The choice of titling system in land

This paper analyzes the choice of the socially optimal titling systemassuming rational individual choices about recording, assurance andregistration decisions. It focuses on the enforcement of propertyrights on land under private titling and the two existing publictitling systems, recording and registration. When the reduction in theexpected costs of eviction compensates the higher cost of initialregistration, it is more efficient to introduce a registration systemrather than a recording system. The development of private "titleassurance" improves the standing of recording as compared toregistration. This improvement depends, however, on the efficiency ofthe assurance technology and, also, on corrective taxation that isneeded to align individual optimization, which disregards the transferelement in eviction, with social objectives.

Earth's Changing Land

Entre el 14 i el 18 de març de 1998 es va celebrar a Barcelona la conferència Earth’s Changing Land sota la tutela dels programes internacionals Global Change in Terrestrial Ecosystems (GCTE) i Land Use and Land Cover Change (LUCC). L’objectiu principal de la trobada era presentar les darreres aportacions científiques sobre els efectes presents i previsibles del canvi global sobre els ecosistemes terrestres i la societat. Al mateix temps, es volia afavorir l’establiment de ponts de diàleg entre els professionals implicats en el canvi global

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

Lobbying, political competition, and local land supply: recent evidence from Spain

We analyze whether local land supply is influenced by the degree of political competition, and interpret the findings as being indicative of the influence wielded by land development lobbies. We use a new database including both political and land supply data for more than 2,000 Spanish municipalities for the period 2003-2007. In Spain, land use policies are largely a local responsibility with municipalities having periodically to pass compre- hensive land use plans. The main policy variable in these plans, and the one analyzed here, is the amount of land classified for potential development. We measure local political competition as the margin of victory of the incumbent government. We instrument this variable using the number of votes obtained by parties represented in local government when standing at the first national legislative elections following the re-establishment of democracy, and the number of votes they actually obtained regionally at the national legislative elections. The results indicate that stiffer political competition does indeed reduce the amount of new land designated for development. This effect is found to be most marked in suburbs, in towns with a high percent of commuters and homeowners, and in municipalities governed by the left.

Lobbying, political competition, and local land supply: recent evidence from Spain

We analyze whether local land supply is influenced by the degree of political competition, and interpret the findings as being indicative of the influence wielded by land development lobbies. We use a new database including both political and land supply data for more than 2,000 Spanish municipalities for the period 2003-2007. In Spain, land use policies are largely a local responsibility with municipalities having periodically to pass compre- hensive land use plans. The main policy variable in these plans, and the one analyzed here, is the amount of land classified for potential development. We measure local political competition as the margin of victory of the incumbent government. We instrument this variable using the number of votes obtained by parties represented in local government when standing at the first national legislative elections following the re-establishment of democracy, and the number of votes they actually obtained regionally at the national legislative elections. The results indicate that stiffer political competition does indeed reduce the amount of new land designated for development. This effect is found to be most marked in suburbs, in towns with a high percent of commuters and homeowners, and in municipalities governed by the left.

Application of fuzzy-rule-based postprocessing to correlation methods in pattern recognition

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

Climatic and land use changes in the NW of Iberian Peninsula recorded in a 1,500-year record from Lake Sanabria

L'estudi de diversos descriptors paleoambientals com ara el pol·len, les diatomees i la sedimentologia, realitzat en sediments procedents del llac de Sanabria (NO de la península Ibèrica), ha aportat informació sobre les oscil·lacions climàtiques atribuïdes als períodes càlids tardoromà i medieval, així com a la petita edat del gel. Entre els anys 440 i 950 dC, el clima es caracteritzà per temperatures suaus i un règim de precipitacions mediterrani, malgrat l¿existència de pulsacions més fredes vers els anys 530 i 700 dC. Les evidències pol·líniques dels usos del sòl indiquen l'extensió d¿activitats ramaderes i agrícoles. Aquesta fase correspon al final del període càlid romà i al període càlid medieval. El canvi de condicions climàtiques es produeix entre els anys 950 i 1100 dC, moment en què els valors mínims de matèria orgànica, pol·len arbori, concentració de diatomees, nitrogen total (TN) i mida del gra indiquen temperatures més baixes i un règim de precipitacions més regular. Aquest període correspon a

Climate Change or Land Use Dynamics: Do We Know What Climate Change Indicators Indicate?

Different components of global change can have interacting effects on biodiversity and this may influence our ability to detect the specific consequences of climate change through biodiversity indicators. Here, we analyze whether climate change indicators can be affected by land use dynamics that are not directly determined by climate change. To this aim, we analyzed three community-level indicators of climate change impacts that are based on the optimal thermal environment and averagelatitude of the distribution of bird species present at local communities. We used multiple regression models to relate the variation in climate change indicators to: i) environmental temperature; and ii) three landscape gradients reflecting important current land use change processes (land abandonment, fire impacts and urbanization), all of them having forest areas at their positive extremes. We found that, with few exceptions, landscape gradients determined the figures of climate change indicators as strongly as temperature. Bird communities in forest habitats had colder-dwelling bird species with more northerndistributions than farmland, burnt or urban areas. Our results show that land use changes can reverse, hide or exacerbate our perception of climate change impacts when measured through community-level climate change indicators. We stress the need of an explicit incorporation of the interactions between climate change and land use dynamics to understand what are current climate change indicators indicating and be able to isolate real climate change impacts

El Land-Art a l'educació 0-3: l'expressió lliure i la comprensió del medi a través de l'art i la natura

Actualment el Land – Art és un moviment poc conegut i difós en la vessant educativa. Aquest treball pretén treure a la llum i transmetre l’essència d’aquest moviment enriquidor cap als infants. Tant és així, que el Land – Art esdevé una eina d’aprenentatge innovadora en el primer cicle d’Educació Infantil a través d’una metodologia constructivista que involucra a tota la comunitat educativa: professionals, família i alumnes. L’objectiu del present projecte és l’ús d’aquest moviment com instrument d’aprenentatge per tal d’observar i analitzar uns resultats que s’han anat construint a partir d’una hipòtesi: “El Land – Art a l’Educació 0-3 fomenta l’expressió lliure i la comprensió del medi”. En aquest treball trobarem, en primer lloc, el marc teòric del projecte; en segon lloc, el seu mètode d’investigació; en tercer lloc, la vessant pràctica del projecte; i, en quart i darrer lloc, les conclusions que reflecteixen la part comparativa entre el marc teòric i la part pràctica, on es finalitzarà amb les reflexions finals.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Application of the Mutual Information Minimization to speaker recognition / identification improvement

In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results for speaker recognition shows that a combination of several strategies can improve the recognition rates with saturated test sentences from 80% to 89.39%, while the results with clean speech (without saturation) is 87.76% for one microphone, and for speaker identification can reduce the minimum detection cost function with saturated test sentences from 6.42% to 4.15%, while the results with clean speech (without saturation) is 5.74% for one microphone and 7.02% for the other one.

Improving a leaves automatic recognition process using PCA

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Empirical mode decomposition-based face recognition system

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.

Does land titling matter? The role of land property rights in the war on illicit crops in Colombia

This paper analyzes the role of formalization of land property rights in the war against illicit crops in Colombia. We argue that as a consequence of the increase of state presence and visibility during the period of 2000 and 2009, municipalities with a higher level of formalization of their land property rights saw a greater reduction in the area allocated to illicit crops. We hypothesize that this is due to the increased cost of growing illicit crops on formal land compared to informal, and due to the possibility of obtaining more benets in the newly in- stalled institutional environment when land is formalized. We exploit the variation in the level of formalization of land property rights in a set of municipalities that had their rst cadastral census collected in the period of 1994-2000; this selection procedure guarantees reliable data and an unbiased source of variation. Using fixed effects estimators, we found a signicant negative relationship between the level of formalization of land property rights and the number of hectares allocated to coca crops per municipality. These results remain robust through a number of sensitivity analyses. Our ndings contribute to the growing body of evidence on the positive effects of formal land property rights, and e ective policies in the war on drugs in Colombia.