Search results for "Hyperspectral"
showing 10 items of 271 documents
Selective Antimicrobial Effects of Curcumin@Halloysite Nanoformulation: A Caenorhabditis elegans Study
2019
Alterations in the normal gastrointestinal microbial community caused by unhealthy diet, environmental factors, and antibiotic overuse may severely affect human health and well-being. Novel antimicrobial drug formulations targeting pathogenic microflora while not affecting or even supporting symbiotic microflora are urgently needed. Here we report fabrication of a novel antimicrobial nanocontainer based on halloysite nanotubes loaded with curcumin and protected with a dextrin outer layer (HNTs+Curc/DX) and its effective use to suppress the overgrowth of pathogenic bacteria in Caenorhabditis elegans nematodes. Nanocontainers have been obtained using vacuum-facilitated loading of hydrophobic …
Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications
2009
Interest in remote sensing (RS) of solar-induced chlorophyll fluorescence (F) by terrestrial vegetation is motivated by the link of F to photosynthetic efficiency which could be exploited for large scale monitoring of plant status and functioning. Today, passive RS of F is feasible with different prototypes and commercial ground-based, airborne, and even spaceborne instruments under certain conditions. This interest is generating an increasing number of research projects linking F and RS, such as the development of new F remote retrieval techniques, the understanding of the link between the F signal and vegetation physiology and the feasibility of a satellite mission specifically designed f…
Hyperspectral techniques and GIS for archaeological investigation
2004
Aerial photos, both in colour and in black and white, have always been very important tools in archaeological surveys. Sensors, called hyperspectral, were available on the market for some years: they are able to expand the research beyond the visible area of the electromagnetic spectrum as far as the thermal infrared too. The use of these sensors, at first restricted to the applications in the traditional fields of Remote Sensing (such as, for instance, Botany, Agronomy, Geology, Hydrology), was spreading, in recent years, to some sectors, such as archaeological surveys, which were unexplored before. The presence of structures and hollows in the top subsurface is likely to cause variations …
Detecting rottenness caused by Penicillium genus fungi in citrus fruits using machine learning techniques
2012
Penicillium fungi are among the main defects that may affect the commercialization of citrus fruits. Economic losses in fruit production may become enormous if an early detection of that kind of fungi is not carried out. That early detection is usually based either on UltraViolet light carried out manually. This work presents a new approach based on hyperspectral imagery for defect segmentation. Both the physical device and the data processing (geometric corrections and band selection) are presented. Achieved results using classifiers based on Artificial Neural Networks and Decision Trees show an accuracy around 98%; it shows up the suitability of the proposed approach.
Regularized RBF Networks for Hyperspectral Data Classification
2004
In this paper, we analyze several regularized types of Radial Basis Function (RBF) Networks for crop classification using hyperspectral images. We compare the regularized RBF neural network with Support Vector Machines (SVM) using the RBF kernel, and AdaBoost Regularized (ABR) algorithm using RBF bases, in terms of accuracy and robustness. Several scenarios of increasing input space dimensionality are tested for six images containing six crop classes. Also, regularization, sparseness, and knowledge extraction are paid attention.
Land surface temperature retrieval from thermal infrared data: An assessment in the context of the Surface Processes and Ecosystem Changes Through Re…
2005
[1] SPECTRA (Surface Processes and Ecosystem Changes Through Response Analysis) is one of the core candidate missions which is being proposed for implementation in the European Space Agency (ESA) Earth Explorer program of research oriented missions. The scientific objective of the SPECTRA mission is to describe, understand, and model the role of terrestrial vegetation in the global carbon cycle and its response to climate variability under the increasing pressure of human activity. The SPECTRA satellite will embark an optical hyperspectral payload covering the solar spectral range (0.4 to 2.4 μm) and thermal infrared region (10.3 to 12.3 μm). This paper is focused on the land surface temper…
Detection of Water Stress in an Olive Orchard with Thermal Remote Sensing Imagery
2006
An investigation of the detection of water stress in non-homogeneous crop canopies such as orchards using high-spatial resolution remote sensing thermal imagery is presented. An airborne campaign was conducted with the Airborne Hyperspectral Scanner (AHS) acquiring imagery in 38 spectral bands in the 0.43–12.5 mm spectral range at 2.5 m spatial resolution. The AHS sensor was flown at 7:30, 9:30 and 12:30 GMT in 25 July 2004 over an olive orchard with three different water-deficit irrigation treatments to study the spatial and diurnal variability of temperature as a function of water stress. A total of 10 AHS bands located within the thermal-infrared region were assessed for the retrieval of…
Hyperspectral response of agronomic variables to background optical variability: Results of a numerical experiment
2022
Understanding how biophysical and biochemical variables contribute to the spectral characteristics of vegetation canopies is critical for their monitoring. Quantifying these contributions, however, remains difficult due to extraneous factors such as the spectral variability of canopy background materials, including soil/crop-residue moisture, soil-type, and non-photosynthetic vegetation (NPV). This study focused on exploring the spectral response of two important agronomic variables (1) leaf chlorophyll content (Cab ) and (2) leaf area index (LAI) under various canopy backgrounds through a global sensitivity analysis of wheat-like canopy spectra simulated using the physically-based PROSAIL …
Multi-fidelity Gaussian Process Emulation for Atmospheric Radiative Transfer Models
2023
This repository contains several datasets of spectral atmospheric transfer functions (i.e. path radiance, transmittances, spherical albedo) simulated with MODTRAN6 atmospheric radiative transfer model. The simulations are stored in hdf5 files using the Atmospheric Look-up table Generator (ALG) toolbox (https://doi.org/10.5194/gmd-13-1945-2020). Each dataset has an associated .xml file that includes the configuration of ALG/MODTRAN6 executions. All datasets include the input atmospheric/geometric variables that are summarized in the following table. Each dataset file has a random distribution (based on latin hypercube sampling) these input variables with varying number of points (e.g. train5…
Optimizing LUT-based radiative transfer model inversion for retrieval of biophysical parameters using hyperspectral data
2012
Inversion of radiative transfer models using a lookup-table (LUT) approach against hyperspectral data streams leads to retrievals of biophysical parameters such as chlorophyll content (Chl), but necessary optimization strategies are not consolidated yet. Here, various regularization options have been evaluated to the benefit of improved Chl retrieval from hyperspectral CHRIS data, being: i) the role of added noise, ii) the role of multiple best solutions, and iii) the role of applied cost functions in LUT-based inversion. By using data from the ESA-led field campaign SPARC (Barrax, Spain), it was found that introducing noise and opting for multiple best solutions in the inversion considerab…