Search results for "Hyperspectral"
showing 10 items of 271 documents
Performance of Spectral Fitting Methods for vegetation fluorescence quantification
2010
The Fraunhofer Line Discriminator (FLD) principle has long been considered as the reference method to quantify solar-induced chlorophyll fluorescence (F) from passive remote sensing measurements. Recently, alternative retrieval algorithms based on the spectral fitting of hyperspectral radiance observations, Spectral Fitting Methods (SFMs), have been proposed. The aim of this manuscript is to investigate the performance of such algorithms and to provide relevant information regarding their use. FLD and SFMs were used to estimate F starting from Top Of Canopy (TOC) fluxes at very high spectral resolution (0.12 nm) and sampling interval (0.1 nm), exploiting the O2-B (687.0 nm) and O2-A (760.6 …
Discrimination of astringent and deastringed hard ‘Rojo Brillante’ persimmon fruit using a sensory threshold by means of hyperspectral imaging
2019
[EN] Persimmon fruit cv. 'Rojo Brillante' is an astringent cultivar due to its content of soluble tannins, which are insolubilised during the ripening of the fruit. Traditionally, the consumption of this cultivar has only been possible when the fruit is overripe and the texture is soft. Postharvest treatments based on exposing fruits to high CO2 concentrations allow astringency removal while preserving high flesh firmness. However, the effectiveness of this treatment is controlled by means of slow destructive methods. The aim of this work is to study the application of hyperspectral imaging in the spectral range 450-1040 nm to discriminate astringent (A) and deastringed (DA) fruits non-dest…
A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data
2021
The current exponential increase of spatiotemporally explicit data streams from satellite-based Earth observation missions offers promising opportunities for global vegetation monitoring. Intelligent sampling through active learning (AL) heuristics provides a pathway for fast inference of essential vegetation variables by means of hybrid retrieval approaches, i.e., machine learning regression algorithms trained by radiative transfer model (RTM) simulations. In this study we summarize AL theory and perform a brief systematic literature survey about AL heuristics used in the context of Earth observation regression problems over terrestrial targets. Across all relevant studies it appeared that…
A Survey on Gaussian Processes for Earth-Observation Data Analysis: A Comprehensive Investigation
2016
Gaussian processes (GPs) have experienced tremendous success in biogeophysical parameter retrieval in the last few years. GPs constitute a solid Bayesian framework to consistently formulate many function approximation problems. This article reviews the main theoretical GP developments in the field, considering new algorithms that respect signal and noise characteristics, extract knowledge via automatic relevance kernels to yield feature rankings automatically, and allow applicability of associated uncertainty intervals to transport GP models in space and time that can be used to uncover causal relations between variables and can encode physically meaningful prior knowledge via radiative tra…
EAGLE 2006 - Multi-purpose, multi-angle and multi-sensor in-situ and airborne campaigns over grassland and forest
2009
EAGLE2006 – an intensive field campaign for the advances in land surface hydrometeorological processes – was carried out in the Netherlands from 8th to 18th June 2006, involving 16 institutions with in total 67 people from 16 different countries. In addition to the acquisition of multi-angle and multi-sensor satellite data, several airborne instruments – an optical imaging sensor, an imaging microwave radiometer, and a flux airplane – were deployed and extensive ground measurements were conducted over one grassland site at Cabauw and two forest sites at Loobos and Speulderbos in the central part of the Netherlands. The generated data set is both unique and urgently needed for the developmen…
Optical types of inland and coastal waters
2017
Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in-water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of condi…
Advances in Kernel Machines for Image Classification and Biophysical Parameter Retrieval
2017
Remote sensing data analysis is knowing an unprecedented upswing fostered by the activities of the public and private sectors of geospatial and environmental data analysis. Modern imaging sensors offer the necessary spatial and spectral information to tackle a wide range problems through Earth Observation, such as land cover and use updating, urban dynamics, or vegetation and crop monitoring. In the upcoming years even richer information will be available: more sophisticated hyperspectral sensors with high spectral resolution, multispectral sensors with sub-metric spatial detail or drones that can be deployed in very short time lapses. Besides such opportunities, these new and wealthy infor…
First results from the PROBA/CHRIS hyperspectral/multiangular satellite system over land and water targets
2005
The Project for On-Board Autonomy (PROBA) platform developed by the European Space Agency was launched on October 22, 2001. The instrument payload includes the Compact High Resolution Imaging Spectrometer (CHRIS). The coupled system provides high spatial resolution hyperspectral/multi-angular data, which represents a new-generation source of information for Earth observation purposes. The first results obtained from the preprocessing (noise removal and geometric/atmospheric correction) of two different datasets, collected over agricultural crops and inland waters, are presented in this letter. In situ measurements are used to assess the quality of the data and to validate the processing alg…
CHRIS/PROBA toolbox for hyperspectral and multiangular data exploitations
2009
The project CHRIS/Proba Toolbox for BEAM (CHRIS-Box) has been developed in order to support users of data from the CHRIS sensor onboard of ESA's Proba platform. BEAM and the CHRIS-Box are user tools which ESA/ESRTN are providing free of charge to the Earth Observation Community. The CHRIS-Box software provides extensions for BEAM that allows accomplishing the following tasks: a) Noise reduction to remove the vertical striping and other noise present in CHRIS response-corrected images; b) Cloud screening to mark cloudy pixels in CHRIS noise-corrected images; the cloud screening algorithm provides cloud probability and abundances for each pixel; c) Atmospheric correction that provides surface…
EAGLE 2006 – multi-purpose, multi-angle and multi-sensor in-situ, airborne and space borne campaigns over grassland and forest
2009
Abstract. EAGLE2006 – an intensive field campaign for the advances in land surface hydrometeorological processes – was carried out in the Netherlands from 8 to 18 June 2006, involving 16 institutions with in total 67 people from 16 different countries. In addition to the acquisition of multi-angle and multi-sensor satellite data, several airborne instruments – an optical imaging sensor, an imaging microwave radiometer, and a flux airplane – were deployed and extensive ground measurements were conducted over one grassland site at Cabauw and two forest sites at Loobos and Speulderbos in the central part of the Netherlands. The generated data set is both unique and urgently needed for the deve…