Estimation of canopy attributes in beech forests using true colourdigital images from a small fixed-wing UAV

Accurate estimates of forest canopy are essential for the characterization of forest ecosystems. Remotely-sensed techniques provide a unique way to obtain estimates over spatially extensive areas, but their application is limited by the spectral and temporal resolution available from these systems, which is often not suited to meet regional or local objectives. The use of unmanned aerial vehicles (UAV) as remote sensing platforms has recently gained increasing attention, but their applications in forestry are still at an experimental stage. In this study we described a methodology to obtain rapid and reliable estimates of forest canopy from a small UAV equipped with a commercial RGB camera. The red, green and blue digital numbers were converted to the green leaf algorithm (GLA)and to the CIE L∗a∗b∗colour space to obtaine stimates of canopy cover, foliage clumping and leaf area index (L) from aerial images. Canopy attributes were compared with in situ estimates obtained from two digital canopy photographic techniques (cover and fisheye photography).The method was tested in beech forests. UAV images accurately quantified canopy cover even in very dense stand conditions, despite a tendency to not detecting small within-crown gaps in aerial images, leading to a measurement of a quantity much closer to crown cover estimated from in situ cover photography. Estimates of L from UAV images significantly agreed with that obtained from fisheye images, but the accuracy of UAV estimates is influenced by the appropriate assumption of leaf angle distribution. We concluded that true colour UAV images can be effectively used to obtain rapid, cheap and meaningful estimates of forest canopy attributes at medium-large scales. UAV can combine the advantage of high resolution imagery with quick turnaround series, being therefore suitable for routine forest stand monitoring and real-time applications.L'articolo è disponibile sul sito dell'editore www.elsevier.com/locate/ja

Detection and Quantitative Analysis of Two Independent Binding Modes of a Small Ligand Responsible for DC-SIGN Clustering

DC-SIGN (dendritic cell-specific ICAM-3 grabbing non-integrin) is a C-type lectin receptor (CLRs) present, mainly in dendritic cells (DCs), as one of the major pattern recognition receptors (PRRs). This receptor has a relevant role in viral infection processes. Recent approaches aiming to block DC-SIGN have been presented as attractive anti-HIV strategies. DC-SIGN binds mannose or fucose-containing carbohydrates from viral proteins such as the HIV envelope glycoprotein gp120. We have previously demonstrated that multivalent dendrons bearing multiple copies of glycomimetic ligands were able to inhibit DC-SIGN-dependent HIV infection in cervical explant models. Optimization of glycomimetic ligands requires detailed characterization and analysis of their binding modes because they notably influence binding affinities. In a previous study we characterized the binding mode of DC-SIGN with ligand 1, which shows a single binding mode as demonstrated by NMR and X-ray crystallography. In this work we report the binding studies of DC-SIGN with pseudotrisaccharide 2, which has a larger affinity. Their binding was analysed by TR-NOESY and STD NMR experiments, combined with the CORCEMA-ST protocol and molecular modelling. These studies demonstrate that in solution the complex cannot be explained by a single binding mode. We describe the ensemble of ligand bound modes that best fit the experimental data and explain the higher inhibition values found for ligand

The SURPRISE demonstrator: a super-resolved compressive instrument in the visible and medium infrared for Earth Observation

While Earth Observation (EO) data has become ever more vital to understanding the planet and addressing societal challenges, applications are still limited by revisit time and spatial resolution. Though low Earth orbit missions can achieve resolutions better than 100 m, their revisit time typically stands at several days, limiting capacity to monitor dynamic events. Geostationary (GEO) missions instead typically provide data on an hour-basis but with spatial resolution limited to 1 km, which is insufficient to understand local phenomena. In this paper, we present the SURPRISE project - recently funded in the frame of the H2020 programme – that gathers the expertise from eight partners across Europe to implement a demonstrator of a super-spectral EO payload - working in the visible (VIS) - Near Infrared (NIR) and in the Medium InfraRed (MIR) and conceived to operate from GEO platform -with enhanced performance in terms of at-ground spatial resolution, and featuring innovative on-board data processing and encryption functionalities. This goal will be achieved by using Compressive Sensing (CS) technology implemented via Spatial Light Modulators (SLM). SLM-based CS technology will be used to devise a super-resolution configuration that will be exploited to increase the at-ground spatial resolution of the payload, without increasing the number of detector’s sensing elements at the image plane. The CS approach will offer further advantages for handling large amounts of data, as is the case of superspectral payloads with wide spectral and spatial coverage. It will enable fast on-board processing of acquired data for information extraction, as well as native data encryption on top of native compression. SURPRISE develops two disruptive technologies: Compressive Sensing (CS) and Spatial Light Modulator (SLM). CS optimises data acquisition (e.g. reduced storage and transmission bandwidth requirements) and enables novel onboard processing and encryption functionalities. SLM here implements the CS paradigm and achieves a super-resolution architecture. SLM technology, at the core of the CS architecture, is addressed by: reworking and testing off-the-shelf parts in relevant environment; developing roadmap for a European SLM, micromirror array-type, with electronics suitable for space qualification. By introducing for the first time the concept of a payload with medium spatial resolution (few hundreds of meters) and near continuous revisit (hourly), SURPRISE can lead to a EO major breakthrough and complement existing operational services. CS will address the challenge of large data collection, whilst onboard processing will improve timeliness, shortening time needed to extract information from images and possibly generate alarms. Impact is relevant to industrial competitiveness, with potential for market penetration of the demonstrator and its components

A Fast Iterative Procedure for Adjacency Effects Correction on Remote Sensed Data

This paper describes a simple, iterative atmospheric correction procedure based on the MODTRAN®5 radiative transfer code. Such a procedure receives in input a spectrally resolved at-sensor radiance image, evaluates the different contributions to received radiation, and corrects the effect of adjacency from surrounding pixels permitting the retrieval of ground reflectance spectrum for each pixel of the image. The procedure output is a spectral ground reflectance image obtained without the need of any user-provided a priori hypothesis. The novelty of the proposed method relies on its iterative approach for evaluating the contribution of surrounding pixels: a first run of the atmospheric correction procedure is performed by assuming that the spectral reflectance of the surrounding pixels is equal to that of the pixel under investigation. Such information is used in the subsequent iteration steps to estimate the spectral radiance of the surrounding pixels, in order to make a more accurate evaluation of the reflectance image. The results are here presented and discussed for two different cases: synthetic images produced with the hyperspectral simulation tool PRIMUS and real images acquired by CHRIS–PROBA sensor. The retrieved reflectance error drops after a few iterations, providing a quantitative estimate for the number of iterations needed. Relative error after the procedure converges is in the order of few percent, and the causes of remaining uncertainty in retrieved spectra are discussed

Experimental Tests on TIR Multispectral Images for Temperature-Emissivity Separation by Using the MaxEnTES Algorithm

Satellite images in the TIR are relevant for several Earth Observation applications. The retrieval of temperature and emissivity from the emitted radiance, however, requires the use of suitable algorithms, such as the MaxEnTES that uses the concept of maximum entropy to solve the Temperature-Emissivity Separation problem. Here we discuss the performance of MaxEnTES when applied to TIR images with a limited number of channels, specifically simulated HyspIRI multispectral images and real multispectral images by ASTER. The results were respectively compared with the original temperatures used for the simulations and with the temperatures obtained by using the ASTER TES algorithm

Radiometric and signal-to-noise ratio properties of multiplex dispersive spectrometry

Recent theoretical investigations have shown important radiometric disadvantages of interferential multiplexing in Fourier transform spectrometry that apparently can be applied even to coded aperture spectrometers. We have reexamined the methods of noninterferential multiplexing in order to assess their signal-to-noise ratio (SNR) performance, relying on a theoretical modeling of the multiplexed signals. We are able to show that quite similar SNR and radiometric disadvantages affect multiplex dispersive spectrometry. The effect of noise on spectral estimations is discussed

Algorithms and prototyping of a compressive hyperspectral imager

Compressive sensing (CS) (Candes and Tao 2006) has recently emerged as an efficient technique for sampling a signal with fewer coefficients than dictated by classical Shannon/Nyquist theory. The assumption underlying this approach is that the signal to be sampled must have concise representation on a convenient basis, meaning that there exists a basis where the signal can be expressed with few large coefficients and many (close-to-)zero coefficients. In CS, sampling is performed by taking a number of linear projections of the signal onto pseudorandom sequences, whereas reconstruction exploits knowledge of a domain where the signal is "sparse." CS has also been used to develop innovative "compressive" imaging systems. A single-pixel camera (Compressive Sensing and Sparse Approximation s.d.) uses a single detector to sequentially acquire random linear measurements of a scene via light modulation. This kind of design is very interesting for imaging at wavelengths beyond the visible light spectrum, where manufacturing detectors is very expensive; CS could be used to design cheaper sensors or sensors providing better resolution for an equal number of detectors. This paradigm is even more appealing for spectral imaging (e.g., Barducci, et al. 2012, 2013, 2014; Magli et al. 2012), where the amount of data generated by the imaging sensor is very large and the system can benefit from a natively compressed imaging format; reconstruction of such large datasets may require ad hoc algorithms in order to fully exploit data redundancies (e.g., Coluccia et al. 2012; Kuiteing et al., 2014). Although compressive hyperspectral imaging has been studied in simulation, there are very few practical implementations; the related background is described in detail in Section 15.1.2. In this chapter, we describe a prototype implementation of a compressive hyperspectral imager, highlighting design, and data quality issues

Effect of low dose high energy O3+ Implantation on the refrective index and linear electro-optic properties in X-Cut LiNbO3: Planar optical waveguide formation and characterization

X-cut LiNbO3 crystals were implanted at room temperature by 5.0 MeV O3+ ions with doses ranging from 1.0x10^14 to 6.0x10^14 O/cm^2. Secondary ion mass spectrometry profiles of atomic species migration as well as damage profiles by the Rutherford backscattering channeling technique and refractive index variation were investigated as a function of dose and subsequent annealing conditions. Two different kinds of damage produced by oxygen implantation were seen: near-surface damage correlated to electronic stopping, which causes an increase of the extraordinary refractive index, and end-of-ion range damage generated by collision cascades, which decreases the extraordinary refractive index values. The different nature of the two kinds of damage is also seen by the different temperature conditions needed for recovery. Low loss planar optical waveguides were obtained and characterized by the prism coupling technique

Smart Design of ZnFe and ZnFe@Fe Nanoparticles for MRI-Tracked Magnetic Hyperthermia Therapy: Challenging Classical Theories of Nanoparticles Growth and Nanomagnetism

Iron Oxide Nanoparticles (IONPs) hold the potential to exert significant influence on fighting cancer through their theranostics capabilities as contrast agents (CAs) for magnetic resonance imaging (MRI) and as mediators for magnetic hyperthermia (MH). In addition, these capabilities can be improved by doping IONPs with other elements. In this work, the synthesis and characterization of single-core and alloy ZnFe novel magnetic nanoparticles (MNPs), with improved magnetic properties and more efficient magnetic-to-heat conversion, are reported. Remarkably, the results challenge classical nucleation and growth theories, which cannot fully predict the final size/shape of these nanoparticles and, consequently, their magnetic properties, implying the need for further studies to better understand the nanomagnetism phenomenon. On the other hand, leveraging the enhanced properties of these new NPs, successful tumor therapy by MH is achieved following their intravenous administration and tumor accumulation via the enhanced permeability and retention (EPR) effect. Notably, these results are obtained using a single low dose of MNPs and a single exposure to clinically suitable alternating magnetic fields (AMF). Therefore, as far as the authors are aware, for the first time, the successful application of intravenously administered MNPs for MRI-tracked MH tumor therapy in passively targeted tumor xenografts using clinically suitable conditions is demonstrated

Structural and compositional characterization of X-cut LiNbO3 crystals implanted with high energy oxygen and carbon ions

High energy implantation of medium-light elements such as oxygen and carbon was performed in X-cut LiNbO3 single crystals in order to prepare high quality optical waveguides. The compositional and damage profiles, obtained by exploiting the secondary ion mass spectrometry and Rutherford back-scattering techniques respectively, were correlated to the structural properties measured by the high resolution X-ray diffraction. This study evidences the devel- opment of tensile strain induced by the ion implantation that can contribute to the decrease of the ordinary refractive index variation through the photo-elastic effect