Search results for " Remote"

Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory

2018

International audience; Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability ('p-theory'), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types.…

Sandbar shark aggregation in the central Mediterranean Sea and potential effects of tourism

2021

An aggregation of sandbar sharks Carcharhinus plumbeus occurs every summer around the remote uninhabited islet of Lampione (Pelagie Islands Marine Protected Area, south-western Mediterranean Sea), attracting an increasing number of tourists for a shark watching experience. Despite the ecological and socio-economic importance of this rare occurrence in Mediterranean waters, there is a lack of scientific data and lack of information as to the potential impact of tourist activities on the presence and behaviour of this shark species. Using baited underwater videos, this study provides the first assessment of this shark aggregation, as well as a preliminary evaluation of the potential effects t…

Advanced methods of plant disease detection. A review

2014

International audience; Plant diseases are responsible for major economic losses in the agricultural industry worldwide. Monitoring plant health and detecting pathogen early are essential to reduce disease spread and facilitate effective management practices. DNA-based and serological methods now provide essential tools for accurate plant disease diagnosis, in addition to the traditional visual scouting for symptoms. Although DNA-based and serological methods have revolutionized plant disease detection, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic diffusion. They need at least 1–2 days for sample harvest, processing, and analysis. Here, we d…

A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data

2018

This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then a…

Planktonic stages of small pelagic fishes (Sardinella aurita and Engraulis encrasicolus) in the central Mediterranean Sea: The key role of physical f…

2018

Abstract Multidisciplinary studies are recently aiming to define diagnostic tools for fishery sustainability by coupling ichthyoplanktonic datasets, physical and bio-geochemical oceanographic measurements, and ocean modelling. The main goal of these efforts is to understand those processes that control the dispersion and fate of fish larvae and eggs, and thus tuning the inter-annual variability of the biomass of small pelagic fish species. In this paper we analyse the distribution of eggs and larvae as well as the biological features of the two species of pelagic fish, Engraulis encrasicolus and Sardinella aurita in the north-eastern sector of the Sicily Channel (Mediterranean Sea) from ich…

Multitemporal unmixing of MERIS FR data

2007

Evapotranspiration from an Olive Orchard using Remote Sensing-Based Dual Crop Coefficient Approach

2013

A remote sensing-based approach to estimate actual evapotranspiration (ET) was tested in an area covered by olive trees and characterized by Mediterranean climate. The methodology is a modified version of the standard FAO-56 dual crop coefficient procedure, in which the crop potential transpiration, T p, is obtained by directly applying the Penman-Monteith (PM) equation with actual canopy characteristics (i.e., leaf area index, albedo and canopy height) derived from optical remote sensing data. Due to the minimum requirement of in-situ ancillary inputs, the methodology is suitable also for applications on large areas where the use of tabled crop coefficient values become problematic, due to…

Applications of a remote sensing-based two-source energy balance algorithm for mapping surface fluxes without in situ air temperature observations

2012

Abstract The two-source energy balance (TSEB) model uses remotely sensed maps of land–surface temperature (LST) along with local air temperature estimates at a nominal blending height to model heat and water fluxes across a landscape, partitioned between dual sources of canopy and soil. For operational implementation of TSEB, however, it is often difficult to obtain representative air temperature data that are compatible with the LST retrievals, which may themselves have residual errors due to atmospheric and emissivity corrections. To address this issue, two different strategies in applying the TSEB model without requiring local air temperature data were tested over a typical Mediterranean…

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 …

Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators

2021

One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…