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陆地卫星地表产品验证仪器:大麦克演习

Landsat Surface Product Validation Instrumentation: The BigMAC Exercise.

作者信息

Helder Dennis, Shrestha Mahesh, Mann Joshua, Maddox Emily, Irwin Jeffery, Leigh Larry, Gerace Aaron, Eon Rehman, Falcon Lucy, Conran David, Raqueno Nina, Bauch Timothy, Durell Christopher, Russell Brandon

机构信息

KBR, Contractor to U.S. Geological Survey Earth Resources Observation and Science Center, Sioux Falls, SD 57030, USA.

U.S. Geological Survey Earth Resources Observation and Science Center, Sioux Falls, SD 57030, USA.

出版信息

Sensors (Basel). 2025 Apr 19;25(8):2586. doi: 10.3390/s25082586.

Abstract

Users of remotely sensed Earth optical imagery are increasingly demanding a surface reflectance or surface temperature product instead of the top-of-atmosphere products that have been produced historically. Validating the accuracy of surface products remains a difficult task since it involves assessment across a range of atmospheric profiles, as well as many different land surface types. Thus, the standard approaches from the satellite calibration community do not apply, and new technologies need to be developed. The Big Multi-Agency Campaign (BigMAC) was developed to assess current technologies that might be used for the validation of surface products derived from satellite imagery, with emphasis on Landsat. Conducted in August 2021, in Brookings, SD, USA, a variety of measurement technologies were fielded and assessed for accuracy, precision, and deployability. Each technology exhibited its strengths and weaknesses. Handheld spectroradiometers are capable of surface reflectance measurements with accuracies within the 0.01-0.02 absolute reflectance units, but these are expensive to deploy. Unmanned Aircraft System (UAS)-based radiometers have the potential of making measurements with similar accuracy, but these are also difficult to deploy. Mirror-based empirical line methods showed improved accuracy potential, but their deployment also remains an issue. However, there are inexpensive radiometers designed for long-term autonomous use that exhibited good accuracy and precision, in addition to being easy to deploy. Thermal measurement technologies showed an accuracy potential in the 1-2 K range, and some easily deployable instruments are available. The results from the BigMAC indicate that there are technologies available today for conducting operational surface reflectance/temperature measurements, with strong potential for improvements in the future.

摘要

地球光学遥感影像的用户越来越需要地表反射率或地表温度产品,而非以往生成的大气层顶产品。由于要对一系列大气剖面以及多种不同的陆地表面类型进行评估,验证地表产品的准确性仍然是一项艰巨的任务。因此,卫星校准领域的标准方法并不适用,需要开发新技术。开展大型多机构活动(BigMAC)的目的是评估可用于验证源自卫星影像的地表产品的现有技术,重点是陆地卫星。该活动于2021年8月在美国南达科他州布鲁金斯市举行,部署并评估了多种测量技术的准确性、精度和可部署性。每种技术都有其优缺点。手持式光谱辐射计能够进行地表反射率测量,绝对反射率精度在0.01 - 0.02单位以内,但部署成本高昂。基于无人机系统(UAS)的辐射计有潜力实现类似的测量精度,但部署也很困难。基于镜面的经验线方法显示出提高精度的潜力,但其部署仍是个问题。然而,有一些专为长期自主使用设计的廉价辐射计,除了易于部署外,还具有良好的准确性和精度。热测量技术显示出在1 - 2K范围内的精度潜力,并且有一些易于部署的仪器可供使用。BigMAC的结果表明,目前有可用于进行地表反射率/温度业务测量的技术,未来还有很大的改进潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f01a/12031503/168b90504f91/sensors-25-02586-g001.jpg

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