Efficient knowledge retrieval to calibrate input variables in forest fire prediction

Forest fires are a serious threat to humans and nature from an ecological, social and economic point of view. Predicting their behaviour by simulation still delivers unreliable results and remains a challenging task. Latest approaches try to calibrate input variables, often tainted with imprecision, using optimisation techniques like Genetic Algorithms. To converge faster towards fitter solutions, the GA is guided with knowledge obtained from historical or synthetical fires. We developed a robust and efficient knowledge storage and retrieval method. Nearest neighbour search is applied to find the fire configuration from knowledge base most similar to the current configuration. Therefore, a distance measure was elaborated and implemented in several ways. Experiments show the performance of the different implementations regarding occupied storage and retrieval time with overly satisfactory results.

Textural classification of land cover using support vector machines: an empirical comparison with parametric, non parametric and hybrid classifiers in the Bolivian Amazon

Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

Detection of millimetric deformation using a terrestrial laser scanner: experiment and application to a rockfall event

Terrestrial laser scanning (TLS) is one of the most promising surveying techniques for rockslope characterization and monitoring. Landslide and rockfall movements can be detected by means of comparison of sequential scans. One of the most pressing challenges of natural hazards is combined temporal and spatial prediction of rockfall. An outdoor experiment was performed to ascertain whether the TLS instrumental error is small enough to enable detection of precursory displacements of millimetric magnitude. This consists of a known displacement of three objects relative to a stable surface. Results show that millimetric changes cannot be detected by the analysis of the unprocessed datasets. Displacement measurement are improved considerably by applying Nearest Neighbour (NN) averaging, which reduces the error (1¿) up to a factor of 6. This technique was applied to displacements prior to the April 2007 rockfall event at Castellfollit de la Roca, Spain. The maximum precursory displacement measured was 45 mm, approximately 2.5 times the standard deviation of the model comparison, hampering the distinction between actual displacement and instrumental error using conventional methodologies. Encouragingly, the precursory displacement was clearly detected by applying the NN averaging method. These results show that millimetric displacements prior to failure can be detected using TLS.

Classification of textures seen from different distances and under varying illumination direction

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

The ‘Dys-Appearing’ Body in Doris Lessing’s The Diary of a Good Neighbour and Margaret Forster’s Have the Men Had Enough?

If the old body is usually read as a synonym of fragility and upcoming illness, even though not the case for most elderly citizens, the reality is that the longer we live, the increased probability of being affected by different illnesses cannot be eluded or denied. In Doris Lessing’s The Diary of a Good Neighbour and Margaret Forster’s Have the Men Had Enough? the reader is invited to participate in the day-to-day routines of two aged female protagonists, as well as to empathize with their inner feelings as they go through their last life stage. In fact, their ‘dys-appearing’ bodies, marked by their respective terminal illnesses, force these characters to grow closer to those around them and to accept the help of their families and friends, despite their desire to keep their free will and independence until the very end. The analysis of the two novels within the framework of ageing studies aims to show the contradictions existing between a growing ageing society and the negative cultural connotations of old age in Western society and the need to revise them.

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

Urban spatial structure and suburbanisation. The case of the Barcelona Metropolitan

The metropolitan spatial structure displays various patterns, sometimes monocentricity and sometimes multicentricity, which seems much more complicated than the exponential density function used in classic works such as Clark (1961), Muth (1969) or Mills (1973) among others, can effectively represent. It seems that a more flexible density function,such as cubic spline function (Anderson (1982), Zheng (1991), etc.) to describe the density-accessibility relationship is needed. Also, accessibility, the fundamental determinant of density variations, is only partly captured by the inclusion of distance to the city centre as an explanatory variable. Steen (1986) has proposed to correct that miss-especification by including an additional gradient for distance to the nearest transportation axis. In identifying the determinants of urban spatial structure in the context of inter-urban systems, some of the variables proposed by Muth (1969), Mills (1973) and Alperovich (1983) such as city age or population, make no sense in the case of a single urban system. All three criticism to the exponential density function and its determinants apply for the Barcelona Metropolitan Region, a polycentric conurbation structured on well defined transportation axes.

The existence of periodic solutions of a two dimensional Lattice

We consider a two dimensional lattice coupled with nearest neighbor interaction potential of power type. The existence of infinite many periodic solutions is shown by using minimax methods.

Classificació i importància dels elements paisatgístics del territori Tsimane' segons la percepció local

En aquesta tesis es presenten els resultats de la investigació duta a terme a les comunitats indígenes Tsimane’ de l’Amazònia boliviana. La investigació estudia la percepció dels indígenes sobre l’etnoclassificació del seu territori. S’estableix una clau de classificació i es determina la importància dels elements paisatgístics del territori Tsimane’ segons la percepció local. Aquesta informació permetrà integrar el coneixement local dins dels programes de desenvolupament integral i de planificació territorial en l’Amazònia Boliviana. L’estudi conclou que la població Tsimane’ classifica els elements paisatgístics del seu entorn en 89 taques conformades per una espècies arbòria dominant i que estan incloses en un o més dels nou paisatges identificats: Därsi Därä, Sajras, Sinues Ojñi’, Mayes, Múcúya, Tsäquis Därä, Cum, Tajñi’ i Jaman. A partir d’un anàlisi multicriteri s’ha determinat una importància total per cada paisatge segons els següents criteris d’importància: diversitat de taques, activitats econòmiques realitzables, presència espiritual, percepció individual i importància relativa segons els altres paisatges. Així doncs s’ha trobat que el paisatge més important és el Därsi Därä (bosc primari caracteritzat per un estrat arbori superior a 50 metres d’altura). També s’han analitzat les dades discernint segons el gènere de l’entrevistat i segons la proximitat de les comunitats estudiades a la ciutat més propera.

L'aprenentatge basat en problemes (PBL) en la regulació del metabolisme. Desenvolupament del portal per a l'intercanvi d'experiències en PBL en ciències biomèdiques

L’aprenentatge basat en problemes està en fase experimental en tot el món i és objecte d’anàlisi i reflexió en moltes reunions internacionals. Tanmateix, no hi ha massa feina feta en aquesta direcció en el nostre camp més proper. Hem elaborat problemes per l’aprenentatge de la Regulació del Metabolisme i els hem incorporat a un porta virtual (http://www.ub.edu/GID-BBM). La finalitat d’aquesta estratègia és que mitjançant l’aprenentatge basat en problemes reals o simulacions de problemes reals s’aconsegueixi motivar l’alumnat a treballar de forma continuada durant tot el curs. La millora dels resultats acadèmics haurà de ser la conseqüència lògica d’aquest treball. La finalitat última del projecte que hem desenvolupat és preparar l’alumnat per la seva futura activitat professional a on serà molt important i valorat la seva capacitat de resposta davant de diferents problemes

Regional flows of domestic tourism in Spain = Flujos regionales del turismo doméstico en España

The paper analyses the regional flows of domestic tourism that took place in Spain in year 2000, contributing to the state of knowledge on tourism required by authorities and private firms when faced with decision making, for example, for regional infrastructure planning. Although tourism is one of the main income-generating economic activities in Spain, domestic tourism has received little attention in the literature compared to inbound tourism. The paper uses among others, gravitational model tools and concentration indices, to analyse regional concentration of both domestic demand and supply; tourism flows among regions, and the causes that may explain the observed flows and attractiveness between regions. Among the most remarkable results are the high regional concentration of demand and supply, and the role of population and regional income as explanatory variables. Also remarkable are the attractiveness of own region and neighbour ones, and that domestic tourism may be acting as a regional income redistributing activity

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table hasn rows and m columns and all probabilities are non-null. This kind of table can beseen as an element in the simplex of n · m parts. In this context, the marginals areidentified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclideanelements of the Aitchison geometry of the simplex can also be translated into the tableof probabilities: subspaces, orthogonal projections, distances.Two important questions are addressed: a) given a table of probabilities, which isthe nearest independent table to the initial one? b) which is the largest orthogonalprojection of a row onto a column? or, equivalently, which is the information in arow explained by a column, thus explaining the interaction? To answer these questionsthree orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independenttwo-way tables and fully dependent tables representing row-column interaction. Animportant result is that the nearest independent table is the product of the two (rowand column)-wise geometric marginal tables. A corollary is that, in an independenttable, the geometric marginals conform with the traditional (arithmetic) marginals.These decompositions can be compared with standard log-linear models.Key words: balance, compositional data, simplex, Aitchison geometry, composition,orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure,contingency table

Aplicació de visió per dispositius mòbils

En aquest projecte es presenta l’aplicació per a dispositius mòbils Doppelganger. La seva funció és, a partir d’una fotografia, detectar la cara i mostrar la persona famosa de la nostra base de dades que més s’assembla a la persona en la fotografia. Per la implementació s’han utilitzat algoritmes de visió per computador i d’aprenentatge automàtic com per exemple el PCA i el K-Nearest Neighbor, tot utilitzant llibreries gratuïtes com són les OpenCV.