ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters

被引:184
|
作者
Pahlevan, Nima [1 ,2 ]
Mangin, Antoine [3 ]
Balasubramanian, Sundarabalan V. [4 ]
Smith, Brandon [1 ,2 ]
Alikas, Krista [5 ]
Arai, Kohei [6 ]
Barbosa, Claudio [7 ]
Belanger, Simon [8 ]
Binding, Caren [9 ]
Bresciani, Mariano [10 ]
Giardino, Claudia [10 ]
Gurlin, Daniela [11 ]
Fan, Yongzhen [12 ]
Harmel, Tristan [13 ]
Hunter, Peter [14 ]
Ishikaza, Joji [15 ]
Kratzer, Susanne [16 ]
Lehmann, Moritz K. [17 ,18 ]
Ligi, Martin [5 ]
Ma, Ronghua [19 ]
Martin-Lauzer, Francois-Regis [3 ]
Olmanson, Leif [20 ]
Oppelt, Natascha [21 ]
Pan, Yanqun [8 ,22 ]
Peters, Steef [23 ]
Reynaud, Nathalie [24 ]
de Carvalho, Lino A. Sander [25 ]
Simis, Stefan [26 ]
Spyrakos, Evangelos [14 ]
Steinmetz, Francois [27 ]
Stelzer, Kerstin [28 ]
Sterckx, Sindy [29 ]
Tormos, Thierry [30 ]
Tyler, Andrew [14 ]
Vanhellemont, Quinten [31 ]
Warren, Mark [26 ]
机构
[1] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
[2] Sci Syst & Applicat Inc SSAI, Lanham, MD USA
[3] ACRI ST, Sophia Antipolis, France
[4] Geosensing & Imaging Solut Consultancy, Trivandrum, Kerala, India
[5] Univ Tartu, Tartu Observ, Tartumaa, Estonia
[6] Saga Univ, Dept Informat Sci, Saga, Japan
[7] Natl Inst Space Res INPE, Instrumentat Lab Aquat Syst LabISA, Sao Jose Dos Campos, Brazil
[8] Univ Quebec Rimouski, Dept Biol Chim & Geog, Grp BOREAS & Quebec Ocean, Rimouski, PQ, Canada
[9] Environm & Climate Change Canada, Burlington, ON, Canada
[10] CNR IREA, Natl Res Council Italy, Inst Electromagnet Sensing Environm, Naples, Italy
[11] Wisconsin Dept Nat Resources, Madison, WI USA
[12] Stevens Inst Technol, Dept Phys & Engn Phys, Hoboken, NJ 07030 USA
[13] Geosci Environm Toulouse GET, Toulouse, France
[14] Univ Stirling, Dept Biol & Environm Sci, Earth & Planetary Observat Sci EPOS, Stirling, Scotland
[15] Nagoya Univ, Inst Space Earth Environm Res ISEE, Nagoya, Aichi, Japan
[16] Stockholm Univ, Dept Ecol Environm & Plant Sci DEEP, Stockholm, Sweden
[17] Xerra Earth Observat Inst, Alexandra, New Zealand
[18] Univ Waikato, Hamilton, New Zealand
[19] Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Watershed Geog Sci, Nanjing, Peoples R China
[20] Univ Minnesota, Dept Forest Resources, St Paul, MN USA
[21] Univ Kiel, Dept Geog, Earth Observat & Modelling, Kiel, Germany
[22] ARCTUS, Rimouski, PQ, Canada
[23] Water Insight, Wageningen, Netherlands
[24] INRAE, UR RECOVER Pole ECLA, Aix En Provence, France
[25] Fed Univ Rio de Janeiro UFRJ, Dept Meteorol, Rio De Janeiro, Brazil
[26] Plymouth Marine Lab, Plymouth, Devon, England
[27] Euratechnologies, Hygeos, Lille, France
[28] Brockmann Consult GmbH, Hamburg, Germany
[29] Flemish Inst Technol Res VITO, Remote Sensing Unit, Mol, Belgium
[30] Off Francais Biodivers OFB, Unite ECosyst LAcustres Pole ECLA, Aix En Provence, France
[31] Royal Belgian Inst Nat Sci RBINS, Operat Directorate Nat Environm, Brussels, Belgium
基金
巴西圣保罗研究基金会; 欧盟地平线“2020”; 英国自然环境研究理事会;
关键词
Landsat - Rivers - Uncertainty analysis - Optical remote sensing - Biogeochemistry - Data handling - NASA - Reservoirs (water);
D O I
10.1016/j.rse.2021.112366
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA - ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances ((rho) over cap (w)). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in (rho) over cap (w)(560) and (rho) over cap (w)(664) were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15-30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20-30% uncertainties in (rho) over cap (w)(490 <= lambda <= 743 nm) yielded 25-70% uncertainties in derived Chla and TSS products for top-performing AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems.
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页数:22
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