Multispectral UAS Data Accuracy for Different Radiometric Calibration Methods
Unmanned aircraft systems (UAS) allow us to collect aerial data at high spatial and temporal resolution. Raw images are taken along a predetermined flight path and processed into a single raster file covering the entire study area. Radiometric calibration using empirical or manufacturer methods is r...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/16/1917 |
| _version_ | 1818971369022423040 |
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| author | Aurelie M. Poncet Thorsten Knappenberger Christian Brodbeck Michael Fogle Joey N. Shaw Brenda V. Ortiz |
| author_facet | Aurelie M. Poncet Thorsten Knappenberger Christian Brodbeck Michael Fogle Joey N. Shaw Brenda V. Ortiz |
| author_sort | Aurelie M. Poncet |
| collection | DOAJ |
| description | Unmanned aircraft systems (UAS) allow us to collect aerial data at high spatial and temporal resolution. Raw images are taken along a predetermined flight path and processed into a single raster file covering the entire study area. Radiometric calibration using empirical or manufacturer methods is required to convert raw digital numbers into reflectance and to ensure data accuracy. The performance of five radiometric calibration methods commonly used was investigated in this study. Multispectral imagery was collected using a Parrot Sequoia camera. No method maximized data accuracy in all bands. Data accuracy was higher when the empirical calibration was applied to the processed raster rather than the raw images. Data accuracy achieved with the manufacturer-recommended method was comparable to the one achieved with the best empirical method. Radiometric error in each band varied linearly with pixel radiometric values. Smallest radiometric errors were obtained in the red-edge and near-infrared (NIR) bands. Accuracy of the composite indices was higher for the pixels representing a dense vegetative cover in comparison to a lighter cover or bare soil. Results provided a better understanding of the advantages and limitations of existing radiometric calibration methods as well as the impact of the radiometric error on data quality. The authors recommend that researchers evaluate the performance of their radiometric calibration before analyzing UAS imagery and interpreting the results. |
| first_indexed | 2024-12-20T14:51:16Z |
| format | Article |
| id | doaj.art-13b142b61deb4a4a90936f0fa7b9e3c6 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T14:51:16Z |
| publishDate | 2019-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-13b142b61deb4a4a90936f0fa7b9e3c62022-12-21T19:36:57ZengMDPI AGRemote Sensing2072-42922019-08-011116191710.3390/rs11161917rs11161917Multispectral UAS Data Accuracy for Different Radiometric Calibration MethodsAurelie M. Poncet0Thorsten Knappenberger1Christian Brodbeck2Michael Fogle3Joey N. Shaw4Brenda V. Ortiz5Department of Crop, Soil, and Environmental Sciences, 201 Funchess Hall, Auburn University, Auburn, AL 36849, USADepartment of Crop, Soil, and Environmental Sciences, 201 Funchess Hall, Auburn University, Auburn, AL 36849, USADepartment of Biosystems Engineering, 207 Corley Building, Auburn University, Auburn, AL 36849, USADepartment of Physics, 206 Allison Laboratories, Auburn University, Auburn, AL 36849, USADepartment of Crop, Soil, and Environmental Sciences, 201 Funchess Hall, Auburn University, Auburn, AL 36849, USADepartment of Crop, Soil, and Environmental Sciences, 201 Funchess Hall, Auburn University, Auburn, AL 36849, USAUnmanned aircraft systems (UAS) allow us to collect aerial data at high spatial and temporal resolution. Raw images are taken along a predetermined flight path and processed into a single raster file covering the entire study area. Radiometric calibration using empirical or manufacturer methods is required to convert raw digital numbers into reflectance and to ensure data accuracy. The performance of five radiometric calibration methods commonly used was investigated in this study. Multispectral imagery was collected using a Parrot Sequoia camera. No method maximized data accuracy in all bands. Data accuracy was higher when the empirical calibration was applied to the processed raster rather than the raw images. Data accuracy achieved with the manufacturer-recommended method was comparable to the one achieved with the best empirical method. Radiometric error in each band varied linearly with pixel radiometric values. Smallest radiometric errors were obtained in the red-edge and near-infrared (NIR) bands. Accuracy of the composite indices was higher for the pixels representing a dense vegetative cover in comparison to a lighter cover or bare soil. Results provided a better understanding of the advantages and limitations of existing radiometric calibration methods as well as the impact of the radiometric error on data quality. The authors recommend that researchers evaluate the performance of their radiometric calibration before analyzing UAS imagery and interpreting the results.https://www.mdpi.com/2072-4292/11/16/1917aerial imagerydroneempirical calibrationradiometric errorerror propagationvegetation indices |
| spellingShingle | Aurelie M. Poncet Thorsten Knappenberger Christian Brodbeck Michael Fogle Joey N. Shaw Brenda V. Ortiz Multispectral UAS Data Accuracy for Different Radiometric Calibration Methods Remote Sensing aerial imagery drone empirical calibration radiometric error error propagation vegetation indices |
| title | Multispectral UAS Data Accuracy for Different Radiometric Calibration Methods |
| title_full | Multispectral UAS Data Accuracy for Different Radiometric Calibration Methods |
| title_fullStr | Multispectral UAS Data Accuracy for Different Radiometric Calibration Methods |
| title_full_unstemmed | Multispectral UAS Data Accuracy for Different Radiometric Calibration Methods |
| title_short | Multispectral UAS Data Accuracy for Different Radiometric Calibration Methods |
| title_sort | multispectral uas data accuracy for different radiometric calibration methods |
| topic | aerial imagery drone empirical calibration radiometric error error propagation vegetation indices |
| url | https://www.mdpi.com/2072-4292/11/16/1917 |
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