The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm
Abstract
:1. Introduction
2. Data
2.1. Land Cover Classification Data
2.2. AI-Based AOD
2.3. Other Satellite-Based AOD Data
2.4. In Situ Data
3. Comparison with In Situ Measurements
4. The Effect of AOD Estimate on Atmospheric Correction
4.1. Satellite-Based AOD
4.2. In Situ AOD
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
AOD | Aerosol Optical Depth |
AI | Aerosol Index |
SZA | Solar Zenith Angle |
TOA | Top Of Atmosphere |
constructed AOD time series 1982–2014 | |
AOD retrieved from MODIS observations | |
AOD retrieved from MISR observations | |
AOD retrieved from SeaWIFS observations | |
the mean value of calculated AOD values (from AERONET data) at 550 nm | |
corresponds to the used AOD information | |
R[] | a surface reflectance values calculated using SMAC |
SMAC | a Simplified Method for Atmospheric Correction algorithm |
DJF | December–January–February |
MAM | March–April–May |
JJA | June–July–August |
SON | September–October–November |
CLARA-Ax SAL | the Surface ALbedo from the CMSAF cLoud, Albedo and RAdiation data record, version x |
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Satellite | Product | Version | Period | L3 Resolution | |
---|---|---|---|---|---|
AOD | |||||
- | - | v1.0 | January 1982–December 2014 | 0.25 0.25 | |
MISR | Terra | MIL3DAE | V4 | February 2000–December 2014 | 0.50 0.50 |
MODIS | Aqua | MYD08 | 006 | January 2005–December 2014 | 1.00 1.00 |
SeaWIFS | SeaStar | SWDB_L305 | v004 | September 1997–December 2010 | 0.50 0.50 |
AERONET | - | - | v3 | 1999–2014 | - |
LUC | |||||
AVHRR | - | UMD Global Land | - | 1981–1994 | 1.00 1.00 |
Cover Classification | |||||
VEGETATION | SPOT 4 | GLC2000 | - | 2000 | 0.01 0.01 |
Name | (Lat, Long) | LUC | Period | |
---|---|---|---|---|
W | GSFC | (38.99, −76.83) | wooded grassland | 1999–2014 |
MD Science Center | (37.94, −75.48) | mixed coniferous forest and woodland | 1999–2014 | |
Wallops | (39.28, −76.62) | wooded grassland | 1999–2014 | |
W | Alta Floresta | (−9.87, −56.10) | broadleaf evergreen forest | 1999–2013 |
Rio Branco | (−9.96, −67.87) | broadleaf evergreen forest | 2000–2013 | |
W | Dunkerque | (51.04, 2.37) | cultivated crops | 2003–2014 |
Lille | (50.61, 3.14) | wooded grassland | 1999–2014 | |
Oostende | (51.23, 2.93) | cultivated crops | 2001–2014 | |
W | Agoufou | (15.35, −1.48) | grassland | 2002–2011 |
Banizoumbou | (13.54, 2.66) | shrubs and bare ground | 1999–2011 | |
IER Cinzana | (13.28, −5.93) | grassland | 2004–2011 | |
W | Beijing | (39.98, 116.38) | broadleaf decidious forest and woodland | 2001–2014 |
XiangHe | (39.75, 116.96) | broadleaf decidious forest and woodland | 2001, 2004–2014 |
– | – | – | – | |
---|---|---|---|---|
W | 0.00 | 0.03 | 0.00 | −0.02 |
W | 0.15 | 0.06 | 0.06 | −0.02 |
W | 0.05 | 0.03 | 0.03 | 0.00 |
W | −0.08 | −0.01 | −0.02 | −0.04 |
W | −0.22 | −0.06 | −0.39 | −0.35 |
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Jääskeläinen, E.; Manninen, T.; Tamminen, J.; Laine, M. The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm. Remote Sens. 2017, 9, 1095. https://doi.org/10.3390/rs9111095
Jääskeläinen E, Manninen T, Tamminen J, Laine M. The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm. Remote Sensing. 2017; 9(11):1095. https://doi.org/10.3390/rs9111095
Chicago/Turabian StyleJääskeläinen, Emmihenna, Terhikki Manninen, Johanna Tamminen, and Marko Laine. 2017. "The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm" Remote Sensing 9, no. 11: 1095. https://doi.org/10.3390/rs9111095