Towards the Copernicus Hyperspectral Imaging Mission For The Environment (CHIME)

Nieke, Jens; Rast, M.

doi:10.1109/igarss.2018.8518384

Cited by 93 publications

(75 citation statements)

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“…In view of future hyperspectral satellite missions like Italian PRISMA [34], US HyspIRI [35], Israeli-Italian SHALOM [36], European CHIME [37], and German EnMAP [38] fast and efficient retrieval methods for large datasets are required. Mathematically simpler physically-based approaches have been applied before to circumvent the equifinality problem and to reduce the computational effort of RTM-based model inversion.…”

Section: Introductionmentioning

confidence: 99%

Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data

et al. 2018

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Quantitative equivalent water thickness on canopy level (EWT canopy ) is an important land surface variable and retrieving EWT canopy from remote sensing has been targeted by many studies. However, the effect of radiative penetration into the canopy has not been fully understood. Therefore, in this study the Beer-Lambert law is applied to inversely determine water content information in the 930 to 1060 nm range of canopy reflectance from measured winter wheat and corn spectra collected in 2015, 2017, and 2018. The spectral model was calibrated using a look-up-table (LUT) of 50,000 PROSPECT spectra. Internal model validation was performed using two leaf optical properties datasets (LOPEX93 and ANGERS). Destructive in-situ measurements of water content were collected separately for leaves, stalks, and fruits. Correlation between measured and modelled water content was most promising for leaves and ears in case of wheat, reaching coefficients of determination (R 2 ) up to 0.72 and relative RMSE (rRMSE) of 26% and in case of corn for the leaf fraction only (R 2 = 0.86, rRMSE = 23%). These findings indicate that, depending on the crop type and its structure, different parts of the canopy are observed by optical sensors. The results from the Munich-North-Isar test sites indicated that plant compartment specific EWT canopy allows us to deduce more information about the physical meaning of model results than from equivalent water thickness on leaf level (EWT) which is upscaled to canopy water content (CWC) by multiplication of the leaf area index (LAI). Therefore, it is suggested to collect EWT canopy data and corresponding reflectance for different crop types over the entire growing cycle. Nevertheless, the calibrated model proved to be transferable in time and space and thus can be applied for fast and effective retrieval of EWT canopy in the scope of future hyperspectral satellite missions.

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Section: Introductionmentioning

confidence: 99%

Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data

et al. 2018

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“…The performance of our method was tested here by adding scaled random Gaussian noise, relative to three SNR values, namely: low (100), moderate (300), and high (600). The noise was added according to Equation (12) in [17]:…”

Section: Add Noise To the Datamentioning

confidence: 99%

The Potential of Multi- and HyperSpectral Air- and Spaceborne Sensors to Detect Crude Oil Hydrocarbon in Soils Long after a Contamination Event

Pelta

Ben‐Dor

2019

Applied Sciences

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Crude oil contamination is hazardous to health, negatively impacts vital life sources, and causes land and ecological degradation. The basic premise of the prevalent spectroscopic analyses for detecting such contamination is that crude oil spectral features are observable in the spectrum. Such analyses, however, have failed to address instances where the expected spectral features are not visible in the spectrum. Hence, a more refined method was recently published, which accounts for such cases. This method was successfully applied to a hyperspectral image over an arid area long after a contamination event. This study aimed to determine whether that same method could be successfully applied using a variety of other operational and future instruments, both air- and spaceborne, with different spatial and spectral characteristics. To that end, a series of simulation experiments was performed, including various spectral and spatial resolutions. Quantitative and qualitative evaluations of the classification are reported. The results indicate that the hyperspectral information can be reduced to one-third of its original size, while maintaining high accuracy and a quality classification map. A ground sampling distance of 7.5 m seems to be the boundary of an acceptable classification outcome. The overall conclusion of this study was that the method is robust enough to perform under various spectral and spatial configurations. Therefore, it could be a promising tool to be integrated into environmental protection and resource management programs.

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“…The Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) [8] aims to augment the Copernicus space component with precise spectroscopic measurements to derive quantitative surface characteristics supporting the monitoring, implementation and improvement of a range of policies in the domain of raw materials, agriculture, soils, food security, biodiversity, environmental degradation and hazards, inland and coastal waters, snow, forestry and the urban environment.…”

Section: Chime Detector Pre-developmentmentioning

confidence: 99%

Detector development activities supported by the European Space Agency

Weber

Nelms

Minoglou

et al. 2019

International Conference on Space Optics — ICSO 2018

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Detectors play a crucial role for the instrument design and the achievable instrument performance. The wavebands of interest for remote sensing are the visible and the infrared. Therefore, the European Space Agency has a strong interest in the performance enhancement of detector arrays in those spectral ranges. The Agency follows a continuous development strategy to enhance the capabilities for future Earth observation and astronomy missions. This paper presents the technical and planning status of these detector technology development activities.

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Towards the Copernicus Hyperspectral Imaging Mission For The Environment (CHIME)

Cited by 93 publications

References 0 publications

Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data

Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data

The Potential of Multi- and HyperSpectral Air- and Spaceborne Sensors to Detect Crude Oil Hydrocarbon in Soils Long after a Contamination Event

Detector development activities supported by the European Space Agency

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