Comparison of Cloud Cover Detection Algorithms on Sentinel–2 Images of the Amazon Tropical Forest
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Selection
- T19LFK:
- Covers part of the states of Acre and Amazonas, including an indigenous land (Terra Indígena Apurianã) and a protected area (Reserva Extrativista Chico Mendes). The region is associated with significant recent deforestation.
- T20NPH:
- This area is in the state of Roraima and it partially covers a national forest (Floresta Nacional de Roraima) and an indigenous land (Terra Indígena Yanomami).
- T21LXH:
- This area covers part of the state of Mato Grosso; it includes fragmented forest areas, soybean crops, pasture, and water reservoirs.
- T22MCA:
- In the state of Para, this area overlaps various indigenous reserves (Arara, Araweté, Kararaô, Koatinemo, and Trincheira) and part of a conservation unit; most of the area is covered by native forest with some deforested areas to the North.
- T22NCG:
- This area is in the state of Amapá, including part of a National Forest (Amapá), a national park (Montanhas do Tumucumaque), and an indigenous land (Waiãpi).
2.3. Cloud Detection Algorithms
2.4. Algorithm Configuration
- Fmask 4:
- Dilation parameters for cloud, cloud shadows, and snow were set to 3, 3, and 0 pixels, respectively. The cloud probability threshold was 20%, following Qiu et al. [47].
- S2cloudless:
- Cloud probability threshold was set to 70%, using a four-pixel convolution for averaging cloud probabilities and dilation of two pixels, following the parameters set by Zupanc et al. [27].
- Sen2Cor 2.8:
- The tests used the same configuration as that of the Land Cover maps of ESA’s Climate Change Initiative (http://maps.elie.ucl.ac.be/CCI/viewer/download.php).
- MAJA:
- The evaluation used the same configuration as that of the Sen2Agri application (http://www.esa-sen2agri.org).
2.5. Validation Sample Set
2.6. Label Compatibility
2.7. Validation Metrics
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Band | Resolution (m) | Wavelength (nm) | Revisit Period (Days) |
---|---|---|---|
B01 Coastal aerosol | 60 | 443 | 10 |
B02 Blue | 10 | 490 | 10 |
B03 Green | 10 | 560 | 10 |
B04 Red | 10 | 665 | 10 |
B05 Vegetation red edge | 20 | 705 | 10 |
B06 Vegetation red edge | 20 | 740 | 10 |
B07 Vegetation red edge | 20 | 783 | 10 |
B08 NIR | 10 | 842 | 10 |
B8A Vegetation red edge | 20 | 865 | 10 |
B09 Water vapour | 60 | 945 | 10 |
B10 SWIR - Cirrus | 60 | 1375 | 10 |
B11 SWIR | 20 | 1610 | 10 |
B12 SWIR | 20 | 2190 | 10 |
Tile | Date | Samples |
---|---|---|
T19LFK | 4 October 2016 | 382 |
T19LFK | 2 January 2017 | 437 |
T19LFK | 7 May 2018 | 392 |
T19LFK | 3 November 2018 | 452 |
T20NPH | 1 September 2016 | 326 |
T20NPH | 10 November 2016 | 246 |
T20NPH | 18 February 2017 | 353 |
T20NPH | 18 July 2017 | 311 |
T21LXH | 28 March 2017 | 496 |
T21LXH | 11 June 2018 | 474 |
T21LXH | 19 September 2018 | 436 |
T21LXH | 9 October 2018 | 457 |
T22MCA | 3 June 2017 | 368 |
T22MCA | 23 June 2017 | 404 |
T22MCA | 19 April 2018 | 445 |
T22MCA | 28 June 2018 | 447 |
T22NCG | 29 September 2016 | 464 |
T22NCG | 19 October 2016 | 426 |
T22NCG | 27 May 2017 | 346 |
T22NCG | 6 July 2017 | 433 |
Expert label | Fmask4 | MAJA | s2cloudless | Sen2Cor |
---|---|---|---|---|
Clear | 0 Clear land | 0–1 Clear | 0 Clear | 4 Vegetation |
1 Clear water | 5 Non vegetated | |||
3 Snow | 6 Water | |||
11 Snow | ||||
Cloud | 4 Cloud | 2–3 Cloud | 1 Cloud | 8 Cloud medium probability |
6–7 Cloud | 9 Cloud high probability | |||
10–11 Cloud | 10 Thins cirrus | |||
14–63 Cloud | ||||
64–127 Cirrus | ||||
128–191 Cloud | ||||
192–255 Cirrus | ||||
Cloud shadow | 2 Cloud shadow | 4–5 Cloud shadow | 2 Dark area pixels | |
8–9 Cloud shadow | 3 Cloud shadows | |||
12–13 Cloud shadow | ||||
Other | 0 No data | |||
1 Saturated or defective | ||||
7 Unclassified |
Fmask 4 | MAJA | s2cloudless | Sen2Cor | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Label | F1 | User | Prod | F1 | User | Prod | F1 | User | Prod | F1 | User | Prod |
Clear | 0.90 | 0.90 | 0.89 | 0.73 | 0.82 | 0.66 | 0.44 | 0.42 | 0.46 | 0.77 | 0.67 | 0.89 |
Cloud | 0.94 | 0.91 | 0.96 | 0.77 | 0.64 | 0.97 | 0.66 | 0.59 | 0.75 | 0.89 | 0.90 | 0.88 |
C. Shadow | 0.79 | 0.84 | 0.75 | 0.00 | 0.00 | 0.50 | 0.95 | 0.34 | ||||
Overall | 0.90 | 0.69 | 0.52 | 0.79 |
Fmask 4 | MAJA | s2cloudless | Sen2Cor | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Tile | Label | F1 | User | Prod | F1 | User | Prod | F1 | User | Prod | F1 | User | Prod |
T19LFK | Clear | 0.83 | 0.81 | 0.86 | 0.66 | 0.69 | 0.63 | 0.47 | 0.31 | 0.94 | 0.66 | 0.52 | 0.92 |
Cloud | 0.96 | 0.96 | 0.96 | 0.90 | 0.85 | 0.97 | 0.77 | 0.94 | 0.66 | 0.94 | 0.96 | 0.92 | |
C. Shadow | 0.68 | 0.71 | 0.66 | 0.00 | 0.00 | 0.00 | |||||||
Overall | 0.92 | 0.82 | 0.64 | 0.84 | |||||||||
T20NPH | Clear | 0.91 | 0.95 | 0.88 | 0.78 | 0.89 | 0.70 | 0.53 | 0.47 | 0.62 | 0.84 | 0.73 | 1.00 |
Cloud | 0.95 | 0.90 | 1.00 | 0.71 | 0.56 | 0.98 | 0.57 | 0.54 | 0.60 | 0.93 | 0.99 | 0.88 | |
C. Shadow | 0.80 | 0.82 | 0.78 | 0.00 | 0.00 | 0.59 | 1.00 | 0.42 | |||||
Overall | 0.91 | 0.67 | 0.50 | 0.84 | |||||||||
T21LXH | Clear | 0.88 | 0.82 | 0.95 | 0.80 | 0.89 | 0.72 | 0.35 | 0.33 | 0.36 | 0.78 | 0.64 | 0.99 |
Cloud | 0.94 | 0.96 | 0.92 | 0.77 | 0.64 | 0.98 | 0.60 | 0.52 | 0.70 | 0.91 | 0.99 | 0.83 | |
C. Shadow | 0.81 | 0.89 | 0.75 | 0.00 | 0.00 | 0.58 | 0.98 | 0.41 | |||||
Overall | 0.90 | 0.71 | 0.45 | 0.81 | |||||||||
T22MCA | Clear | 0.94 | 0.94 | 0.94 | 0.88 | 0.83 | 0.93 | 0.58 | 0.62 | 0.54 | 0.85 | 0.74 | 0.98 |
Cloud | 0.94 | 0.90 | 0.98 | 0.82 | 0.71 | 0.97 | 0.70 | 0.56 | 0.93 | 0.95 | 1.00 | 0.90 | |
C. Shadow | 0.81 | 0.89 | 0.74 | 0.00 | 0.00 | 0.49 | 0.87 | 0.34 | |||||
Overall | 0.92 | 0.77 | 0.58 | 0.83 | |||||||||
T22NCG | Clear | 0.87 | 0.95 | 0.80 | 0.42 | 0.70 | 0.30 | 0.23 | 0.34 | 0.18 | 0.63 | 0.64 | 0.63 |
Cloud | 0.87 | 0.79 | 0.96 | 0.58 | 0.43 | 0.92 | 0.61 | 0.46 | 0.94 | 0.71 | 0.62 | 0.83 | |
C. Shadow | 0.80 | 0.82 | 0.77 | 0.00 | 0.00 | 0.53 | 0.97 | 0.36 | |||||
Overall | 0.86 | 0.48 | 0.43 | 0.65 |
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Sanchez, A.H.; Picoli, M.C.A.; Camara, G.; Andrade, P.R.; Chaves, M.E.D.; Lechler, S.; Soares, A.R.; Marujo, R.F.B.; Simões, R.E.O.; Ferreira, K.R.; et al. Comparison of Cloud Cover Detection Algorithms on Sentinel–2 Images of the Amazon Tropical Forest. Remote Sens. 2020, 12, 1284. https://doi.org/10.3390/rs12081284
Sanchez AH, Picoli MCA, Camara G, Andrade PR, Chaves MED, Lechler S, Soares AR, Marujo RFB, Simões REO, Ferreira KR, et al. Comparison of Cloud Cover Detection Algorithms on Sentinel–2 Images of the Amazon Tropical Forest. Remote Sensing. 2020; 12(8):1284. https://doi.org/10.3390/rs12081284
Chicago/Turabian StyleSanchez, Alber Hamersson, Michelle Cristina A. Picoli, Gilberto Camara, Pedro R. Andrade, Michel Eustaquio D. Chaves, Sarah Lechler, Anderson R. Soares, Rennan F. B. Marujo, Rolf Ezequiel O. Simões, Karine R. Ferreira, and et al. 2020. "Comparison of Cloud Cover Detection Algorithms on Sentinel–2 Images of the Amazon Tropical Forest" Remote Sensing 12, no. 8: 1284. https://doi.org/10.3390/rs12081284
APA StyleSanchez, A. H., Picoli, M. C. A., Camara, G., Andrade, P. R., Chaves, M. E. D., Lechler, S., Soares, A. R., Marujo, R. F. B., Simões, R. E. O., Ferreira, K. R., & Queiroz, G. R. (2020). Comparison of Cloud Cover Detection Algorithms on Sentinel–2 Images of the Amazon Tropical Forest. Remote Sensing, 12(8), 1284. https://doi.org/10.3390/rs12081284