Towards consistent assessments of in situ radiometric measurements for the validation of fluorescence satellite missions

Buman, Bastian; Hueni, Andreas; Colombo, R.; Cogliati, Sergio; Celesti, Marco; Julitta, Tommaso; Burkart, Andreas; Siegmann, Bastian; Rascher, Uwe; Drusch, Matthias; Damm, Alexander

doi:10.1016/j.rse.2022.112984

Cited by 16 publications

(7 citation statements)

References 64 publications

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“…An uncertainty budget related to SIF retrieval was recently provided by Buman et al [12], who characterised the uncertainties due to instrumental effects, procedures applied for data calibration, atmospheric correction, SIF retrieval approach and the spatial representativeness of in situ observations compared to satellite measurements. Regarding the uncertainties related to the spatial representativeness, they pointed out the challenge of identifying pseudo-invariant homogeneous calibration sites for SIF products and the potential impact of site heterogeneity on the reliability of in situ SIF retrieval for satellite products validation.…”

Section: Discussionmentioning

confidence: 99%

“…However, the scale mismatch between the satellite and the independent SIF estimates used for validation may introduce uncertainty in the evaluation accuracy if an appropriate number and distribution of higher-spatial-resolution observations are not considered. Validation of SIF products compared to other RS products is further complicated by the fact that these independent sensors do not measure SIF directly, with the resulting estimates affected by uncertainties related to the measuring system, the processing of the raw data to radiance units and the SIF retrieval algorithm [12,13].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the Spatial Representativeness of In Situ SIF Observations for the Validation of Medium-Resolution Satellite SIF Products

et al. 2022

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The upcoming Fluorescence Explorer (FLEX) mission will provide sun-induced fluorescence (SIF) products at unprecedented spatial resolution. Thus, accurate calibration and validation (cal/val) of these products are key to guarantee robust SIF estimates for the assessment and quantification of photosynthetic processes. In this study, we address one specific component of the uncertainty budget related to SIF retrieval: the spatial representativeness of in situ SIF observations compared to medium-resolution SIF products (e.g., 300 m pixel size). Here, we propose an approach to evaluate an optimal sampling strategy to characterise the spatial representativeness of in situ SIF observations based on high-spatial-resolution SIF data. This approach was applied for demonstration purposes to two agricultural areas that have been extensively characterized with a HyPlant airborne imaging spectrometer in recent years. First, we determined the spatial representativeness of an increasing number of sampling points with respect to a reference area (either monocultural crop fields or hypothetical FLEX pixels characterised by different land cover types). Then, we compared different sampling approaches to determine which strategy provided the most representative reference data for a given area. Results show that between 3 and 13.5 sampling points are needed to characterise the average SIF value of both monocultural fields and hypothetical FLEX pixels of the agricultural areas considered in this study. The number of sampling points tends to increase with the standard deviation of SIF of the reference area, as well as with the number of land cover classes in a FLEX pixel, even if the increase is not always statistically significant. This study contributes to guiding cal/val activities for the upcoming FLEX mission, providing useful insights for the selection of the validation site network and particularly for the definition of the best sampling scheme for each site.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of the Spatial Representativeness of In Situ SIF Observations for the Validation of Medium-Resolution Satellite SIF Products

et al. 2022

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“…Sensitivity assessment of state-of-the-art approaches: Remote sensing measurements and retrieved crop information can be subject to insensitivity or uncertainties caused by various sources, e.g., instrumental effects and calibration issues (Pacheco-Labrador et al, 2019a), spatial-spectral-temporal sampling design (Aasen et al, 2019), retrieval assumptions (Cendrero-Mateo et al, 2019), cf. Buman et al (2022) for an overview of related uncertainties on SIF. Such effects can result in a mismatch between expected and observed crop behaviour (e.g.…”

Section: Proposed Conceptional Framework: Integration Of Crop Growth ...mentioning

confidence: 99%

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

Berger

Machwitz

Kycko

et al. 2022

Remote Sensing of Environment

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“…Therefore, in situ measurements are often used as the truth of objects and plays an important role in the applications of Earth observation and environmental monitoring systems [3]. The main applications include the following: the vicarious calibration of remote sensors [4]; the correction of atmospheric effects on airborne or spaceborne images [5]; the validation of the quantitative remote sensing data products [6]; the identification and classification of the targets from images [7]; the establishment of models of biophysical attributes, biological processes, and remote sensing feature attributes [8]; the prediction of the best spectral bands, geometric configurations, and the optimum time for a specific task [9]; and the supplementation of the spectral library.…”

Section: Introductionmentioning

confidence: 99%

The Impact and Correction of Sensitive Environmental Factors on Spectral Reflectance Measured In Situ

Zhao,

Wang,

Jia

et al. 2023

Remote Sensing

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The spectral reflectance measured in situ is often regarded as the “truth” of objects, which plays an important role in Earth observation applications. However, in situ measurements are influenced by several factors such as atmospheric conditions, illumination and view geometry (I&VG), cloud coverage, and adjacency effects. In order to avoid the influence of these factors, in situ measurements are usually carried out under sunny days and close to noon. However, the impact of I&VG is still present in most cases. At present, people still know little about the influence mechanism of I&VG. Moreover, correcting the impact of I&VG is also a problem that needs to be urgently solved in reflectance spectroscopy. In this work, experiments are carried out using the multi-directional hyperspectral remote sensing simulation facility (MHSRS2F), which allows adjustment and control of the I&VG parameters. This paper proposes an uncertainty evaluation model for I&VG and quantifies the uncertainty caused by different I&VG parameters. Then, the sensitivity of reflectance to I&VG at different wavelengths is explored based on uncertainty models. Finally, a correction model for reflectance under different I&VG conditions is proposed. The results reveal that the uncertainty and sensitivity caused by observation height are relatively high, regardless of the surface heterogeneity. It directly affects the size of the field of view and the physicochemical characteristics of the object. For objects that approximate the Lambertian surface, more attention should be paid to the selection and variation of solar and view zenith angles and view azimuth angles. For objects with surface heterogeneity, the selection and variation of solar azimuth angle, view azimuth angle, and solar zenith angle are more crucial. The correction model proposed in this paper has a 41.25% correction effect on different view zenith angles, but the correction effect on other environmental factors is not significant.

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Towards consistent assessments of in situ radiometric measurements for the validation of fluorescence satellite missions

Cited by 16 publications

References 64 publications

Evaluation of the Spatial Representativeness of In Situ SIF Observations for the Validation of Medium-Resolution Satellite SIF Products

Evaluation of the Spatial Representativeness of In Situ SIF Observations for the Validation of Medium-Resolution Satellite SIF Products

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

The Impact and Correction of Sensitive Environmental Factors on Spectral Reflectance Measured In Situ

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