from the National Oceanic and Atmospheric Administration satellite is one of the earliest data applied in aerosol research. The dense dark vegetation (DDV) algorithm is a popular method for the present land aerosol retrieval. One of the most crucial steps in the DDV algorithm with AVHRR data is estimating the land surface reflectance (LSR). However, LSR cannot be easily estimated because of the lack of a 2.13 μm band. In this article, the moderate resolution imaging spectroradiometer (MODIS) vegetation index product (MYD13) is introduced to support the estimation of AVHRR LSR. The relationship between MODIS NDVI and the AVHRR LSR of the visible band is analysed to retrieve aerosol optical depth (AOD) from AVHRR data. Retrieval experiments are carried out in mid-eastern America. The AOD data from AErosol RObotic NETwork (AERONET) measurements are used to evaluate the aerosol retrieval from AVHRR data, the results indicate that about 74% of the retrieved AOD are within the expected error range of ±(0.05+0.2), and a cross comparison of the AOD retrieval results with the MODIS aerosol product (MYD04) shows that the AOD datasets have a similar spatial distribution.

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Section: Validation With the Modis Aerosol Productsupporting

confidence: 91%

A New Algorithm for the Aod Inversion From Noaa/Avhrr Data

Sun

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…AODs derived from MODIS and AVHRR data are encumbered with high uncertainty, which complicates long‐term variability analysis. In the case of the MODIS Deep Blue algorithm, the uncertainty is about ±0.03 + 0.2·AOD (Sayer et al, ), while for AVHRR data for the Europe region, 75% of AOD uncertainties are within the range ±(0.05 + 15%) (Xue et al, ).…”

Section: Introductionmentioning

confidence: 99%

Long‐Term Variability of Aerosol Optical Depth in the Tatra Mountain Region of Central Europe

et al. 2019

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This paper presents the results of long‐term observations (1964–2010) of direct solar flux at two stations in the Tatra Mountains in Poland (Central Europe). The measurements obtained from a Linke‐Feussner actinometers are used to estimate broadband (0.29–2.9 μm) and wideband (0.53–0.63 μm) aerosol optical depth (BAOD and WAOD, respectively). Both BAOD and WAOD at Mount Kasprowy Wierch (1,991 m a.s.l.) and in Zakopane (851 m a.s.l.) show similar annual cycles with peaks during spring and summer. Coincidence of actinometer observation at the top of the Tatra Mountains and in Zakopane valley allows determination of AOD in the column between 851 and 1,991 m a.s.l. Annual variabilities of both BAOD and WAOD for this layer are similar to PM10 concentration measurements in Zakopane. Conversely, BAOD and WAOD obtained at both stations show opposing annual variability, which is consistent with the Aerosol Robotic Network and model results in Central Europe. Long‐term data show significant reduction of both BAOD and WAOD in Zakopane (−0.018 ± 0.003 and −0.023 ± 0.003, respectively, per decade) and lower reductions at Mt. Kasprowy Wierch (−0.005 ± 0.002 and −0.009 ± 0.002, respectively, per decade). Trends for BAOD and WAOD defined between 851 and 1,991 m a.s.l. are the same (−0.013 ± 0.004 per decade), which corresponds to the reduction of WAOD and BAOD by about 60% between 1964 and 2010. Conversely, emission data for the Zakopane region obtained from Emissions Database for Global Atmospheric Research inventories shows reduction of SO2 by a factor of 3 and of NOx and PM10 by about 40% between 1988 and 2010.

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“…With almost the same historical span, the advanced very high resolution radiometers (AVHRRs) provide decades of daily observations. The high frequency leads to increased probability of cloud free observations, and via composting method yields near-seamless data records in support of global change studies [3,8,9]. However, AVHRRs lack onboard calibration Both sensors have their advantages and disadvantages.…”

Section: Introductionmentioning

confidence: 97%

Using a MODIS Index to Quantify MODIS-AVHRRs Spectral Differences in the Visible Band

Fan

Liu

2018

Remote Sensing

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Spectral band differences are a critical issue for progressing into an integrated earth observation framework and in particular, in sensor intercalibration. The differences are currently normalized using spectral band adjustment factor (SBAF) that is generated from hyperspectral data. In this context, the current study proposes a method for calculating moderate-resolution imaging spectroradiometer (MODIS)-advanced very high resolution radiometers (AVHRRs) SBAF in the visible band, using the MODIS surface reflectance data. The method involves a uniform ratio index calculated using the MODIS 552-nm and 645-nm bands, and a sensor-specific quadratic equation, producing SBAF data at 500-m spatial resolution. The calculated SBAFs are in good agreement at site scale with literature reported data (relative error < 1.0%), and at local scale with Hyperion-derived data (total uncertainty ≈ 0.001), and significantly improve MODIS-AVHRR surface reflectance data consistency in the visible band (better than 1.0% reflectance units). The calculation is more sensitive to atmospheric effects over the vegetated areas. At global scale, MODIS-AVHRRs SBAFs are generally large (>1.0) over densely vegetated areas and extremely low over deserts and barren lands (0.96-0.98), indicative of large MODIS-AVHRRs differences. Deserts show temporally stable SBAF values, while still suffer from intra-annual BRDF effects and short-term cloud contamination. By means of daily MODIS data, the proposed method can produce ongoing SBAF data at a spatial scale that is comparable to AVHRRs. It increases the sampling of MODIS-AVHRRs image pairs for intercalibration, and offers insight into spectral band conversion, finally contributing to an integrated earth observation at moderate spatial resolutions.

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Long-time series aerosol optical depth retrieval from AVHRR data over land in North China and Central Europe

Cited by 32 publications

References 45 publications

A New Algorithm for the Aod Inversion From Noaa/Avhrr Data

A New Algorithm for the Aod Inversion From Noaa/Avhrr Data

Long‐Term Variability of Aerosol Optical Depth in the Tatra Mountain Region of Central Europe

Using a MODIS Index to Quantify MODIS-AVHRRs Spectral Differences in the Visible Band

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