Estudi preliminar per la creació d'una nova categoria d'impacte ambiental dins el marc de l'ACV: la dimensió natural del paisatge

L’Anàlisi de Cicle de Vida (ACV) és una eina emprada per gestionar els impactes ambientals i els recursos usats al llarg del cicle de vida d’un bé o servei. Existeixen reptes de futur en el desenvolupament de l’ACV, tals com la introducció de noves categories d’impacte ambiental, que permetin una anàlisi més específica dels impactes sobre determinats elements del medi, com ara el paisatge. En el present estudi s’analitza la dimensió natural del paisatge per tal de proposar la creació d’un índex de paisatge. Així doncs, s’han revisat les noves propostes de categories d’impacte en ACV que inclouen directament o indirecta el paisatge i s’ha analitzat una mostra de 33 estudis d’indicadors de paisatge. Aquesta cerca deriva en l’elecció de 6 indicadors: els usos del sòl, la diversitat paisatgística, la fragmentació, la connectivitat, la riquesa d’espècies i la densitat de carreteres. En la determinació dels seus respectius mètodes de càlcul s’ha detectat la importància de l’ús dels SIG, l’elecció d’una base de dades d’usos del sòl comuna (CORINE) i les interrelacions que existeixen entre indicadors. La proposta de l’índex hauria de poder ésser un punt de partida per a futurs estudis en aquest àmbit i derivar en una nova categoria d’impacte de paisatge, donat que caldrà estudiar alguns elements, com la interrelació entre indicadors.

Urban population density functions : the case of the Barcelona region

L'anàlisi de la densitat urbana és utilitzada per examinar la distribució espacial de la població dins de les àrees urbanes, i és força útil per planificar els serveis públics. En aquest article, s'estudien setze formes funcionals clàssiques de la relació existent entre la densitat i la distancia en la regió metropolitana de Barcelona i els seus onze subcentres.

Cubic spline population density functions and subcentre delimitation. The case of Barcelona

The presence of subcentres cannot be captured by an exponential function. Cubic spline functions seem more appropriate to depict the polycentricity pattern of modern urban systems. Using data from Barcelona Metropolitan Region, two possible population subcentre delimitation procedures are discussed. One, taking an estimated derivative equal to zero, the other, a density gradient equal to zero. It is argued that, in using a cubic spline function, a delimitation strategy based on derivatives is more appropriate than one based on gradients because the estimated density can be negative in sections with very low densities and few observations, leading to sudden changes in estimated gradients. It is also argued that using as a criteria for subcentre delimitation a second derivative with value zero allow us to capture a more restricted subcentre area than using as a criteria a first derivative zero. This methodology can also be used for intermediate ring delimitation.

The density of injective endomorphisms of a free group

"Vegeu el resum a l'inici del document del fitxer adjunt."

Economic effects of road accessibility in the Pyrenees: user perspective

At present, Spain faces one of the key moments in planning the future design of the infrastructure network. As a consequence of the critical role played by haulage in intra-European trade, the most important investments are those that guarantee that road haulage traffic can move freely at the borders. That is why it is necessary to make serious evaluations of the economic and social profitability of these investments. Normally the most significant social benefit of investment projects in transport infrastructure is time saving, which in turn changes traffic intensity. In this article we analyse the changes in the user excess caused by public investment in transport infrastructure planned by the Spanish government and which will be located on the border between Spain and France. In particular, we study the increase in network user surplus for HGV traffic in the Spanish and French border zones in the Pyrenees.

Comparison of recent toll road concession transactions in the United States and France

Recent concessions in France and in the US have resulted in a dramatic difference in the valuation placed on the toll roads; the price paid by the investors in France was twelve times current cash flow whereas investors paid sixty times current cash flow for the U.S. toll roads. In this paper we explore two questions: What accounts for the difference in these multiples, and what are the implications with respect to the public interest. Our analysis illustrates how structural and procedural decisions made by the public owner affect the concession price. Further, the terms of the concession have direct consequences that are enjoyed or borne by the various stakeholders of the toll road.

On the density distribution across space: a probabilistic approach

This paper aims at providing a Bayesian parametric framework to tackle the accessibility problem across space in urban theory. Adopting continuous variables in a probabilistic setting we are able to associate with the distribution density to the Kendall's tau index and replicate the general issues related to the role of proximity in a more general context. In addition, by referring to the Beta and Gamma distribution, we are able to introduce a differentiation feature in each spatial unit without incurring in any a-priori definition of territorial units. We are also providing an empirical application of our theoretical setting to study the density distribution of the population across Massachusetts.

Scene classifier for real time road detection

L’objectiu principal del projecte és el de classificar escenes de carretera en funció del contingut de les imatges per així poder fer un desglossament sobre quin tipus de situació tenim en el moment. És important que fixem els paràmetres necessaris en funció de l’escenari en què ens trobem per tal de treure el màxim rendiment possible a cada un dels algoritmes. La seva funcionalitat doncs, ha de ser la d’avís i suport davant els diferents escenaris de conducció. És a dir, el resultat final ha de contenir un algoritme o aplicació capaç de classificar les imatges d’entrada en diferents tipus amb la màxima eficiència espacial i temporal possible. L’algoritme haurà de classificar les imatges en diferents escenaris. Els algoritmes hauran de ser parametritzables i fàcilment manejables per l’usuari. L’eina utilitzada per aconseguir aquests objectius serà el MATLAB amb les toolboxs de visió i xarxes neuronals instal·lades.

Anàlisi i diagnosi ambiental de la dinàmica del porc senglar (Sus scrofa) al Parc del Garraf

El Parc del Garraf (PG) és una zona on la dinàmica del porc senglar amb el medi té una alta importància, tot i que la densitat de població al PG d’aquest ungulat és de les menors de Catalunya. Els aspectes més rellevants de la relació porc senglar-medi són: la correlació que hi ha entre l’abandonament d’àrees de conreu i activitats forestals amb l’augment de la població de porc senglar, i l’afectació que per tant, provoca a les àrees de conreu que hi ha actualment, que es pot veure minvada aplicant bones mesures correctores. També la relació que té amb el margalló (Chamaerops humilis), que és positiva ajudant a la recuperació, conservació i a la dinàmica ecològica de l’espècie, així com amb el medi del PG en general, i, per últim, els impactes viaris a la xarxa viària del PG, tot i que no existeix cap TCCU (Tram de Concentració de Col·lisions amb Ungulats) dins els límits del PG. Referent a la caça, actualment és la única mesura viable de control de la població de porc senglar, tot i que no hi ha relleu generacional per a aquesta activitat.

Sobolev mappings: Lipschitz density is not an isometric invariant of the target

"Vegeu el resum a l'inici del document del fitxer adjunt."

Gaussian estimates for the density of the non-linear stochastic heat equation in any space dimension

In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise which is white in time with some spatially homogeneous covariance. These estimates are obtained using tools of the Malliavin calculus. The most challenging part is the lower bound, which is obtained by adapting a general method developed by Kohatsu-Higa to the underlying spatially homogeneous Gaussian setting. Both lower and upper estimates have the same form: a Gaussian density with a variance which is equal to that of the mild solution of the corresponding linear equation with additive noise.

The impact of agglomeration effects and accessibility on wages

This paper contributes to the empirical literature on the effects of agglomeration and road accessibility on productivity of firms by looking at the case of Spain. We approach productivity indirectly by using individual wages allocated at the NUTS III level. We use a repeated cross-section of individual micro-data for the years 1995, 2002 and 2006. The availability of interprovincial travel time data for each of the three years allows controlling for transport improvements over the period by using a market potential variable. Additionally, agglomeration is approached by employment density and we control for localization economies, human capital externalities and a large set of individual and workplace characteristics. Estimating by instrumental variables, our results show a positive and significant effect of market accessibility on wages and non linear effect for employment density.

Comparing methods for dimensionality reduction when data are density functions

Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions)

Hilbert space on probability density functions with Aitchison geometry

Compositional data analysis motivated the introduction of a complete Euclidean structure in the simplex of D parts. This was based on the early work of J. Aitchison (1986) and completed recently when Aitchinson distance in the simplex was associated with an inner product and orthonormal bases were identified (Aitchison and others, 2002; Egozcue and others, 2003). A partition of the support of a random variable generates a composition by assigning the probability of each interval to a part of the composition. One can imagine that the partition can be refined and the probability density would represent a kind of continuous composition of probabilities in a simplex of infinitely many parts. This intuitive idea would lead to a Hilbert-space of probability densitiesby generalizing the Aitchison geometry for compositions in the simplex into the set probability densities

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques