Geocorrection of Airborne Mid-Wave Infrared Imagery for Mapping Wildfires without GPS or IMU
<p>(<b>A</b>) Sioux Lookout (SLK-37) site located near Pickle Lake, Northern Ontario, Canada. FLIR MWIR data was recorded twice in successive alternating directions over eight flight lines between 2 August and 3 August 2017. (<b>B</b>) Photograph taken over the study area acquired on 3 August 2017, at 11:27 (EST). (<b>C</b>) Boundaries of the five selected flight lines (i.e., FL-02 to FL-06) for data analysis.</p> "> Figure 2
<p>Workflow representation of the adjusted data and processing steps to compute GPS-tagged orthoimages of FLIR airborne data.</p> "> Figure 3
<p>Calculation for the horizontal (H<sub>FoV</sub>) and vertical (V<sub>FoV</sub>) field of view (FoV) with respect to the sensor (S) and the aircraft-ground separation below the central pixel (Z<sub>center</sub>).</p> "> Figure 4
<p>The initial pixel position assignment (x<sub>pos,0</sub>, y<sub>pos,0</sub>), shown in the dashed-line box. The post-rotation position (x<sub>pos</sub>, y<sub>pos</sub>) is shown in the solid-line box. H<sub>FoV</sub> and V<sub>FoV</sub> are the horizontal and vertical dimensions.</p> "> Figure 5
<p>An outline of the general image registration process on an idealized feature (red line). Note that the spacing between the frames in the far right set have been exaggerated for clarity, and the middle pair of frames are more indicative of the usual spatial shift from frame to frame. f<sub>r</sub> is the moving frame’s registered coordinates, f<sub>f</sub> is the fixed frame’s coordinates, t<sub>x</sub> is the translation in the x direction, and t<sub>y</sub> is the translation in the y direction.</p> "> Figure 6
<p>An exaggerated example of the gridding process on an idealized feature (red line). The dashed gray lines indicate the grid of cells. The left grids show the before and after representation of imagery during the gridding process. The three frames on the top right exemplify the process of determining what value should be in the final cell. Example shown for a 1 m pixel size.</p> "> Figure 7
<p>Workflow displaying the georeferencing methodology developed to reduce the geolocation error of the acquired FLIR data.</p> "> Figure 8
<p>Relationship between counts recorded by the FLIR sensor and calculated radiance using the Planck function and a wavelength of 3.74 µm at integration times of (<b>A</b>) 1.4 ms, (<b>B</b>) 0.3 ms, (<b>C</b>) 0.04 ms, and (<b>D</b>) 0.0021 ms modified from [<a href="#B36-sensors-21-03047" class="html-bibr">36</a>]. The equations yielded by the trend line at each integration time were used to calculate radiance across each frame recorded by the sensor.</p> "> Figure 9
<p>A histogram of the FLIR data in Radiance (Wm<sup>−2</sup> sr<sup>−1</sup> µm<sup>−1</sup>). The distribution of count values remains very similar through the geocorrection process, even though the amount of data has been greatly reduced.</p> "> Figure 10
<p>(<b>A</b>) An example of reported RMSE of the orthoimage (before the georeferencing process) in units of radiance (Wm<sup>−2</sup> sr<sup>−1</sup> µm<sup>−1</sup>) of FL-04, at an integration time of 1.4 ms, from F-04 acquired on 3 August 2017. Areas showing the misalignments and RMSE found following the geocorrection process for (<b>B</b>) the northwest and (<b>C</b>) southeast corners of the flight line.</p> "> Figure 11
<p>(<b>A</b>) Reported RMSE following the georeferencing process of the FLIR imagery in units of Radiance (Wm<sup>−2</sup> sr<sup>−1</sup> µm<sup>−1</sup>) acquired on 3 August 2017, F-04, at the 1.4 ms integration time. Areas showing RMSE following the georeferencing process for (<b>B</b>) the northwest and (<b>C</b>) southeast corners of the flight lines.</p> "> Figure 12
<p>Radiance (Wm<sup>−2</sup> sr<sup>−1</sup> µm<sup>−1</sup>) captured during the nighttime flight, F-03, acquired on 2 August 2017, over four different area (<b>A</b>–<b>D</b>) of the SLK-37 site. Radiance of the 1.4 ms, 0.3 ms, 0.04 ms, and 0.0021 ms integration times superimposed based on the set thresholds (<a href="#sec3dot3-sensors-21-03047" class="html-sec">Section 3.3</a>). Radiance below 1 Wm<sup>−2</sup> sr<sup>−1</sup> µm<sup>−1</sup> (white) not displayed.</p> "> Figure 13
<p>Radiance (Wm<sup>−2</sup> sr<sup>−1</sup> µm<sup>−1</sup>) captured during the nighttime flight, F-04, acquired on 3 August 2017, over four different area (<b>A</b>–<b>D</b>) of the SLK-37 site. Radiance of the 1.4 ms, 0.3 ms, 0.04 ms, and 0.0021 ms integration times superimposed based on the set thresholds (<a href="#sec3dot3-sensors-21-03047" class="html-sec">Section 3.3</a>). Radiance below 1 Wm<sup>−2</sup> sr<sup>−1</sup> µm<sup>−1</sup> (white) not displayed.</p> "> Figure 14
<p>Probability density and statistics (minimum, maximum, mean, standard deviation and sum) of FRPD (kW<sup>−2</sup>) at the different integration times (i.e., 1.4 ms, 0.3 ms, 0.04 ms, and 0.0021 ms) for (<b>A</b>) FL-02, (<b>B</b>) FL-03, (<b>C</b>) FL-04, (<b>D</b>) FL-05, and (<b>E</b>) FL-06 acquired during night flight (F-03) and day flight (F-04) for the 2017 campaign.</p> "> Figure 15
<p>Example of FRPD (kWm<sup>−2</sup>) captured over FL-05 during both (<b>A</b>) nighttime flight, FL-03, on 2 August, and, (<b>B</b>) daytime flight, F-04, on 3 August, during the 2017 campaign over the SLK-37 site. Calculated FRDP of the 1.4 ms, 0.3 ms, 0.04 ms, and 0.0021 ms integration times superimposed based on the set thresholds (<a href="#sec3dot3-sensors-21-03047" class="html-sec">Section 3.3</a>). Overall inset area shown in brightness temperature (K) as a reference.</p> ">
Abstract
:1. Introduction
2. Data Collection
2.1. Field Campaign
2.2. FLIR Sensor
2.3. Twin Otter Survey Aircraft Hardware
3. Methods
3.1. Geocorrection Process
3.1.1. Initial Imagery Setup and Databoss Alignment
3.1.2. Initial Geolocation
3.1.3. Frame Registration
3.1.4. Gridding
3.2. Georeferencing Process
3.3. Data Products
4. Results
4.1. Geocorrection Assessment
4.2. Georeferencing Assessment
4.3. Data Products
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Flt No. | Date | Time Period | No. of Lines | Start Time (EST) | End Time (EST) | Altitude (m MSL) | Ground Speed (Knots) |
---|---|---|---|---|---|---|---|
F-03 | August 2 a | Night | 16 b | 22:20 | 23:37 | 2888.2 | 92.5 |
F-04 | August 3 | Day | 16 b | 10:26 | 11:41 | 2915.1 | 93.9 |
Characteristic | Value |
---|---|
Spectral Range (µm) | 3.0–5.0 |
Detector Pitch (µm) | 14 |
Frame Rate (Hz) | Up to 125 |
Resolution (pixels) | 1344 × 784 |
Temperature Accuracy | ±2 or 2% |
Standard Temperature Range (°C) | −20 to +350 |
Operating Temperature Range (°C) | −40 to 50 |
Weight without lens (kg) | 4.5 |
Variable | Raw, All Frames | Geocorrected, Gridded | Change (%) |
---|---|---|---|
Total Data Points | 527,901,696 | 4,701,690 | 99.11 |
Mean | −1.18 | −1.20 | 1.70 |
Median | −1.44 | −1.44 | 0.00 |
Standard Deviation | 3.08 | 2.86 | 7.14 |
Minimum | −1.66 | −1.64 | 1.21 |
Maximum | 77.39 | 77.05 | 0.44 |
Skewness | 21.18 | 22.50 | 6.23 |
Kurtosis | 489.75 | 553.33 | 12.98 |
Variable | Abs. Easting (m) | Abs. Northing (m) | Total RMSE (m) |
---|---|---|---|
Mean | 6.96 | 8.66 | 11.90 |
Minimum | 0.30 | 0.25 | 0.87 |
Maximum | 24.13 | 25.43 | 29.25 |
Median | 5.30 | 7.46 | 10.75 |
Standard deviation | 5.21 | 6.65 | 7.26 |
Variable | Abs. Easting (m) | Abs. Northing (m) | Total RMSE (m) |
---|---|---|---|
Mean | 2.38 | 2.53 | 3.86 |
Minimum | 0.01 | 0.04 | 0.17 |
Maximum | 9.42 | 13.17 | 14.28 |
Median | 2.02 | 1.55 | 3.21 |
Standard deviation | 1.96 | 2.76 | 2.92 |
Flight Line | Night Flight (August 2) | Day Flight (August 3) | |||
---|---|---|---|---|---|
IT (ms) | PGCPs | RMSE (m) | PGCPs | RMSE (m) | |
FL-02 | 1.4 | 9 | 10.85 | 10 | 8.83 |
0.3 | 9 | 8.73 | 10 | 8.83 | |
0.04 | 9 | 9.67 | 9 | 9.71 | |
FL-03 | 1.4 | 9 | 16.22 | 9 | 14.28 |
0.3 | 10 | 14.54 | 9 | 14.28 | |
0.04 | 10 | 14.54 | 9 | 14.93 | |
FL-04 | 1.4 | 9 | 17.32 | 13 | 11.76 |
0.3 | 10 | 12.46 | 13 | 11.76 | |
0.04 | 9 | 13.36 | 12 | 12.58 | |
0.0021 | 9 | 13.36 | 12 | 12.39 | |
FL-05 | 1.4 | 9 | 24.50 | 10 | 16.65 |
0.3 | 10 | 16.99 | 10 | 16.65 | |
0.04 | 9 | 18.21 | 12 | 17.44 | |
0.0021 | 9 | 18.21 | 12 | 17.33 | |
FL-06 | 1.4 | 10 | 17.33 | 10 | 13.84 |
0.3 | 10 | 14.57 | 10 | 13.84 | |
0.04 | 9 | 15.58 | 12 | 14.64 | |
0.0021 | 9 | 15.58 | 12 | 14.62 |
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Ifimov, G.; Naprstek, T.; Johnston, J.M.; Arroyo-Mora, J.P.; Leblanc, G.; Lee, M.D. Geocorrection of Airborne Mid-Wave Infrared Imagery for Mapping Wildfires without GPS or IMU. Sensors 2021, 21, 3047. https://doi.org/10.3390/s21093047
Ifimov G, Naprstek T, Johnston JM, Arroyo-Mora JP, Leblanc G, Lee MD. Geocorrection of Airborne Mid-Wave Infrared Imagery for Mapping Wildfires without GPS or IMU. Sensors. 2021; 21(9):3047. https://doi.org/10.3390/s21093047
Chicago/Turabian StyleIfimov, Gabriela, Tomas Naprstek, Joshua M. Johnston, Juan Pablo Arroyo-Mora, George Leblanc, and Madeline D. Lee. 2021. "Geocorrection of Airborne Mid-Wave Infrared Imagery for Mapping Wildfires without GPS or IMU" Sensors 21, no. 9: 3047. https://doi.org/10.3390/s21093047