A Spatial Analysis of Agricultural Land Prices in Bavaria. Factor Markets Working Document No. 50, June 2013

This paper empirically analyses a dataset of more than 7,300 agricultural land sales transactions from 2001 and 2007 to identify the factors influencing agricultural land prices in Bavaria. We use a general spatial model, which combines a spatial lag and a spatial error model, and in addition account for endogeneity introduced by the spatially lagged dependent variable as well as other explanatory variables. Our findings confirm the strong influence of agricultural factors such as land productivity, of variables describing the regional land market structure, and of non-agricultural factors such as urban pressure on agricultural land prices. Moreover, the involvement of public authorities as a seller or buyer increases sales prices in Bavaria. We find a significant capitalisation of government support payments into agricultural land, where a decrease of direct payments by 1% would decrease land prices in 2007 and 2001 by 0.27% and 0.06%, respectively. In addition, we confirm strong spatial relationships in our dataset. Neglecting this leads to biased estimates, especially if aggregated data is used. We find that the price of a specific plot increases by 0.24% when sales prices in surrounding areas increase by 1%.

Evaluating Effects of Everglades Restoration on American Crocodile Populations in South Florida Using a Spatially-Explicit, Stage-Based Population Model

The distribution and abundance of the American crocodile (Crocodylus acutus) in the Florida Everglades is dependent on the timing, amount, and location of freshwater flow. One of the goals of the Comprehensive Everglades Restoration Plan (CERP) is to restore historic freshwater flows to American crocodile habitat throughout the Everglades. To predict the impacts on the crocodile population from planned restoration activities, we created a stage-based spatially explicit crocodile population model that incorporated regional hydrology models and American crocodile research and monitoring data. Growth and survival were influenced by salinity, water depth, and density-dependent interactions. A stage-structured spatial model was used with discrete spatial convolution to direct crocodiles toward attractive sources where conditions were favorable. The model predicted that CERP would have both positive and negative impacts on American crocodile growth, survival, and distribution. Overall, crocodile populations across south Florida were predicted to decrease approximately 3 % with the implementation of CERP compared to future conditions without restoration, but local increases up to 30 % occurred in the Joe Bay area near Taylor Slough, and local decreases up to 30 % occurred in the vicinity of Buttonwood Canal due to changes in salinity and freshwater flows.

ELUM: a spatial modelling tool to predict soil greenhouse gas changes from land conversion to bioenergy in the UK

Acknowledgements This work is based on the Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial (ELUM) project, which was commissioned and funded by the Energy Technologies Institute (ETI). The authors are grateful to Niall McNamara (Centre for Ecology & Hydrology, Lancaster) for coordinating the project and to Dagmar Henner (University of Aberdeen) for project assistance. We are also grateful to staff at the ETI, particularly to Geraldine Newton-Cross, Geraint Evans and Hannah Evans for constructive advice and feedback, and to Jonathan Oxley for project support. The ELUM Software Package contains Ordnance Survey data © Crown copyright and database right 2012.

Local influence analysis in general spatial models

Spatial variability of satured soil hydraulic conductivity in the region of Araguaia River - Brazil.

This study evaluates the spatial variability of saturated hydraulic conductivity in the soil in an area of 51,850 ha at the headwaters of the Araguaia River MT/GO. This area is highly vulnerable because it is a location of recharging through natural water infiltration of the Guarani Aquifer System and an area of intense increases in agriculture since its adoption by growers in the last 30 years. Soil samples were collected at 383 points, geographically located by GPS. The samples were collected from depths of 0 - 20 cm and 60 - 80 cm. Exploratory statistics and box-plot were used in the descriptive analysis and semivariogram were constructed to determine the spatial model. The exploratory analysis showed that the mean hydraulic conductivity in the superficial layer was less than at the level of 60-80 cm; however, the greatest variability evaluated with a coefficient of variation also was from this layer. Data tended towards a normal distribution. These results can be explained by the greater soil compaction in the superficial layer. The semivariogram models, adjusted for the two layers, were exponential and demonstrated moderate and strong dependence, with ranges of 5000 and 3000 utm respectively. It was concluded that soil use is influencing the spatial distribution model of the hydraulic conductivity in the region.

Biomass sustainability, availability and productivity

Research conducted on biomass for Ulcos (""Ultra-Low CO(2) Steelmaking"" European Integrated Project) has progressively focused on charcoal supply from tropical eucalyptus plantations. The sustainability of such plantations is being investigated from the viewpoint of their carbon, water and nutrient budgets: they must all be neutral or positive. Field research is producing results at the tree or stand level in several sites of Congo and Brazil, while a spatial model is developed to identify the conditions of biomass neutrality at the scale of the forest ecosystem. The productivity of biomass has been analyzed through the description of practices along the various supply-schemes that competitively feed the steel industry in Brazil and identification of bottlenecks for further expansion.

Exploração da Point Cloud Library aplicada à percepção em sistemas autónomos

A navegação e a interpretação do meio envolvente por veículos autónomos em ambientes não estruturados continua a ser um grande desafio na actualidade. Sebastian Thrun, descreve em [Thr02], que o problema do mapeamento em sistemas robóticos é o da aquisição de um modelo espacial do meio envolvente do robô. Neste contexto, a integração de sistemas sensoriais em plataformas robóticas, que permitam a construção de mapas do mundo que as rodeia é de extrema importância. A informação recolhida desses dados pode ser interpretada, tendo aplicabilidade em tarefas de localização, navegação e manipulação de objectos. Até à bem pouco tempo, a generalidade dos sistemas robóticos que realizavam tarefas de mapeamento ou Simultaneous Localization And Mapping (SLAM), utilizavam dispositivos do tipo laser rangefinders e câmaras stereo. Estes equipamentos, para além de serem dispendiosos, fornecem apenas informação bidimensional, recolhidas através de cortes transversais 2D, no caso dos rangefinders. O paradigma deste tipo de tecnologia mudou consideravelmente, com o lançamento no mercado de câmaras RGB-D, como a desenvolvida pela PrimeSense TM e o subsequente lançamento da Kinect, pela Microsoft R para a Xbox 360 no final de 2010. A qualidade do sensor de profundidade, dada a natureza de baixo custo e a sua capacidade de aquisição de dados em tempo real, é incontornável, fazendo com que o sensor se tornasse instantaneamente popular entre pesquisadores e entusiastas. Este avanço tecnológico deu origem a várias ferramentas de desenvolvimento e interacção humana com este tipo de sensor, como por exemplo a Point Cloud Library [RC11] (PCL). Esta ferramenta tem como objectivo fornecer suporte para todos os blocos de construção comuns que uma aplicação 3D necessita, dando especial ênfase ao processamento de nuvens de pontos de n dimensões adquiridas a partir de câmaras RGB-D, bem como scanners laser, câmaras Time-of-Flight ou câmaras stereo. Neste contexto, é realizada nesta dissertação, a avaliação e comparação de alguns dos módulos e métodos constituintes da biblioteca PCL, para a resolução de problemas inerentes à construção e interpretação de mapas, em ambientes indoor não estruturados, utilizando os dados provenientes da Kinect. A partir desta avaliação, é proposta uma arquitectura de sistema que sistematiza o registo de nuvens de pontos, correspondentes a vistas parciais do mundo, num modelo global consistente. Os resultados da avaliação realizada à biblioteca PCL atestam a sua viabilidade, para a resolução dos problemas propostos. Prova da sua viabilidade, são os resultados práticos obtidos, da implementação da arquitectura de sistema proposta, que apresenta resultados de desempenho interessantes, como também boas perspectivas de integração deste tipo de conceitos e tecnologia em plataformas robóticas desenvolvidas no âmbito de projectos do Laboratório de Sistemas Autónomos (LSA).

Spatio-temporal modelling of environmental data

Programa Doutoral em Matemática e Aplicações.

Anatomically informed basis functions

Neuroimaging, functional image analysis, spatial model, cortical surface, spatially variable convolution

Political Competition in Hard Times

This paper analyzes a spatial model of political competition between two policy- motivated parties in hard times of crisis. Hard times are modeled in terms of policy- making costs carried by a newly elected party. The results predict policy divergence in equilibrium. If the ideological preferences of parties are quite diverse and extreme, there is a unique equilibrium in which the parties announce symmetric platforms and each party wins with probability one half. If one party is extreme while the other is more moderate, there is a unique equilibrium in which the parties announce asymmetric platforms. If the preferred policies of the parties are not very distinct, there are two equilibria with asymmetric platforms. An important property of equilibrium with asymmetric platforms is that a winning party necessarily announces its most preferred policy as a platform. JEL classification: D72. Keywords: Spatial model; Political competition; Two-party system; Policy-motivated parties; Hard times; Crisis.

Municipal distribution of bladder cancer mortality in Spain: Possible role of mining and industry

BACKGROUND Spain shows the highest bladder cancer incidence rates in men among European countries. The most important risk factors are tobacco smoking and occupational exposure to a range of different chemical substances, such as aromatic amines. METHODS This paper describes the municipal distribution of bladder cancer mortality and attempts to "adjust" this spatial pattern for the prevalence of smokers, using the autoregressive spatial model proposed by Besag, York and Molliè, with relative risk of lung cancer mortality as a surrogate. RESULTS It has been possible to compile and ascertain the posterior distribution of relative risk for bladder cancer adjusted for lung cancer mortality, on the basis of a single Bayesian spatial model covering all of Spain's 8077 towns. Maps were plotted depicting smoothed relative risk (RR) estimates, and the distribution of the posterior probability of RR>1 by sex. Towns that registered the highest relative risks for both sexes were mostly located in the Provinces of Cadiz, Seville, Huelva, Barcelona and Almería. The highest-risk area in Barcelona Province corresponded to very specific municipal areas in the Bages district, e.g., Suría, Sallent, Balsareny, Manresa and Cardona. CONCLUSION Mining/industrial pollution and the risk entailed in certain occupational exposures could in part be dictating the pattern of municipal bladder cancer mortality in Spain. Population exposure to arsenic is a matter that calls for attention. It would be of great interest if the relationship between the chemical quality of drinking water and the frequency of bladder cancer could be studied.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Language extinction and linguistic fronts

Language diversity has become greatly endangered in the past centuries owing to processes of language shift from indigenous languages to other languages that are seen as socially and economically more advantageous, resulting in the death or doom of minority languages. In this paper, we define a new language competition model that can describe the historical decline of minority languages in competition with more advantageous languages. We then implement this non-spatial model as an interaction term in a reactiondiffusion system to model the evolution of the two competing languages. We use the results to estimate the speed at which the more advantageous language spreads geographically, resulting in the shrinkage of the area of dominance of the minority language. We compare the results from our model with the observed retreat in the area of influence of the Welsh language in the UK, obtaining a good agreement between the model and the observed data

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Essais sur des questions internationales en économie des ressources naturelles

Cette thèse s'articule autour de trois essais portant sur des questions internationales en économie des ressources naturelles. Le premier essai examine la production et l'échange des ressources non-renouvelables dans un modèle spatial et souligne le rôle de la superficie des pays et du coût des transports dans la détermination du sens de l'échange. Le deuxième essai considère le tarif d'extraction de la rente de rareté liée aux ressources naturelles non-renouvelables avec le modèle spatial développé dans premier essai. Le cadre spatial (plus général) permet de représenter des pays qui sont à la fois importateurs et producteurs de la ressource, ce qui n'est pas possible dans les modèles traditionnels de commerce international où les pays sont traités comme des points (sans dimension). Le troisième essai aborde la question des droits de propriétés sur les zones maritimes et examine l'allocation d'une population de pêcheurs entre les activités productives et non-productives dans une communauté côtière. Le premier chapitre propose un modèle spatial de commerce international des ressources non-renouvelables. Le cadre spatial considère explicitement la différence de taille géographique (superficie) entre les pays et permet ainsi de tenir compte du fait que les gisements naturels et leurs utilisateurs soient dispersés dans l'espace, même à l'intérieur d'un pays. En utilisant un modèle spatial à la Hotelling, nous examinons l'évolution dans le temps du sens de l'échange entre deux pays (ou régions) qui diffèrent du point de vue de leur technologie de production, de leur superficie et de leur dotation en gisement d'une ressource naturelle non-renouvelable. Le chapitre met en évidence le rôle de la taille géographique dans la détermination du sens de l'échange, à côté des explications traditionnelles que sont l'avantage comparatif et les dotations des facteurs. Notre analyse est fondamentalement différente des autres contributions dans la littérature sur le commerce international des ressources naturelles parce qu'elle souligne l'importance de la taille géographique et du coût de transport par rapport à d'autres facteurs dans la détermination des flux de ressource à l'équilibre. Le coût unitaire de transport joue un rôle capital pour déterminer si la différence de superficie entre les pays influence le sens de l'échange à l'équilibre plus que les autres facteurs. Le chapitre discute aussi du caractère régional des échanges qui a été observé pour certaines ressources telles que le minerai de fer et la bauxite. Le chapitre deux aborde la question de la répartition de la rente de rareté liée aux ressources naturelles non-renouvelables entre les pays producteurs et les pays consommateurs. Cette question a été abordée dans la littérature sous une hypothèse quelque peu restrictive. En effet, dans la plupart des travaux portant sur ce sujet le pays importateur est automatiquement considéré comme dépourvu de gisement et donc non producteur de la ressource. Pourtant la réalité est qu'il existe des ressources pour lesquelles un pays est à la fois producteur et importateur. Le cadre d'analyse de ce second essai est le modèle spatial développé dans le premier essai, qui permet justement qu'un pays puisse être à la fois importateur et producteur de la ressource. Le pays importateur détermine alors simultanément le tarif optimal et le taux d'extraction de son propre stock. Nous montrons que le tarif optimal croît au taux d'intérêt et de ce fait, ne crée aucune distorsion sur le sentier d'extraction de la ressource. Le tarif optimal permet de récupérer toute la rente lorsque le pays exportateur ne consomme pas la ressource. Néanmoins, la possibilité pour le pays exportateur de consommer une partie de son stock limite la capacité du pays importateur à récupérer la rente chez le pays exportateur. La présence de gisements de la ressource dans le pays importateur réduit la rente du pays exportateur et de ce fait renforce la capacité du pays importateur à récupérer la rente chez le pays exportateur. Le tarif initial est une fonction décroissante du stock de ressource dans le pays importateur. Cet essai aborde également la question de la cohérence dynamique du tarif obtenu avec la stratégie en boucle ouverte. Le troisième chapitre examine un problème d'allocation de l'effort entre les activités productives (par exemple la pêche) et les activités non productives (par exemple la piraterie maritime) dans une population de pêcheurs. La répartition de la population entre les activités de pêche et la piraterie est déterminée de façon endogène comme une conséquence du choix d'occupation. Nous établissons l'existence d'une multiplicité d'équilibres et mettons en évidence la possibilité d'une trappe de piraterie, c'est-à-dire un équilibre stable où une partie de la population est engagée dans les actes de piraterie. Le modèle permet d'expliquer l'augmentation significative des attaques de piraterie dans le Golfe d'Aden au cours des dernières années. Le chapitre discute aussi des différents mécanismes pour combattre la piraterie et souligne le rôle crucial des droits de propriété.