Effect of Atmospheric Corrections on NDVI: Intercomparability of Landsat 8, Sentinel-2, and UAV Sensors
"> Figure 1
<p>Location and detail of the study area. Three landscape types are distinguished by colour. The map corresponds to WGS 1984 Web Mercator Auxiliary Sphere projection.</p> "> Figure 2
<p>Spectral response functions of RED and NIR bands of sensors used and atmosphere transmittance. Sources: ESA [<a href="#B30-remotesensing-13-03550" class="html-bibr">30</a>], NASA [<a href="#B31-remotesensing-13-03550" class="html-bibr">31</a>], User Manual multiSPEC 4C camera [<a href="#B32-remotesensing-13-03550" class="html-bibr">32</a>], and Modtran [<a href="#B33-remotesensing-13-03550" class="html-bibr">33</a>].</p> "> Figure 3
<p>Histogram with highlighted median values of non-corrected TOA and corrected BOA (Level-2, QUAC, FLAASH, ACOLITE, 6S, DOS1, Sen2Cor) bands for NDVI over the study area.</p> "> Figure 4
<p>Comparison of different atmospheric corrections and visualisation of resulting histogram changes for each method. The vertical line indicates the median.</p> "> Figure 5
<p>Comparison of NDVI values for three landscape types calculated after using various methods for correcting atmospheric effect on surface NDVI and when using Landsat 8 and Sentinel-2 satellite images. Horizontal lines representing median, 25th, and 75th percentiles, dots are outliers (further than 1.5 times the IQR from 1Q and 3Q, respectively), and whiskers symbolise minimum and maximum without outliers.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Site
2.2. Geospatial Imagery Data
2.2.1. Satellite Imagery Collection
2.2.2. UAV-Borne Data Acquisition and Processing
2.3. Atmospheric Correction Algorithms
2.3.1. Quick Atmospheric Correction (QUAC)
2.3.2. Dark Object Subtraction 1 (DOS)
2.3.3. Atmospheric Correction for OLI ‘lite’ (ACOLITE)
2.3.4. Fast Line-of-Sight Atmospheric Analysis of Hypercubes (FLAASH)
2.3.5. Second Simulation of Satellite Signal in the Solar Spectrum (6S)
2.3.6. Sen2Cor
2.4. Data Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Landsat 8 | UAV | TOA | DOS1 | 6S | ACOLITE | FLAASH | QUAC | Level2 | |
---|---|---|---|---|---|---|---|---|---|
UAV | 0.8878 | 0.8821 | 0.8901 | 0.8906 | 0.8909 | 0.8904 | 0.8882 | ||
TOA | 0.8878 | 0.9807 | 0.9887 | 0.9903 | 0.9915 | 0.9889 | 0.9875 | ||
DOS1 | 0.8821 | 0.9807 | 0.9963 | 0.9959 | 0.9955 | 0.9966 | 0.9959 | ||
6S | 0.8901 | 0.9887 | 0.9963 | 0.9999 | 0.9997 | 0.9998 | 0.9992 | ||
ACOLITE | 0.8906 | 0.9903 | 0.9959 | 0.9999 | 0.9999 | 0.9998 | 0.9993 | ||
FLAASH | 0.8909 | 0.9915 | 0.9955 | 0.9997 | 0.9999 | 0.9996 | 0.9993 | ||
QUAC | 0.8904 | 0.9889 | 0.9966 | 0.9998 | 0.9998 | 0.9996 | 0.9989 | ||
Level2 | 0.8882 | 0.9875 | 0.9959 | 0.9992 | 0.9993 | 0.9993 | 0.9989 | ||
Sentinel-2 | UAV | TOA | DOS1 | 6S | ACOLITE | FLAASH | QUAC | Level2 | Sen2Cor |
UAV | 0.8994 | 0.8991 | 0.8988 | 0.8993 | 0.8996 | 0.8988 | 0.8990 | 0.8993 | |
TOA | 0.8994 | 0.9985 | 0.9982 | 0.9992 | 0.9995 | 0.9978 | 0.9982 | 0.9988 | |
DOS1 | 0.8991 | 0.9985 | 0.9995 | 0.9995 | 0.9996 | 0.9996 | 0.9991 | 1.0000 | |
6S | 0.8988 | 0.9982 | 0.9995 | 0.9998 | 0.9996 | 0.9994 | 0.9996 | 0.9995 | |
ACOLITE | 0.8993 | 0.9992 | 0.9995 | 0.9998 | 0.9999 | 0.9993 | 0.9995 | 0.9996 | |
FLAASH | 0.8996 | 0.9995 | 0.9996 | 0.9996 | 0.9999 | 0.9991 | 0.9995 | 0.9997 | |
QUAC | 0.8988 | 0.9978 | 0.9996 | 0.9994 | 0.9993 | 0.9991 | 0.9990 | 0.9996 | |
Level2 | 0.8990 | 0.9982 | 0.9991 | 0.9996 | 0.9995 | 0.9995 | 0.9990 | 0.9992 | |
Sen2Cor | 0.8993 | 0.9988 | 1.0000 | 0.9995 | 0.9996 | 0.9997 | 0.9996 | 0.9992 |
Appendix B
Landsat 8 | TOA | Level2 | QUAC | FLAASH | ACOLITE | 6S | |
---|---|---|---|---|---|---|---|
Level2 | <0.001 | ||||||
QUAC | <0.001 | <0.001 | |||||
FLAASH | <0.001 | 0.098 | <0.001 | ||||
ACOLITE | <0.001 | 1.000 | <0.001 | <0.001 | |||
6S | <0.001 | 0.069 | <0.001 | <0.001 | <0.001 | ||
DOS1 | <0.001 | 0.002 | <0.001 | <0.001 | <0.001 | 1.000 | |
Sentinel-2 | TOA | Level2 | QUAC | FLAASH | ACOLITE | 6S | DOS1 |
Level2 | <0.001 | ||||||
QUAC | <0.001 | <0.001 | |||||
FLAASH | <0.001 | <0.001 | <0.001 | ||||
ACOLITE | <0.001 | 0.610 | <0.001 | <0.001 | |||
6S | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | ||
DOS1 | <0.001 | 1.000 | <0.001 | <0.001 | <0.001 | <0.001 | |
Sen2Cor | <0.001 | <0.001 | <0.001 | <0.001 | 0.010 | <0.001 | 1.000 |
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Landsat 8 | Sentinel-2 | Difference | ||||
---|---|---|---|---|---|---|
Median | IQR | Median | IQR | Median | IQR | |
TOA | 0.334 | 0.148 | 0.468 | 0.279 | −0.133 | −0.130 |
Level2 | 0.584 | 0.216 | 0.534 | 0.363 | 0.049 | −0.147 |
QUAC | 0.717 | 0.176 | 0.635 | 0.277 | 0.082 | −0.101 |
FLAASH | 0.564 | 0.270 | 0.551 | 0.329 | 0.013 | −0.060 |
ACOLITE | 0.573 | 0.236 | 0.530 | 0.296 | 0.043 | −0.060 |
6S | 0.583 | 0.246 | 0.563 | 0.303 | 0.019 | −0.057 |
DOS1 | 0.579 | 0.224 | 0.525 | 0.302 | 0.055 | −0.078 |
UAV | 0.784 | 0.193 | 0.782 | 0.229 | ||
Sen2Cor | 0.529 | 0.355 |
DOS1 | 6S | ACOLITE | FLAASH | QUAC | Level2 | TOA | Ʃ | |
---|---|---|---|---|---|---|---|---|
Rural | 0.045 | 0.017 | 0.043 | 0.014 | 0.067 | 0.013 | −0.167 | 0.031 |
Urban | 0.097 | 0.058 | 0.074 | 0.046 | 0.150 | 0.146 | −0.037 | 0.535 |
Vegetated | 0.073 | 0.046 | 0.069 | 0.049 | 0.087 | 0.040 | −0.142 | 0.223 |
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Moravec, D.; Komárek, J.; López-Cuervo Medina, S.; Molina, I. Effect of Atmospheric Corrections on NDVI: Intercomparability of Landsat 8, Sentinel-2, and UAV Sensors. Remote Sens. 2021, 13, 3550. https://doi.org/10.3390/rs13183550
Moravec D, Komárek J, López-Cuervo Medina S, Molina I. Effect of Atmospheric Corrections on NDVI: Intercomparability of Landsat 8, Sentinel-2, and UAV Sensors. Remote Sensing. 2021; 13(18):3550. https://doi.org/10.3390/rs13183550
Chicago/Turabian StyleMoravec, David, Jan Komárek, Serafín López-Cuervo Medina, and Iñigo Molina. 2021. "Effect of Atmospheric Corrections on NDVI: Intercomparability of Landsat 8, Sentinel-2, and UAV Sensors" Remote Sensing 13, no. 18: 3550. https://doi.org/10.3390/rs13183550
APA StyleMoravec, D., Komárek, J., López-Cuervo Medina, S., & Molina, I. (2021). Effect of Atmospheric Corrections on NDVI: Intercomparability of Landsat 8, Sentinel-2, and UAV Sensors. Remote Sensing, 13(18), 3550. https://doi.org/10.3390/rs13183550