Intercomparison of Landsat Operational Land Imager and Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer Radiometric Calibrations Using Radiometric Calibration Network Data

被引:1
|
作者
Yarahmadi, Mehran [1 ]
Thome, Kurtis [2 ]
Wenny, Brian N. [1 ]
Czapla-Myers, Jeff [3 ]
Voskanian, Norvik [1 ]
Tahersima, Mohammad [1 ]
Eftekharzadeh, Sarah [1 ]
机构
[1] Sci Syst & Applicat Inc, 10210 Greenbelt Rd, Lanham, MD 20706 USA
[2] NASA, Goddard Space Flight Ctr, 8800 Greenbelt Rd, Greenbelt, MD 20771 USA
[3] Univ Arizona, Wyant Coll Opt Sci, 1630 E Univ Blvd, Tucson, AZ 85721 USA
基金
美国国家航空航天局;
关键词
Landsat; 8; 9; ASTER; in situ radiometric calibration; RadCalNet; VNIR vicarious calibration; SI-traceable; intercomparison; remote sensing; ASTER;
D O I
10.3390/rs16020400
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper presents a comprehensive intercomparison study investigating the radiometric performance of and concurrence among the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat 8 Operational Land Imager (L8 OLI), and Landsat 9 OLI (L9 OLI) instruments. This study leverages data sourced from the Radiometric Calibration Network (RadCalNet) and focuses on spectral bands relevant for vegetation analysis and land cover classification, encompassing a thorough assessment of data quality, uncertainties, and underlying influencing factors. This study's outcomes underscore the efficacy of RadCalNet in evaluating the precision and reliability of remote sensing data, offering valuable insights into the strengths and limitations of ASTER, L8 OLI, and L9 OLI. These insights serve as a foundation for informed decision making in environmental monitoring and resource management, highlighting the pivotal role of RadCalNet in gauging the radiometric performance of remote sensing sensors. Results from RadCalNet sites, namely Railroad Valley Playa and Gobabeb, show their possible suitability for sensors with spatial resolutions down to 15 m. The results indicate that the measurements from both ASTER and OLI closely align with the data from RadCalNet, and the observed agreement falls comfortably within the total range of potential errors associated with the sensors and the test site information.
引用
收藏
页数:21
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