Search results for "support"
showing 10 items of 2310 documents
Comparison of gap-filling techniques applied to the CCI soil moisture database in Southern Europe
2021
Abstract Soil moisture (SM) is a key variable that plays an important role in land-atmosphere interactions. Monitoring SM is crucial for many applications and can help to determine the impact of climate change. Therefore, it is essential to have continuous and long-term databases for this variable. Satellite missions have contributed to this; however, the continuity of the series is compromised due to the data gaps derived by different factors, including revisit time, presence of seasonal ice or Radio Frequency Interference (RFI) contamination. In this work, the applicability of different gap-filling techniques is evaluated on the ESA Climate Change Initiative (CCI) SM combined product, whi…
Bright Hot Impacts by Erupted Fragments Falling Back on the Sun: Magnetic Channelling
2016
Dense plasma fragments were observed to fall back on the solar surface by the Solar Dynamics Observatory after an eruption on 7 June 2011, producing strong EUV brightenings. Previous studies investigated impacts in regions of weak magnetic field. Here we model the $\sim~300$ km/s impact of fragments channelled by the magnetic field close to active regions. In the observations, the magnetic channel brightens before the fragment impact. We use a 3D-MHD model of spherical blobs downfalling in a magnetized atmosphere. The blob parameters are constrained from the observation. We run numerical simulations with different ambient density and magnetic field intensity. We compare the model emission i…
Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations
2021
Abstract Estimation of Green Area Index (GAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) from decametric satellites was investigated in this study using a large database of ground measurements over croplands. It covers six main crop types including rice, corn, wheat and barley, sunflower, soybean and other types of crops. Ground measurements were completed using either digital hemispherical cameras, LAI-2000 or AccuPAR devices over sites representative of a decametric pixel. Sites were spread over the globe and the data collected at several growth stages concurrently to the acquisition of Landsat-8 images. Several machine learning techniques were investigated to re…
Evaluation of image processing technique as an expert system in mulberry fruit grading based on ripeness level using artificial neural networks (ANNs…
2020
Abstract Image processing and artificial intelligence (AI) techniques have been applied to analyze, evaluate and classify mulberry fruit according to their ripeness (unripe, ripe, and overripe). A total of 577 mulberries were graded by an expert and the images were captured by an imaging system. Then, the geometrical properties, color, and texture characteristics of each segmented mulberry was extracted using two feature reduction methods: Correlation-based Feature Selection subset (CFS) and Consistency subset (CONS). Artificial Neural Networks (ANN) and Support Vector Machine (SVM) were applied to classify mulberry fruit. ANN classification with the CFS subset feature extraction method res…
Diversion of Fishing Pressure on the Economically Important Species Barbus barbus (Linnaeus, 1758) to Protect the Community Interest Congeneric Barbu…
2018
Abstract The ADONIS:CE instrument has been used in the field of congeners species, Barbus barbus – of economic interest and Barbus meridionalis – of conservation interest, to build a support-system model for management decision-making. Analysis of the habitat needs and the indicators for favorable conservation status have identified pressures and threats to these fish species for which management actions have been proposed. This management system favors the decrease of fishing pressure on Barbus meridionalis species by its transfer to Barbus barbus species.
Management Elements for Two Alburninae Species, Alburnus alburnus (Linnaeus, 1758) and Alburnoides bipunctatus (Bloch, 1782) Based on a Decision-Supp…
2019
Abstract ADONIS:CE has been used as a base to create a support-system management decision-making model for Alburnus alburnus (Linnaeus, 1758) and Alburnoides bipunctatus (Bloch, 1782) species. Investigation of the habitat necessities and the identification of the necessary elements for a good status of conservation of these two fish species populations has revealed the pressures and threats to these congener species, for which specific management activities have been finally recommended.
Decision support systems (DSS) for wastewater treatment plants - A review of the state of the art.
2019
The use of decision support systems (DSS) allows integrating all the issues related with sustainable development in view of providing a useful support to solve multi-scenario problems. In this work an extensive review on the DSSs applied to wastewater treatment plants (WWTPs) is presented. The main aim of the work is to provide an updated compendium on DSSs in view of supporting researchers and engineers on the selection of the most suitable method to address their management/operation/design problems. Results showed that DSSs were mostly used as a comprehensive tool that is capable of integrating several data and a multi-criteria perspective in order to provide more reliable results. Only …
A bark beetle infestation predictive model based on satellite data in the frame of decision support system TANABBO
2020
The European spruce bark beetle Ips typographus L. causes significant economic losses in managed coniferous forests in Central and Northern Europe. New infestations either occur in previously undisturbed forest stands (i.e., spot initiation) or depend on proximity to previous years’ infestations (i.e., spot spreading). Early identification of newly infested trees over the forested landscape limits the effective control measures. Accurate forecasting of the spread of bark beetle infestation is crucial to plan efficient sanitation felling of infested trees and prevent further propagation of beetle-induced tree mortality. We created a predictive model of subsequent year spot initiation and spo…
Data-Based Forest Management with Uncertainties and Multiple Objectives
2016
In this paper, we present an approach of employing multiobjective optimization to support decision making in forest management planning. The planning is based on data representing so-called stands, each consisting of homogeneous parts of the forest, and simulations of how the trees grow in the stands under different treatment options. Forest planning concerns future decisions to be made that include uncertainty. We employ as objective functions both the expected values of incomes and biodiversity as well as the value at risk for both of these objectives. In addition, we minimize the risk level for both the income value and the biodiversity value. There is a tradeoff between the expected val…
Bitterling Populations in The Sighisoara-Târnava Mare Natura 2000 Site ‒ A Support System for Management Decisions
2016
Abstract The predominant threats to the Bitterling populations in the Sighisoara-Târnava Mare Natura 2000 site are the hydro technical modifications of the river channels, organic contamination and illegal fishing. ADONIS:CE is applied commonly for business processes modelling, however, in this study case was applied in an ecology/biology sphere of interest. The authors acquired a Bitterling model which contained all of the identified habitat species’ necessities, the specific indicators that give good preservation status and the present pressures and threats. The keeping of the riverbed morphodynamics is especially necessary - the meanders existence is significant for the aquatic mollusc s…