Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ Measurements
The radiometric calibration network (RadCalNet) comprises four pseudo-invariant calibration sites (PICS): Gobabeb, Baotou, Railroad Valley Playa, and La Crau. Due to its site stability characteristics, it is widely used for sensor performance monitoring and radiometric calibration, which require hig...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/10/2639 |
| _version_ | 1797598424628985856 |
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| author | Enchuan Qiao Chao Ma Hao Zhang Zhenzhen Cui Chenglong Zhang |
| author_facet | Enchuan Qiao Chao Ma Hao Zhang Zhenzhen Cui Chenglong Zhang |
| author_sort | Enchuan Qiao |
| collection | DOAJ |
| description | The radiometric calibration network (RadCalNet) comprises four pseudo-invariant calibration sites (PICS): Gobabeb, Baotou, Railroad Valley Playa, and La Crau. Due to its site stability characteristics, it is widely used for sensor performance monitoring and radiometric calibration, which require high spatiotemporal stability. However, some studies have found that PICS are not invariable. Previous studies used top-of-atmosphere (TOA) data without verifying site data, which could affect the accuracy of their results. In this study, we analyzed the short- and long-term radiometric trends of RadCalNet sites using bottom-of-atmosphere (BOA) data, and verified the trends revealed by the TOA data from Landsat 7, 8, and Sentinel-2. Besides the commonly used methods (e.g., nonparametric Mann–Kendall and sequential Mann–Kendall tests), a more robust Sen’s slope method was used to estimate the magnitude of the change. We found that (1) the trends based on TOA reflectance contrasted with those based on BOA reflectance in certain cases, e.g., the reflectance trends in the red band of BOA data for La Crau in summer and autumn and Baotou were not significant, while the TOA data showed a significant downward trend; (2) the temporal trends showed statistically significant and abrupt changes in all PICS, e.g., the SWIR2 band of La Crau in winter and spring changed by 1.803% per year, and the SWIR1 band of Railroad Valley Playa changed by >0.282% per year, indicating that the real changes in sensor performance are hard to detect using these sites; (3) spatial homogeneity was verified using the coefficient of variation (CV) and Getis statistic (Gi*) for each PICS (CV < 3% and Gi* > 0). Overall, the RadCalNet remains a highly reliable tool for vicarious calibration; however, the temporal stability should be noted for radiometric performance monitoring of sensors. |
| first_indexed | 2024-03-11T03:21:02Z |
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| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T03:21:02Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj.art-076d6311d80f478c9ffe73787f45e16a2023-11-18T03:08:03ZengMDPI AGRemote Sensing2072-42922023-05-011510263910.3390/rs15102639Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ MeasurementsEnchuan Qiao0Chao Ma1Hao Zhang2Zhenzhen Cui3Chenglong Zhang4School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaAirborne Remote Sensing Center, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaAirborne Remote Sensing Center, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaThe radiometric calibration network (RadCalNet) comprises four pseudo-invariant calibration sites (PICS): Gobabeb, Baotou, Railroad Valley Playa, and La Crau. Due to its site stability characteristics, it is widely used for sensor performance monitoring and radiometric calibration, which require high spatiotemporal stability. However, some studies have found that PICS are not invariable. Previous studies used top-of-atmosphere (TOA) data without verifying site data, which could affect the accuracy of their results. In this study, we analyzed the short- and long-term radiometric trends of RadCalNet sites using bottom-of-atmosphere (BOA) data, and verified the trends revealed by the TOA data from Landsat 7, 8, and Sentinel-2. Besides the commonly used methods (e.g., nonparametric Mann–Kendall and sequential Mann–Kendall tests), a more robust Sen’s slope method was used to estimate the magnitude of the change. We found that (1) the trends based on TOA reflectance contrasted with those based on BOA reflectance in certain cases, e.g., the reflectance trends in the red band of BOA data for La Crau in summer and autumn and Baotou were not significant, while the TOA data showed a significant downward trend; (2) the temporal trends showed statistically significant and abrupt changes in all PICS, e.g., the SWIR2 band of La Crau in winter and spring changed by 1.803% per year, and the SWIR1 band of Railroad Valley Playa changed by >0.282% per year, indicating that the real changes in sensor performance are hard to detect using these sites; (3) spatial homogeneity was verified using the coefficient of variation (CV) and Getis statistic (Gi*) for each PICS (CV < 3% and Gi* > 0). Overall, the RadCalNet remains a highly reliable tool for vicarious calibration; however, the temporal stability should be noted for radiometric performance monitoring of sensors.https://www.mdpi.com/2072-4292/15/10/2639PICSRadCalNetMann–Kendallsequential Mann–KendallSen’s slope |
| spellingShingle | Enchuan Qiao Chao Ma Hao Zhang Zhenzhen Cui Chenglong Zhang Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ Measurements Remote Sensing PICS RadCalNet Mann–Kendall sequential Mann–Kendall Sen’s slope |
| title | Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ Measurements |
| title_full | Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ Measurements |
| title_fullStr | Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ Measurements |
| title_full_unstemmed | Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ Measurements |
| title_short | Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ Measurements |
| title_sort | evaluation of temporal stability in radiometric calibration network sites using multi source satellite data and continuous in situ measurements |
| topic | PICS RadCalNet Mann–Kendall sequential Mann–Kendall Sen’s slope |
| url | https://www.mdpi.com/2072-4292/15/10/2639 |
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