The PRISMA mission

Candela, Leonardo; Formaro, Roberto; Guarini, Rocchina; Loizzo, R.; Longo, F.; Varacalli, G.

doi:10.1109/igarss.2016.7729057

Cited by 38 publications

(20 citation statements)

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“…It belongs to the class of small satellites, with an expected operating life of 5 years. The PRISMA system provides the capability to acquire, downlink and archive images of all hyperspectral/panchromatic channels totalling 200,000 km 2 daily over the primary area of interest defined as in the following ranges: 180°W—180°E and 70°S—70°N [ 37 ]. A comprehensive description of the PRISMA optical design and technical specifications, including pre-launch and in-flight spectral and radiometric characterization/calibration information, are described in [ 38 ].…”

Section: Methodsmentioning

confidence: 99%

“…Overall, PRISMA offers the scientific community and users many applications in the field of environmental monitoring and resources management in multiple domains, such as agriculture and forestry, raw material exploration and mining, snow and inland and coastal waters [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ]. Due to its potential recognised use in aquatic remote sensing [ 39 ], PRISMA images are expected to provide significant advance in algorithm development and innovative monitoring tools.…”

Section: Methodsmentioning

confidence: 99%

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First Evaluation of PRISMA Level 1 Data for Water Applications

Giardino

Bresciani

Braga

et al. 2020

Sensors

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This study presents a first assessment of the Top-Of-Atmosphere (TOA) radiances measured in the visible and near-infrared (VNIR) wavelengths from PRISMA (PRecursore IperSpettrale della Missione Applicativa), the new hyperspectral satellite sensor of the Italian Space Agency in orbit since March 2019. In particular, the radiometrically calibrated PRISMA Level 1 TOA radiances were compared to the TOA radiances simulated with a radiative transfer code, starting from in situ measurements of water reflectance. In situ data were obtained from a set of fixed position autonomous radiometers covering a wide range of water types, encompassing coastal and inland waters. A total of nine match-ups between PRISMA and in situ measurements distributed from July 2019 to June 2020 were analysed. Recognising the role of Sentinel-2 for inland and coastal waters applications, the TOA radiances measured from concurrent Sentinel-2 observations were added to the comparison. The results overall demonstrated that PRISMA VNIR sensor is providing TOA radiances with the same magnitude and shape of those in situ simulated (spectral angle difference, SA, between 0.80 and 3.39; root mean square difference, RMSD, between 0.98 and 4.76 [mW m−2 sr−1 nm−1]), with slightly larger differences at shorter wavelengths. The PRISMA TOA radiances were also found very similar to Sentinel-2 data (RMSD < 3.78 [mW m−2 sr−1 nm−1]), and encourage a synergic use of both sensors for aquatic applications. Further analyses with a higher number of match-ups between PRISMA, in situ and Sentinel-2 data are however recommended to fully characterize the on-orbit calibration of PRISMA for its exploitation in aquatic ecosystem mapping.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

First Evaluation of PRISMA Level 1 Data for Water Applications

Giardino

Bresciani

Braga

et al. 2020

Sensors

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“…Spaceborne hyperspectral sensors, combining high resolution spectral and temporal sampling to cover dynamic processes, are especially promising for agricultural purposes [41]. Amongst the currently planned hyperspectral spaceborne missions are EnMAP [42], PRISMA [43], SHALOM [44], HyspIRI [45] and CHIME [46].…”

Section: Descriptionmentioning

confidence: 99%

Fitted PROSAIL Parameterization of Leaf Inclinations, Water Content and Brown Pigment Content for Winter Wheat and Maize Canopies

et al. 2019

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Decades after release of the first PROSPECT + SAIL (commonly called PROSAIL) versions, the model is still the most famous representative in the field of canopy reflectance modelling and has been widely used to obtain plant biochemical and structural variables, particularly in the agricultural context. The performance of the retrieval is usually assessed by quantifying the distance between the estimated and the in situ measured variables. While this has worked for hundreds of studies that obtained canopy density as a one-sided Leaf Area Index (LAI) or pigment content, little is known about the role of the canopy geometrical properties specified as the Average Leaf Inclination Angle (ALIA). In this study, we exploit an extensive field dataset, including narrow-band field spectra, leaf variables and canopy properties recorded in seven individual campaigns for winter wheat (4x) and silage maize (3x). PROSAIL outputs generally did not represent field spectra well, when in situ variables served as input for the model. A manual fitting of ALIA and leaf water (EWT) revealed significant deviations for both variables (RMSE = 14.5°, 0.020 cm) and an additional fitting of the brown leaf pigments (Cbrown) was necessary to obtain matching spectra at the near infrared (NIR) shoulder. Wheat spectra tend to be underestimated by the model until the emergence of inflorescence when PROSAIL begins to overestimate crop reflectance. This seasonal pattern could be attributed to an attenuated development of ALIAopt compared to in situ measured ALIA. Segmentation of nadir images of wheat was further used to separate spectral contributors into dark background, ears and leaves + stalks. It could be shown that the share of visible fruit ears from nadir view correlates positively with the deviations between field spectral measurement and PROSAIL spectral outputs (R² = 0.78 for aggregation by phenological stages), indicating that retrieval errors increase for ripening stages. An appropriate model parameterization is recommended to assure accurate retrievals of biophysical and biochemical products of interest. The interpretation of inverted ALIA as physical leaf inclinations is considered unfeasible and we argue in favour of treating it as a free calibration parameter.

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“…In particular, the Environmental Mapping and Analysis Program (EnMAP) is a German mission which will measure in the VSWIR spectral range with an average spectral sampling of 10 nm, a 30 m GSD, a 30 km swath width and a revisit time under quasi-nadir observation of less than 4 weeks (Guanter et al, 2015). These characteristics are shared by the Italian Space Agency's PRISMA (Hyperspectral Precursor of the Application Mission) (Candela et al, 2016), which in addition presents a panchromatic channel with a 5 m GSD. Other projects, such as NASA's Hyperspectral Infrared Imager (HyspIRI) (Lee et al, 2015), and the Italian-Israeli SHALOM (Spaceborne Hyperspectral Applicative Land and Ocean Mission), currently awaiting the final decision for implementation, could follow EnMAP and PRISMA by mid 2020s.…”

Section: Introductionmentioning

confidence: 99%

“…The combination of optical IS and MS missions can thus be used for a temporal and/or spatial enhancement of the rich spectral information provided by the IS data set. This is also the rationale for the inclusion of a panchromatic channel in the PRISMA mission concept (Candela et al, 2016) and for the joint deployment of Hyperion and the Advanced Land Imager (ALI) onboard the EO-1 platform.…”

Section: Introductionmentioning

confidence: 99%

Synergies of Spaceborne Imaging Spectroscopy with Other Remote Sensing Approaches

et al. 2018

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Imaging spectroscopy (IS), also commonly known as hyperspectral remote sensing, is a powerful remote sensing technique for the monitoring of the Earth's surface and atmosphere. Pixels in optical hyperspectral images consist of continuous reflectance spectra formed by hundreds of narrow spectral channels, allowing an accurate representation of the surface composition through spectroscopic techniques. However, technical constraints in the definition of imaging spectrometers make spectral coverage and resolution to be usually traded by spatial resolution and swath width, as opposed to optical multispectral (MS) systems typically designed to maximize spatial and/or temporal resolution. This complementarity suggests that a synergistic exploitation of spaceborne IS and MS data would be an optimal way to fulfill those remote sensing applications requiring not only high spatial and temporal resolution data, but also rich spectral information. On the other hand, IS has been shown to yield a strong synergistic potential with non-optical remote sensing methods, such as thermal infrared (TIR) and light detection and ranging (LiDAR). In this contribution we review theoretical and methodological aspects of potential synergies between optical IS and other remote sensing techniques. The focus is put on the evaluation of synergies between spaceborne optical IS and MS systems because of the expected availability of the two types of data in the next years. Short reviews of potential synergies of IS with TIR and LiDAR measurements are also provided.

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The PRISMA mission

Cited by 38 publications

References 0 publications

First Evaluation of PRISMA Level 1 Data for Water Applications

First Evaluation of PRISMA Level 1 Data for Water Applications

Fitted PROSAIL Parameterization of Leaf Inclinations, Water Content and Brown Pigment Content for Winter Wheat and Maize Canopies

Synergies of Spaceborne Imaging Spectroscopy with Other Remote Sensing Approaches

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