Setting Up Optimal Meteorological Networks: An Example From Italy

2021 ◽  
Author(s):  
Rita Aromolo ◽  
Valerio Moretti ◽  
Tiziano Sorgi
Keyword(s):  
Sustainable Forest Management ◽  
Meteorological Data ◽  
Descriptive Statistics ◽  
Relative Importance ◽  
Forest Resource ◽  
Climate Regime ◽  
Site Specific ◽  
Forest Resource Management ◽  
Plot Sampling ◽  
Forest Sites

A permanent assessment of climate regime in forest sites has a key role in forest resource conservation and preservation of ecosystem services, biodiversity and landscape multi-functionality, informing sustainable forest management. In this view, time-series of meteorological data relative to several monitoring sites from the ICP-Forest network in Italy, were analyzed with the aim to define the number of site-specific observations, which can be considered adequate for further analysis on forest resource management. The relative importance of each factor accounted in our analysis (season, year, variable, plot, sampling proportion) was investigated comparing results through the use of descriptive statistics.

scholarly journals Forest Resource Management: An Empirical Study in Northern Pakistan

2021 ◽  
Vol 13 (16) ◽  
pp. 8752
Author(s):  
Sajjad Ali ◽  
Dake Wang ◽  
Talib Hussain ◽  
Xiaocong Lu ◽  
Mohammad Nurunnabi
Keyword(s):  
Resource Management ◽  
Forest Management ◽  
Goodness Of Fit ◽  
Sustainable Forest Management ◽  
Local Level ◽  
Forest Resources ◽  
Equation Modeling ◽  
Forest Resource ◽  
Factors Affecting ◽  
Forest Resource Management

Community participation for forest sustainability and use of forest resources for community development is considered a vital way in all societies. This study was conducted to assess the public views toward sustainable forest management in the area of Gilgit–Baltistan, Pakistan, through collecting data from 255 respondents. Views about forest management techniques at different levels were discussed. Three main areas of focus to manage forest resources were: strategic-level management, local-level management, and communication-level management. To provide confidence and to measure factors affecting sustainable forest management, this study applied the structural equation modeling approach and built a model that explained and identified the critical factors affecting sustainable forest management. A quantitative approach via Smart Partial Least Squares version 3.2.8 was used for analysis. The findings of the study show that the R2 value of the model was 0.653, which means that the three exogenous latent constructs collectively explained 65.3% of the variance in sustainable forest management. In this study, the goodness of fit of the model was 0.431, which is considered valid for further analysis. Among the three proposed levels for forest management, the strategic-level-management factor was found the most important of the three variables. This study concluded that for better and sustainable forest management, policies should flow from the strategic level to the local and also focus on communication-level management because all these factors appear to be significant in measuring sustainable forest management. Community engagement and awareness are also found to be an important way for forest resource management.

scholarly journals Standortkartierung im Lehr- und Forschungswald der ETH in Sedrun | Site mapping in the ETH Research Forest of Sedrun

2009 ◽  
Vol 160 (2) ◽  
pp. 27-36
Author(s):  
Jacques Doutaz ◽  
Hans-Ulrich Frey ◽  
Harald Bugmann
Keyword(s):  
Classification System ◽  
Sustainable Forest Management ◽  
Structural Characteristics ◽  
Site Classification ◽  
Classification Methods ◽  
Site Type ◽  
Forest Sites ◽  
Site Mapping ◽  
A Site ◽  
Site Types

Phytosociology has advanced in various respects since the fundamental groundwork was laid, which was mainly concerned with developing a classification system of vegetation units. Current site classification methods for forests consider not only floristic aspects, but also pedological, topographic and structural characteristics of forest stands. During the summer of 2007, a site mapping was carried out in the ETH Research Forest near Sedrun (Switzerland). This paper describes the methods employed, and it evaluates the applicability thereof based on case studies. Site mapping is based on expert opinion, and as such it includes a certain degree of generalization and subjectivity in the evaluation of stands and their assignment to a site type. However, we propose that site classification constitutes a suitable tool for describing and characterizing the complexity of forest sites. The accurate description of site types strongly facilitates the interpretation and the applicability of a classification system in decision support for sustainable forest management.

Honor and Human Rights: A Comparative Study of Russia and Ukraine

2016 ◽  
Vol 15 (6) ◽  
pp. 669-698 ◽  
Author(s):  
Anton Oleinik
Keyword(s):  
Human Rights ◽  
Human Dignity ◽  
Russian Language ◽  
Descriptive Statistics ◽  
Relative Importance ◽  
Two Cultures ◽  
Quantitative Content ◽  
The Two Cultures ◽  
The Russian Language ◽  
Representative Samples

This article discusses the relative importance attached to honor and human rights in two cultures, Russian and Ukrainian. These cultures have elements of honor cultures, both historically and in the present. There are also elements of a more universalistic interpretation of human dignity that are expressed through the concept of human rights, especially in the case of Ukraine. However, the movement towards the universalistic understanding of human dignity slows down or may even be reversed in the context of a protracted war. Two sources of data inform the analysis: primary (two surveys conducted on representative samples in Russia, N = 1602, and Ukraine, N = 2020) and secondary (the complete works of two poets considered representative of the two cultures, A. Pushkin and T. Shevchenko, as well as documents in the Russian-language and Ukrainian-language segments of the Google online databank). The data were processed using methods of descriptive statistics, binary statistic regression and quantitative content analysis.

scholarly journals A Novel Framework for Selecting Informative Meteorological Stations Using Monte Carlo Feature Selection (MCFS) Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Rizwan Niaz ◽  
Ibrahim M. Almanjahie ◽  
Zulfiqar Ali ◽  
Muhammad Faisal ◽  
Ijaz Hussain
Keyword(s):  
Monte Carlo ◽  
Feature Selection ◽  
Significant Role ◽  
Meteorological Data ◽  
Accurate Estimation ◽  
Relative Importance ◽  
Drought Prediction ◽  
Monte Carlo Feature Selection ◽  
Remaining Time ◽  
Scale Data

Spatial distribution of meteorological stations has a significant role in hydrological research. The meteorological data play a significant role in drought monitoring; in this regard, accurate and suitable provision of meteorological stations is becoming crucial to improve and strengthen the skill of drought prediction. In this perspective, the choice of meteorological stations in a specific region has substantial importance for accurate estimation and continuous monitoring of drought hazards at the regional level. However, installation and data mining on a large number of meteorological stations require high cost and resources. Therefore, it is necessary to rank and find dependencies among existing meteorological stations in a particular region for further climatological analysis and reanalysis of databases. In this paper, the Monte Carlo feature selection and interdependency discovery (MCFS-ID) algorithm-based framework is proposed to identify the important meteorological station in a particular region. We applied the proposed framework on 12 meteorological stations situated in varying climatological regions of Punjab (Pakistan). We employed the drought index SPTI on 1-, 3-, 6-, 9-, 12-, 24-, and 48-month time-scale data to find the interdependencies among meteorological stations at various locations. We found that Sialkot has significance regional importance for studying SPTI-3, SPTI-6, and SPTI-48 indices. This regional importance is based on scores of relative importance (RI); for example, the RI values for SPTI-3, SPTI-6, and SPTI-48 indices are 0.1570, 0.1080, and 0.0270, respectively. Furthermore, the Jhelum station has more relative importance (RI = 0.1410 and 0.1030) for SPTI-1 and SPTI-9 indices, while varying concentration behaviour is observed in the remaining time scales.

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