We have recently reported on a simple, low cost, and highly stable way to convert a standard microscope into a holographic one [Opt. Express 22, 14929 (2014)]. The method, named spatially multiplexed interferometric microscopy (SMIM), proposes an off-axis holographic architecture implemented onto a regular (nonholographic) microscope with minimum modifications: the use of coherent illumination and a properly placed and selected one-dimensional diffraction grating. In this contribution, we report on the implementation of partially (temporally reduced) coherent illumination in SMIM as a way to improve quantitative phase imaging. The use of low coherence sources forces the application of phase shifting algorithm instead of off-axis holographic recording to recover the sample’s phase information but improves phase reconstruction due to coherence noise reduction. In addition, a less restrictive field of view limitation (1/2) is implemented in comparison with our previously reported scheme (1/3). The proposed modification is experimentally validated in a regular Olympus BX-60 upright microscope considering a wide range of samples (resolution test, microbeads, swine sperm cells, red blood cells, and prostate cancer cells).
The Satellite Application Facilities on Land Surface Analysis (LSA SAF) is aimed to produce and disseminate geophysical products using data from EUMETSAT satellites such as the geostationary MSG1 and the polar orbiting METOP. One of the main scientific objectives for LSA SAF validation activities is to provide the User Community with measures of uncertainty for all derived products.
In this context, this document is the first of a two-part set which proposes a consistent methodology for the validation of the LSA SAF vegetation products (LAI/FVC/fAPAR) derived from SEVIRI /MSG . The methodology includes (1) an appropriate field data sampling strategy over different test sites, (2) derivation of high-resolution biophysical variable maps over a larger area (approximately the same size as the SPOT4-HRVIR2 multispectral image) along with an associated uncertainty, and (3) up-scaling to medium and coarse (MSG) resolution scales.
This paper aims at developing the stage (1) of the methodology at the specific test site of Barrax, an agricultural area in Central Spain (39°3'N, 2°12'W), whereas the part (2) is addressed in a second document (this issue) and the part (3) will be addressed for future tasks. This work includes a detailed description along with an exhaustive analysis of the vegetation product estimates by the hemispherical camera during the SPARC'03 field campaign, which took place in July 2003 at Barrax test site. The hemispherical photographs have proved to provide accurate estimates of biophysical parameters in crop canopies with significant advantages such as the possibility to evaluate the gap fraction in all viewing direction. On the other hand, a test analysis of the (CAN-EYE) software package used for the hemispherical photographs processing was undertaken. This paper also includes the intercomparison with another ground data set collected by the optical instrument LI-COR LAI2000 during the same campaign.
This paper is the second part of two-part set which proposes a methodology in order to validate the LSA SAF vegetation products (LAI/FVC/fAPAR) derived from SEVIRI/MSG. The main objective of this methodology refers to assessing the uncertainty of SEVIRI/MSG products by analytical comparison to in situ measurements. The scaling problem is solved in this work by considering high-resolution maps in order to make the direct comparison between ground truth and coarse-resolution products. A detail description of the measurement acquisition and estimates was presented in a first document whereas the estimation of the high-resolution biophysical maps from this in situ data set is undertaken in this paper.
This work attempts to evaluate the capabilities of a geostatistical approach in the estimation of high-resolution LAI/FVC/fAPAR maps. The geostatistical approach is based on collocated cokriging, which allows to derive high-resolution maps from in situ measurements over a small area (5x5 km2), centred at Barrax test site. This technique takes into account the spatial dependence of the data, the neighbouring information, densely sampled auxiliary information and the variance estimation as opposed to empirical functions. The method has shown to be appropriate for the spatial extension of in situ measurements. An important contribution of this work is the analysis of the uncertainties associated to the method which provides an appreciation of the varying precision of the cokriged estimates due to the irregular disposition of informative points by means of the estimated variance. On the other hand, a flag image is also provided by using the convex hull tool in order to account for possible uncertainties in previous steps to the final cokriging output.
In this work we present an innovative method for retrieving vegetation variables whilst at the same time making optimal use of the new generation satellite sensors. The approach is aimed to the generation of vegetation products exploding the angular capabilities provided by the MSG/SEVIRI and EPS/AVHRR within the LSA SAF Project. The products include leaf area index (LAI) and fractional vegetation cover (FVC). The algorithm is based on the complementary use of Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) and the inversion of a light-canopy interaction model, namely DISMA (DIrectional Spectral Mixture Analysis), which combines the geometric optics of large scale canopy structure with principles of radiative transfer for volume scattering within individual crowns. Unlike VMESMA, DISMA fully accounts for additional information on directional anisotropy. The prototype has been implemented in the LSA SAF system and tested using SEVIRI synthetic data. The algorithm validation includes feasibility analyses, sensitivity assessments as well as evaluation of the prototype on SEVIRI synthetic data. The study contributes to assess the uncertainties with SEVIRI based vegetation products.
EUMETSAT has developed a network of Satellite Application Facilities (SAF) for the future Application Ground Segments for the new generation Meteosat Second Generation (MSG) and European Polar System (EPS) platforms. Our main concern in LSA SAF is to develop an operational algorithm for retrieving vegetation parameters. In particular, fractional vegetation cover (FVC) and leaf area index (LAI), which are key parameters in the description of both land-surface processes and land-atmosphere interactions. The LSA SAF vegetation products will be provided over the full MSG disk at 3-km spatial resolution with a temporal resolution of 10-days. The use of BRDF models assures that these products will be corrected of the surface anisotropy effects. The algorithm is based on the complementary use of variable and multiple endmember spectral mixture analysis (DISMA), according with the available directional sampling. Land cover map, soil type databases and the clumping index are auxiliary information in the prototype. The prototyping algorithm has been tested using both airborne POLDER data over croplands, and the POLDEr on ADEOS BRDF database. A first version of the prototype for the MSG developed on synthetic MSG data is already implemented in the LSA SAF system. In this paper, the prototyping algorithm designed to retrieve the LSA SAF vegetation products and its validation on the above mentioned data sets are presented.
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