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Remote sensing reflectance (Rrs), which is currently measured mainly using the above-water approach, is the most crucial parameter in the remote sensing inversion of plateau inland water colors. It is very difficult to measure the Rrs of plateau inland unmanned areas; thus, we provide a measurement solution using a micro-spectrometer. Currently, commercial micro-spectrometers are not factory calibrated for radiation, and thus, a radiometric calibration of the micro-spectrometer is an essential step. This article uses an Ocean Optics micro-spectrometer (STS-VIS) and a traditional water spectrometer (Trios) to simultaneously measure the irradiance and radiance of diffuse reflectance plates with different reflectance values for field calibration. The results show the following: (1) different fiber types have different calibration coefficients, and the integration time is determined according to the diameter of the fiber and the type of fiber, and (2) by comparing the simultaneous measurement results of STS-VIS with Trios, the mean absolute percentage difference (MAPD) of both reached 18.64% and 5.11% for Qinghai Lake and Golmud River, respectively, which are accurate Rrs measurements of water bodies. The Rrs of the Hoh Xil and Qarhan Salt Lake water bodies in unmanned areas of China was measured, and this was the first collection of in situ spectral information with a micro-spectrometer. This article shows that the micro-spectrometer can perform the in situ measurement of water Rrs in unmanned inland areas. With this breakthrough in the radiometric performance of the micro-spectrometer, we are able to obtain more accurate remote sensing reflectance results of unmanned water bodies. [ABSTRACT FROM AUTHOR]

Combinations of unmanned aerial platforms and multispectral sensors are considered low-cost tools for detailed spatial and temporal studies addressing spectral signatures, opening a broad range of applications in remote sensing. Thus, a key step in this process is knowledge of multi-spectral sensor calibration parameters in order to identify the physical variables collected by the sensor. This paper discusses the radiometric calibration process by means of a vicarious method applied to a high-spatial resolution unmanned flight using low-cost artificial and natural covers as control and check surfaces, respectively. [ABSTRACT FROM AUTHOR]

Radiometric intercomparison between satellite remote sensing instruments has become an increasingly common practice to monitor the stability and even the accuracy of their radiance products. The assessment also enables the evaluation of calibration improvements made to these products, as well as the identification and resolution of remaining calibration inadequacies. In this paper, the radiance products of the Cross-track Infrared Sounder (CrIS), an interferometer-based hyperspectral IR sounder in low Earth orbit (LEO), is compared with the level-1b (L1b) radiance products of the infrared (IR) bands of the Advanced Baseline Imager (ABI), an imaging radiometer in geostationary (GEO) orbit. Two CrIS instruments are currently in operation on S-NPP and NOAA-20 satellites, respectively, and two ABI instruments are in operation on GOES-16 and GOES-17 satellites, respectively. Radiometric intercomparisons are performed between each CrIS-ABI pair. An established procedure by GSICS for such GEO-LEO instrument comparison is principally followed to emulate the radiance of ABI IR bands from CrIS spectra of the collocated pixels to be compared with the actual ABI radiance. Results show that the long-term time series of CrIS-ABI radiance bias have been stable within 0.2 K for nearly all ABI IR bands within a spectral range from 3.7 μ m to 13.3 μ m, except those with known calibration issues. Miscellaneous calibration events that had occurred to either instrument and altered the biases are identified and explained. While the main goal of the work is to support the on-orbit Cal/Val of CrIS, including the future JPSS-2/3/4 CrIS, such observations can also be referenced to further improve the calibration of ABI. [ABSTRACT FROM AUTHOR]

Vicarious calibration, as one on-orbit calibration method, is a supplement to onboard calibration of sensors. The application of vicarious calibration, however, is greatly limited due to the time- and effort-consuming field measurements of atmosphere and surface. Fortunately, the Radiometric Calibration Network (RadCalNet) provides automated in situ data at multiple sites, thus increasing the opportunities to achieve ongoing ground-reference calibration of in-orbit instruments. The MEdium Resolution Spectrum Imager-II (MERSI-II) onboard FengYun-3D (FY) has the temporal, spectral, spatial, and radiometric capacity for image capture at a level on par with other sensors used worldwide, such as the Moderate Resolution Imaging Spectroradiometer (MODIS). Its on-orbit radiometric performance, however, is assessed in a limited manner. In this study, the reflectance-based vicarious calibration method was employed to calibrate the MERSI-II sensor using ground measurements from RadCalNet at the Railroad Valley Playa site. The calibration of the MERSI-II sensor with large view angles presents difficulties due to the uncertainties introduced by surface bidirectional reflectance distribution function (BRDF) effects. Thus, we performed BRDF correction to harmonize the sensor and ground measurements to consistent observation geometries, before the in-situ measurements were taken as inputs for the 6SV radiative transfer model to predict at-sensor radiance. The calibration results were comprehensively validated with ground data and MODIS benchmark datasets. The results show that accounting for BRDF correction could improve the accuracy of vicarious calibration and ensure inter-consistency between different sensors. An analysis of the vicarious calibration of FY-3D MERSI-II yielded uncertainties of <5% for solar reflective bands, which meets the radiometric accuracy requirements typical for land-monitoring space missions. The proposed approach is also applicable to the calibration of other large footprint sensors. [ABSTRACT FROM AUTHOR]

The Earth's climate is undoubtedly changing; however, the time scale, consequences, and causal attribution remain the subject of significant debate and uncertainty. Detection of subtle indicators from a background of natural variability requires measurements over a time-base of decades. This places severe demands on the instrumentation used, requiring measurements of sufficient accuracy and sensitivity that can allow reliable judgements to be made decades apart. The International System of Units (SI) was developed to address such requirements, providing a reference framework tied to invariant constants of nature. However, ensuring and maintaining SI traceability of sufficient accuracy in instruments orbiting the Earth presents a significant new challenge to the Earth Observation and metrology communities. This paper describes a new satellite mission, called Traceable Radiometry Underpinning Terrestrial- and Helio- Studies (TRUTHS), which enables, for the first time, high-accuracy SI traceability to be established in orbit. The direct use of a 'primary standard' and replication of the terrestrial traceability chain extends the SI into space, in effect realizing a 'metrology laboratory in space' providing and enabling SI-traceable measurements of unequivocal accuracy in the solar reflective domain—an enabling element of an international space-based climate observing system. TRUTHS will not only provide a benchmark of the radiation state of the planet (incoming and outgoing) from which to compare change in the shortest time possible, but also facilitate an upgrade in performance of the Earth Observing system as a whole, through 'in-orbit' reference calibration. [ABSTRACT FROM AUTHOR]

This paper focuses on the calibration of multispectral sensors typically used for remote sensing. These systems are often provided with "factory" radiometric calibration and vignette correction parameters. These parameters, which are assumed to be accurate when the sensor is new, may change as the camera is utilized in real-world conditions. As a result, regular calibration and characterization of any sensor should be conducted. An end-user laboratory method for computing both the vignette correction and radiometric calibration function is discussed in this paper. As an exemplar, this method for radiance computation is compared to the method provided by MicaSense for their RedEdge series of sensors. The proposed method and the method provided by MicaSense for radiance computation are applied to a variety of images captured in the laboratory using a traceable source. In addition, a complete error propagation is conducted to quantify the error produced when images are converted from digital counts to radiance. The proposed methodology was shown to produce lower errors in radiance imagery. The average percent error in radiance was −10.98%, −0.43%, 3.59%, 32.81% and −17.08% using the MicaSense provided method and their "factory" parameters, while the proposed method produced errors of 3.44%, 2.93%, 2.93%, 3.70% and 0.72% for the blue, green, red, near infrared and red edge bands, respectively. To further quantify the error in terms commonly used in remote sensing applications, the error in radiance was propagated to a reflectance error and additionally used to compute errors in two widely used parameters for assessing vegetation health, NDVI and NDRE. For the NDVI example, the ground reference was computed to be 0.899 ± 0.006, while the provided MicaSense method produced a value of 0.876 ± 0.005 and the proposed method produced a value of 0.897 ± 0.007. For NDRE, the ground reference was 0.455 ± 0.028, MicaSense method produced 0.239 ± 0.026 and the proposed method produced 0.435 ± 0.038. [ABSTRACT FROM AUTHOR]

Drone-based remote sensing has evolved rapidly in recent years. Miniaturized hyperspectral imaging sensors are becoming more common as they provide more abundant information of the object compared to traditional cameras. Reflectance is a physically defined object property and therefore often preferred output of the remote sensing data capture to be used in the further processes. Absolute calibration of the sensor provides a possibility for physical modelling of the imaging process and enables efficient procedures for reflectance correction. Our objective is to develop a method for direct reflectance measurements for drone-based remote sensing. It is based on an imaging spectrometer and irradiance spectrometer. This approach is highly attractive for many practical applications as it does not require in situ reflectance panels for converting the sensor radiance to ground reflectance factors. We performed SI-traceable spectral and radiance calibration of a tuneable Fabry-Pérot Interferometer -based (FPI) hyperspectral camera at the National Physical Laboratory NPL (Teddington, UK). The camera represents novel technology by collecting 2D format hyperspectral image cubes using time sequential spectral scanning principle. The radiance accuracy of different channels varied between ±4% when evaluated using independent test data, and linearity of the camera response was on average 0.9994. The spectral response calibration showed side peaks on several channels that were due to the multiple orders of interference of the FPI. The drone-based direct reflectance measurement system showed promising results with imagery collected over Wytham Forest (Oxford, UK). [ABSTRACT FROM AUTHOR]