7 resultados para spatial trend analysis

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Precision horticulture and spatial analysis applied to orchards are a growing and evolving part of precision agriculture technology. The aim of this discipline is to reduce production costs by monitoring and analysing orchard-derived information to improve crop performance in an environmentally sound manner. Georeferencing and geostatistical analysis coupled to point-specific data mining allow to devise and implement management decisions tailored within the single orchard. Potential applications range from the opportunity to verify in real time along the season the effectiveness of cultural practices to achieve the production targets in terms of fruit size, number, yield and, in a near future, fruit quality traits. These data will impact not only the pre-harvest but their effect will extend to the post-harvest sector of the fruit chain. Chapter 1 provides an updated overview on precision horticulture , while in Chapter 2 a preliminary spatial statistic analysis of the variability in apple orchards is provided before and after manual thinning; an interpretation of this variability and how it can be managed to maximize orchard performance is offered. Then in Chapter 3 a stratification of spatial data into management classes to interpret and manage spatial variation on the orchard is undertaken. An inverse model approach is also applied to verify whether the crop production explains environmental variation. In Chapter 4 an integration of the techniques adopted before is presented. A new key for reading the information gathered within the field is offered. The overall goal of this Dissertation was to probe into the feasibility, the desirability and the effectiveness of a precision approach to fruit growing, following the lines of other areas of agriculture that already adopt this management tool. As existing applications of precision horticulture already had shown, crop specificity is an important factor to be accounted for. This work focused on apple because of its importance in the area where the work was carried out, and worldwide.

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La ricerca è mirata a valutare come l’attuazione delle politiche ambientali di Sviluppo Rurale possa contribuire al miglioramento del paesaggio, analizzando i suoi effetti territoriali. Nell’ambito del caso di studio della Regione Emilia-Romagna vengono analizzate le misure agro-ambientali e di forestazione agricola dal 1994 al 2011, comprendendo gli interventi realizzati con i Regolamenti (CEE) 2078/1992, 2080/1992 e dai Programmi di Sviluppo Rurale (PSR) 2000-2006 e 2007-2013. In particolare, sono approfonditi i fattori che determinano la partecipazione territoriale delle misure agro-ambientali, individuate a livello aziendale le motivazioni alla partecipazione per le azioni con effetto diretto sul paesaggio, valutati i conseguenti effetti tecnico-economici e analizzati gli impatti degli interventi sul paesaggio a livello territoriale, in funzione del contesto ambientale. I risultati hanno consentito di approfondire quanto già riportato nelle valutazioni istituzionali dei PSR e in letteratura scientifica, individuando i fattori determinanti della partecipazione a livello regionale. A questo scopo sono state utilizzate analisi di econometria spaziale che hanno permesso di evidenziare effetti di concentrazione territoriale delle superfici sotto impegno, in funzione delle priorità della misura e degli ordinamenti produttivi dei beneficiari. Sono stati inoltre analizzati gli impatti paesaggistici in un’area di studio ristretta a livello territoriale e aziendale: gli interventi specifici, in alcuni contesti territoriali dove è stata raggiunta una certa concentrazione delle superfici sotto impegno, hanno modificato il paesaggio rurale, differenziandolo rispetto alla matrice agricola intensiva in cui sono stati inseriti. A livello aziendale sono stati rilevati effetti significativi sull’economia dei beneficiari che scelgono di aderire a tali misure, con un diffuso effetto di riduzione della redditività. I contributi compensano in maniera differenziata i costi legati all’implementazione degli interventi in funzione della tipologia di intervento e delle scelte tecniche aziendali adottate per la loro gestione.

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This doctoral thesis aims at contributing to the literature on transition economies focusing on the Russian Federations and in particular on regional income convergence and fertility patterns. The first two chapter deal with the issue of income convergence across regions. Chapter 1 provides an historical-institutional analysis of the period between the late years of the Soviet Union and the last decade of economic growth and a presentation of the sample with a description of gross regional product composition, agrarian or industrial vocation, labor. Chapter 2 contributes to the literature on exploratory spatial data analysis with a application to a panel of 77 regions in the period 1994-2008. It provides an analysis of spatial patterns and it extends the theoretical framework of growth regressions controlling for spatial correlation and heterogeneity. Chapter 3 analyses the national demographic patterns since 1960 and provides a review of the policies on maternity leave and family benefits. Data sources are the Statistical Yearbooks of USSR, the Statistical Yearbooks of the Russian Soviet Federative Socialist Republic and the Demographic Yearbooks of Russia. Chapter 4 analyses the demographic patterns in light of the theoretical framework of the Becker model, the Second Demographic Transition and an economic-crisis argument. With national data from 1960, the theoretically issue of the pro or countercyclical relation between income and fertility is graphically analyzed and discussed, together with female employment and education. With regional data after 1994 different panel data models are tested. Individual level data from the Russian Longitudinal Monitoring Survey are employed using the logit model. Chapter 5 employs data from the Generations and Gender Survey by UNECE to focus on postponement and second births intentions. Postponement is studied through cohort analysis of mean maternal age at first birth, while the methodology used for second birth intentions is the ordered logit model.

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Obiettivo del lavoro è migliorare la lettura della ruralità europea. A fronte delle profonde trasformazioni avvenute, oggi non è più possibile analizzare i territori rurali adottando un mero approccio dicotomico che semplicemente li distingua dalle città. Al contrario, il lavoro integra l’analisi degli aspetti socio-economici con quella degli elementi territoriali, esaltando le principali dimensioni che caratterizzano le tante tipologie di ruralità oggi presenti in Europa. Muovendo dal dibattito sulla classificazione delle aree rurali, si propone dapprima un indicatore sintetico di ruralità che, adottando la logica fuzzy, considera congiuntamente aspetti demografici (densità), settoriali (rilevanza dell’attività agricola), territoriali e geografici (accessibilità e uso del suolo). Tale tecnica permette di ricostruire un continuum di gradi di ruralità, distinguendo così, all’interno dell’Unione Europea (circa 1.300 osservazioni), le aree più centrali da quelle progressivamente più rurali e periferiche. Successivamente, attraverso un’analisi cluster vengono individuate tipologie di aree omogenee in termini di struttura economica, paesaggio, diversificazione dell’attività agricola. Tali cluster risentono anche della distribuzione geografica delle aree stesse: vengono infatti distinti gruppi di regioni centrali da gruppi di regioni più periferiche. Tale analisi evidenzia soprattutto come il binomio ruralità-arretratezza risulti ormai superato: alcune aree rurali, infatti, hanno tratto vantaggio dalle trasformazioni che hanno interessato l’Unione Europea negli ultimi decenni (diffusione dell’ICT o sviluppo della manifattura). L’ultima parte del lavoro offre strumenti di analisi a supporto dell’azione politica comunitaria, analizzando la diversa capacità delle regioni europee di rispondere alle sfide lanciate dalla Strategia Europa 2020. Un’analisi in componenti principali sintetizza le principali dimensioni di tale performance regionale: i risultati sono poi riletti alla luce delle caratteristiche strutturali dei territori europei. Infine, una più diretta analisi spaziale dei dati permette di evidenziare come la geografia influenzi ancora profondamente la capacità dei territori di rispondere alle nuove sfide del decennio.

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The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

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The thesis objectives are to develop new methodologies for study of the space and time variability of Italian upper ocean ecosystem through the combined use of multi-sensors satellite data and in situ observations and to identify the capability and limits of remote sensing observations to monitor the marine state at short and long time scales. Three oceanographic basins have been selected and subjected to different types of analyses. The first region is the Tyrrhenian Sea where a comparative analysis of altimetry and lagrangian measurements was carried out to study the surface circulation. The results allowed to deepen the knowledge of the Tyrrhenian Sea surface dynamics and its variability and to defined the limitations of satellite altimetry measurements to detect small scale marine circulation features. Channel of Sicily study aimed to identify the spatial-temporal variability of phytoplankton biomass and to understand the impact of the upper ocean circulation on the marine ecosystem. An combined analysis of the satellite of long term time series of chlorophyll, Sea Surface Temperature and Sea Level field data was applied. The results allowed to identify the key role of the Atlantic water inflow in modulating the seasonal variability of the phytoplankton biomass in the region. Finally, Italian coastal marine system was studied with the objective to explore the potential capability of Ocean Color data in detecting chlorophyll trend in coastal areas. The most appropriated methodology to detect long term environmental changes was defined through intercomparison of chlorophyll trends detected by in situ and satellite. Then, Italian coastal areas subject to eutrophication problems were identified. This work has demonstrated that satellites data constitute an unique opportunity to define the features and forcing influencing the upper ocean ecosystems dynamics and can be used also to monitor environmental variables capable of influencing phytoplankton productivity.

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This doctoral dissertation presents a new method to asses the influence of clearancein the kinematic pairs on the configuration of planar and spatial mechanisms. The subject has been widely investigated in both past and present scientific literature, and is approached in different ways: a static/kinetostatic way, which looks for the clearance take-up due to the external loads on the mechanism; a probabilistic way, which expresses clearance-due displacements using probability density functions; a dynamic way, which evaluates dynamic effects like the actual forces in the pairs caused by impacts, or the consequent vibrations. This dissertation presents a new method to approach the problem of clearance. The problem is studied from a purely kinematic perspective. With reference to a given mechanism configuration, the pose (position and orientation) error of the mechanism link of interest is expressed as a vector function of the degrees of freedom introduced in each pair by clearance: the presence of clearance in a kinematic pair, in facts, causes the actual pair to have more degrees of freedom than the theoretical clearance-free one. The clearance-due degrees of freedom are bounded by the pair geometry. A proper modelling of clearance-affected pairs allows expressing such bounding through analytical functions. It is then possible to study the problem as a maximization problem, where a continuous function (the pose error of the link of interest) subject to some constraints (the analytical functions bounding clearance- due degrees of freedom) has to be maximize. Revolute, prismatic, cylindrical, and spherical clearance-affected pairs have been analytically modelled; with reference to mechanisms involving such pairs, the solution to the maximization problem has been obtained in a closed form.