The PRISMA Program

Galeazzi, Claudio; Sacchetti, A.; Cisbani, A.; Babini, Gianni

doi:10.1109/igarss.2008.4779667

Cited by 54 publications

(28 citation statements)

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“…Canopy bidirectional reflectance is determined by the interactions between incoming solar radiation and the plants within the canopy, which depends on the optical and structural properties of the vegetation, the underlying soil and the illumination and viewing geometry. It is important to study these bidirectional effects because several present and upcoming sensors, such as CHRIS (Compact High Resolution Imaging Spectrometer) (Barnsley et al 2004), RapidEye (http://www.rapideye.com), EnMAP (Environmental Mapping and Analysis Program) (Stuffler et al 2007, Segl et al 2012, and PRISMA (PRecursore IperSpettrale of the application mission) (Galeazzi et al 2008), can observe the same target under different viewing and illumination geometries (possible off-nadir pointing: CHRIS ± 55° in track, RapidEye ± 25° across track, EnMAP ± 30° across track, PRISMA ± 15° across track). This faces enormous challenges in interpreting the acquired data.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Multitemporal and Hyperspectral Vegetation Canopy Bidirectional Reflectance Using Detailed Virtual 3-D Canopy Models

Kuester

Spengler

Barczi

et al. 2014

IEEE Trans. Geosci. Remote Sensing

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The influence of plant and canopy architecture on canopy bidirectional reflectance and the BRDF is subject of this study. To understand BRDF-influenced reflectance signals, this influence must be identified and quantified, which requires detailed knowledge concerning the structure and BRDF of the observed canopies. BRDF measurements of in-situ canopies are time-consuming and depend on the availability of a field goniometer. In contrast to field measurements, computer based simulations of the canopy BRDF offer an alternative approach that considers parameter-driven setups of virtual canopies under constant illumination conditions. This paper presents the HySimCaR system, which has been developed in the context of the EnMAP mission. This spectral, spatial and temporal simulation system consists of detailed virtual 3D cereal canopies of different phenological stages, whose geometries are linked to corresponding spectral information. The system enables the simulation of realistic bidirectional reflectance spectra on the basis of virtual 3D scenarios by incorporating any possible viewing position with ray tracing techniques. The parameterization of a number of canopy structure parameters, such as phenological stage, row distance and row orientation, enables the modeling of the bidirectional reflectance and based on them the approximation of the BRDF for many structurally different cereal canopies. HySimCaR has been validated with respect to structural and spectral accuracy using three cereal types, including wheat, rye and barley, and 13 different phenological stages. The results show that the virtual cereal canopies are recreated in a realistic way, and it is possible to model their detailed canopy bidirectional reflectance and their BRDF using HySimCaR.

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Section: Introductionmentioning

confidence: 99%

Simulation of Multitemporal and Hyperspectral Vegetation Canopy Bidirectional Reflectance Using Detailed Virtual 3-D Canopy Models

Kuester

Spengler

Barczi

et al. 2014

IEEE Trans. Geosci. Remote Sensing

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“…PRISMA is a medium-resolution hyperspectral imaging instrument developed under the guidance of the Italian Space Agency (ASI) Galeazzi et al (2008). Instrument specifications are listed in Table 3.…”

Section: Specific Results For Prisma-likementioning

confidence: 99%

“…In addition, two new hyperspectral missions namely: EnMAP (Environmental Mapping and Analysis Program), Kaufmann et al (2008), and PRISMA (Hyperspectral Precursor and Application Mission), Galeazzi et al (2008Galeazzi et al ( , 2009, have started. Both missions are intended to provide new observations at approximately 30 m resolution to test and improve the algorithms currently used in atmospheric studies.…”

Section: Introductionmentioning

confidence: 99%

Influence of aerosol and surface reflectance variability on hyperspectral observed radiance

2012

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Abstract. Current aerosol retrievals based on visible and near infrared remote-sensing, are prone to loss of accuracy, where the assumptions of the applied algorithm are violated. This happens mostly over land and it is related to misrepresentation of specific aerosol conditions or surface properties. New satellite missions, based on high spectral resolution instruments, such as PRISMA (Hyperspectral Precursor of the Application Mission), represent a valuable opportunity to improve the accuracy of τ a 550 retrievable from a remote-sensing system developing new atmospheric measurement techniques. This paper aims to address the potential of these new observing systems in more accurate retrieving τ a 550 , specifically over land in heterogeneous and/or homogeneous areas composed by dark and bright targets. The study shows how the variation of the hyperspectral observed radiance can be addressed to recognise a variation of τ a 550 = 0.02. The goal has been achieved by using simulated radiances by combining two aerosol models (urban and continental) and two reflecting surfaces: dark (represented by water) and bright (represented by sand) for the PRISMA instrument, considering the environmental contribution of the observed radiance, i.e., the adjacency effect. Results showed that, in the continental regime, the expected instrument sensitivity would allow for retrieval accuracy of the aerosol optical thickness at 550 nm of 0.02 or better, with a dark surface surrounded by dark areas. The study also showed that for the urban regime, the surface plays a more significant role, with a bright surface surrounded by dark areas providing favourable conditions for the aerosol load retrievals, and dark surfaces representing less suitable situations for inversion independently of the surroundings. However, over all, the results obtained provide evidence that high resolution observations of Earth spectrum between 400 and 1000 nm would allow for a significant improvement of the accuracy of the τ a 550 for anthropogenic/natural aerosols over land.

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“…Future hyperspectral sensors include Precursore Iperspettrale della Missione Operativa (PRISMA) [129], the Hyperspectral Imager Suite (HISUI) [130], the Environmental Mapping and Analysis Program (EnMap) [89], the Hyperspectral Infrared Imager (HyspIRI) [21] and the Ocean Radiometer for Carbon Assessment (ORCA), which is a prototype being designed to meet the requirements of NASA's Aerosol-Cloud-Ecosystem (ACE) and PACE missions [131]. These sensors possess high spatial and spectral resolutions, including SWIR bands with a SNR high enough to validate the black pixel assumption (see Section 6.1 for a definition) over turbid waters [132].…”

Section: Sensor Resolutionsmentioning

confidence: 99%

Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing

et al. 2015

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Accurate correction of the corrupting effects of the atmosphere and the water's surface are essential in order to obtain the optical, biological and biogeochemical properties of the water from satellite-based multi-and hyper-spectral sensors. The major challenges now for atmospheric correction are the conditions of turbid coastal and inland waters and areas in which there are strongly-absorbing aerosols. Here, we outline how these issues can be addressed, with a focus on the potential of new sensor technologies and the opportunities for the development of novel algorithms and aerosol models. We review hardware developments, which will provide qualitative and quantitative increases in spectral, spatial, radiometric and temporal data of the Earth, as well as measurements from other sources, such as the Aerosol Robotic Network for Ocean Color (AERONET-OC) stations, bio-optical sensors on Argo (Bio-Argo) floats and polarimeters. We provide an overview of the state of the art in atmospheric correction algorithms, highlight recent advances and discuss the possible potential for hyperspectral data to address the current challenges.

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The PRISMA Program

Cited by 54 publications

References 0 publications

Simulation of Multitemporal and Hyperspectral Vegetation Canopy Bidirectional Reflectance Using Detailed Virtual 3-D Canopy Models

Simulation of Multitemporal and Hyperspectral Vegetation Canopy Bidirectional Reflectance Using Detailed Virtual 3-D Canopy Models

Influence of aerosol and surface reflectance variability on hyperspectral observed radiance

Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing

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