Search results for "forest"
showing 10 items of 3780 documents
Discussion of “Laboratory and field calibration of the Diviner 2000 probe in two types of soil” by J. Haberland, PhD, R. Galvez, C. Kremer, PhD, and …
2014
The authors deal with the quite interesting and actual problem of Diviner 2000 capacitance probe calibration and present some field and laboratory data obtained on two different layers (0-0.26 cm and 0.26-0.50 cm) of the same soil profile, characterized by different textural class. The importance of site-specific calibration of sensors used to monitor soil or plant water status assumes a particular relevance in semi-arid environments where the application of precision irrigation represents an appropriate management strategy aimed to achieve high values of water use efficiency (Cammalleri et al., 2013). Moreover in clay soils, physical properties are strongly influenced by soil water content…
Assessment of a calibration procedure to estimate soil water content with Sentek Diviner 2000 capacitance probe
2012
Retrieval of Case 2 Water Quality Parameters with Machine Learning
2018
Water quality parameters are derived applying several machine learning regression methods on the Case2eXtreme dataset (C2X). The used data are based on Hydrolight in-water radiative transfer simulations at Sentinel-3 OLCI wavebands, and the application is done exclusively for absorbing waters with high concentrations of coloured dissolved organic matter (CDOM). The regression approaches are: regularized linear, random forest, Kernel ridge, Gaussian process and support vector regressors. The validation is made with and an independent simulation dataset. A comparison with the OLCI Neural Network Swarm (ONSS) is made as well. The best approached is applied to a sample scene and compared with t…
Retrieval of coloured dissolved organic matter with machine learning methods
2017
The coloured dissolved organic matter (CDOM) concentration is the standard measure of humic substance in natural waters. CDOM measurements by remote sensing is calculated using the absorption coefficient (a) at a certain wavelength (e.g. 440nm). This paper presents a comparison of four machine learning methods for the retrieval of CDOM from remote sensing signals: regularized linear regression (RLR), random forest (RF), kernel ridge regression (KRR) and Gaussian process regression (GPR). Results are compared with the established polynomial regression algorithms. RLR is revealed as the simplest and most efficient method, followed closely by its nonlinear counterpart KRR.
Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications
2019
Medical applications challenge today's text categorization techniques by demanding both high accuracy and ease-of-interpretation. Although deep learning has provided a leap ahead in accuracy, this leap comes at the sacrifice of interpretability. To address this accuracy-interpretability challenge, we here introduce, for the first time, a text categorization approach that leverages the recently introduced Tsetlin Machine. In all brevity, we represent the terms of a text as propositional variables. From these, we capture categories using simple propositional formulae, such as: if "rash" and "reaction" and "penicillin" then Allergy. The Tsetlin Machine learns these formulae from a labelled tex…
Reliability analysis of processes with moving cracked material
2015
Abstract The reliability of processes with moving elastic and isotropic material containing initial cracks is considered in terms of fracture. The material is modelled as a moving plate which is simply supported from two of its sides and subjected to homogeneous tension acting in the travelling direction. For tension, two models are studied: (i) tension is constant with respect to time, and (ii) tension varies temporally according to an Ornstein–Uhlenbeck process. Cracks of random length are assumed to occur in the material according to a stochastic counting process. For a general counting process, a representation of the nonfracture probability of the system is obtained that exploits condi…
ECOLOGICAL FEATURES OF MACROMYCETES IN EUCALYPTUS REFORESTATIONS IN SICILY (SOUTHERN ITALY)
2009
The objective of this work was to compare and estimate the ecological features of 192 macromycetes, including nine hypogeous and three semi-hypogeous fungi, collected in Sicilian areas reforested with Eucalyptus. The number of mycorrhizal fungi turned out to be only 22 % of the taxa recorded so far from other areas, and this underlines the difficulties of eucalyptus trees in adapting to the pedological and climatic conditions of Sicily.
Choice between alternative investments in agriculture: The role of organic farming to avoid the abandonment of rural areas
2015
Abstract Sicily has a long tradition in citrus fruit cultivation that, with vineyard and olive tree, represents the main Mediterranean tree crops. Since many Sicilian farmers in recent years have decided to abandon conventional lemon orchards, in this paper we have evaluated the financial sustainability of organic lemon production by comparing it with the conventional one. Financial analysis has been carried out in a case study on the northwestern coast of Sicily, considering a 50-year economic life of an orchard. The results, per hectare of area, showed a clear advantage of organic lemon orchard. This was due to fewer labor requirements and to greater market appreciation for organic produc…