Ontologías turísticas geográficas

Definición de una ontología que permita representar los aspectos relacionados con el ámbito turístico permitiendo definir la latitud y longitud de la información asociada.

Càlcul del volum de terres del subsól

Estudi d'un programari SIG: gvSIG, un programari lliure desenvolupat per iniciativa de la Conselleria d'Obres Públiques de la Generalitat Valenciana.

TFC SIG - cobertura sanitaria en zonas de catástrofe

Comando para trabajar con Geomedia Professional 6.1, que extiende la funcionalidad de la herramienta para adaptarla a un escenario en el cual se ayuda a la gestión de la cobertura sanitaria en zonas de catástrofe, en nuestro caso Haití.

Cobertura sanitaria en zonas de catástrofes

El objetivo de este trabajo es conseguir crear un Sistemas de Información Geográfica (SIG), adquiriendo por el camino todos los conocimientos necesarios para su realización. Este trabajo está estructuradoen 4 partes bien diferenciadas.

TFC-Sistemes d'informació geogràfica

L'objectiu d'aquest projecte és desenvolupar una aplicació que ens permeti generar representacions gràfiques de grafs de mobilitat, visualitzats amb l'entorn GeoMedia Professional. A partir d'unes bases de dades d'entrada, on els trams i les cruïlles seran representades visualment com a línies i punts respectivament, s'ha dissenyat una aplicació que genera una base de dades de sortida on les dades seran visualitzades com un polígons en el cas dels carrers i cruïlles, i la senyalització de cada tram també serà representada gràficament, de manera que tindrem una representació en dos dimensions dels carrers amb la seva senyalització corresponent.

Validation of Logistic Regression Models for Landslide Susceptibility Maps

A wide range of numerical models and tools have been developed over the last decades to support the decision making process in environmental applications, ranging from physical models to a variety of statistically-based methods. In this study, a landslide susceptibility map of a part of Three Gorges Reservoir region of China was produced, employing binary logistic regression analyses. The available information includes the digital elevation model of the region, geological map and different GIS layers including land cover data obtained from satellite imagery. The landslides were observed and documented during the field studies. The validation analysis is exploited to investigate the quality of mapping.

Atlas interactivo de mortalidad de Andalucía (AIMA)

Until now, mortality atlases have been static. Most of them describe the geographical distribution of mortality using count data aggregated over time and standardized mortality rates. However, this methodology has several limitations. Count data aggregated over time produce a bias in the estimation of death rates. Moreover, this practice difficult the study of temporal changes in geographical distribution of mortality. On the other hand, using standardized mortality hamper to check differences in mortality among groups. The Interactive Mortality Atlas in Andalusia (AIMA) is an alternative to conventional static atlases. It is a dynamic Geographical Information System that allows visualizing in web-site more than 12.000 maps and 338.00 graphics related to the spatio-temporal distribution of the main death causes in Andalusia by age and sex groups from 1981. The objective of this paper is to describe the methods used for AIMA development, to show technical specifications and to present their interactivity. The system is available from the link products in www.demap.es. AIMA is the first interactive GIS that have been developed in Spain with these characteristics. Spatio-temporal Hierarchical Bayesian Models were used for statistical data analysis. The results were integrated into web-site using a PHP environment and a dynamic cartography in Flash. Thematic maps in AIMA demonstrate that the geographical distribution of mortality is dynamic, with differences among year, age and sex groups. The information nowadays provided by AIMA and the future updating will contribute to reflect on the past, the present and the future of population health in Andalusia.

A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil

Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.

The Estrada Real project and endemic diseases: the case of schistosomiasis, geoprocessing and tourism

Geographical Information System (GIS) is a tool that has recently been applied to better understand spatial disease distributions. Using meteorological, social, sanitation, mollusc distribution data and remote sensing variables, this study aimed to further develop the GIS technology by creating a model for the spatial distribution of schistosomiasis and to apply this model to an area with rural tourism in the Brazilian state of Minas Gerais (MG). The Estrada Real, covering about 1,400 km, is the largest and most important Brazilian tourism project, involving 163 cities in MG with different schistosomiasis prevalence rates. The model with three variables showed a R² = 0.34, with a standard deviation of risk estimated adequate for public health needs. The main variables selected for modelling were summer vegetation, summer minimal temperature and winter minimal temperature. The results confirmed the importance of Remote Sensing data and the valuable contribution of GIS in identifying priority areas for intervention in tourism regions which are endemic to schistosomiasis.

Bovine tuberculosis in Doñana Biosphere Reserve: the role of wild ungulates as disease reservoirs in the last Iberian lynx strongholds.

Doñana National Park (DNP) in southern Spain is a UNESCO Biosphere Reserve where commercial hunting and wildlife artificial feeding do not take place and traditional cattle husbandry still exists. Herein, we hypothesized that Mycobacterium bovis infection prevalence in wild ungulates will depend on host ecology and that variation in prevalence will reflect variation in the interaction between hosts and environmental risk factors. Cattle bTB reactor rates increased in DNP despite compulsory testing and culling of infected animals. In this study, 124 European wild boar, 95 red deer, and 97 fallow deer were sampled from April 2006 to April 2007 and analyzed for M. bovis infection. Modelling and GIS were used to identify risk factors and intra and inter-species relationships. Infection with M. bovis was confirmed in 65 (52.4%) wild boar, 26 (27.4%) red deer and 18 (18.5%) fallow deer. In the absence of cattle, wild boar M. bovis prevalence reached 92.3% in the northern third of DNP. Wild boar showed more than twice prevalence than that in deer (p<0.001). Modelling revealed that M. bovis prevalence decreased from North to South in wild boar (p<0.001) and red deer (p<0.01), whereas no spatial pattern was evidenced for fallow deer. Infection risk in wild boar was dependent on wild boar M. bovis prevalence in the buffer area containing interacting individuals (p<0.01). The prevalence recorded in this study is among the highest reported in wildlife. Remarkably, this high prevalence occurs in the absence of wildlife artificial feeding, suggesting that a feeding ban alone would have a limited effect on wildlife M. bovis prevalence. In DNP, M. bovis transmission may occur predominantly at the intra-species level due to ecological, behavioural and epidemiological factors. The results of this study allow inferring conclusions on epidemiological bTB risk factors in Mediterranean habitats that are not managed for hunting purposes. Our results support the need to consider wildlife species for the control of bTB in cattle and strongly suggest that bTB may affect animal welfare and conservation.

Map of ecological networks for landscape planning

This paper presents a method based on a geographical information system (GIS) to model ecological networks in a fragmented landscape. The ecological networks are generated with the help of a landscape model (which integrate human activities) and with a wildlife dispersal model. The main results are maps which permit the analysis and the understanding of the impact of human activities on wildlife dispersal. Three applications in a study area are presented: ecological networks at the landscape scale, conflicting areas at the farmstead scale and ecological distance between biotopes. These applications show the flexibility of the model and its potential to give information on ecological networks at different planning scales.

Cluster recognition in spatial-temporal sequences: The case of forest fires

Forest fire sequences can be modelled as a stochastic point process where events are characterized by their spatial locations and occurrence in time. Cluster analysis permits the detection of the space/time pattern distribution of forest fires. These analyses are useful to assist fire-managers in identifying risk areas, implementing preventive measures and conducting strategies for an efficient distribution of the firefighting resources. This paper aims to identify hot spots in forest fire sequences by means of the space-time scan statistics permutation model (STSSP) and a geographical information system (GIS) for data and results visualization. The scan statistical methodology uses a scanning window, which moves across space and time, detecting local excesses of events in specific areas over a certain period of time. Finally, the statistical significance of each cluster is evaluated through Monte Carlo hypothesis testing. The case study is the forest fires registered by the Forest Service in Canton Ticino (Switzerland) from 1969 to 2008. This dataset consists of geo-referenced single events including the location of the ignition points and additional information. The data were aggregated into three sub-periods (considering important preventive legal dispositions) and two main ignition-causes (lightning and anthropogenic causes). Results revealed that forest fire events in Ticino are mainly clustered in the southern region where most of the population is settled. Our analysis uncovered local hot spots arising from extemporaneous arson activities. Results regarding the naturally-caused fires (lightning fires) disclosed two clusters detected in the northern mountainous area.

New tools for epidemiology: a space odyssey

Geographical Information Systems (GIS) facilitate access to epidemiological data through visualization and may be consulted for the development of mathematical models and analysis by spatial statistics. Variables such as land-cover, land-use, elevations, surface temperatures, rainfall etc. emanating from earth-observing satellites, complement GIS as this information allows the analysis of disease distribution based on environmental characteristics. The strength of this approach issues from the specific environmental requirements of those causative infectious agents, which depend on intermediate hosts for their transmission. The distribution of these diseases is restricted, both by the environmental requirements of their intermediate hosts/vectors and by the ambient temperature inside these hosts, which effectively govern the speed of maturation of the parasite. This paper discusses the current capabilities with regard to satellite data collection in terms of resolution (spatial, temporal and spectral) of the sensor instruments on board drawing attention to the utility of computer-based models of the Earth for epidemiological research. Virtual globes, available from Google and other commercial firms, are superior to conventional maps as they do not only show geographical and man-made features, but also allow instant import of data-sets of specific interest, e.g. environmental parameters, demographic information etc., from the Internet.

Análisis de plataformas para la publicación de información geográfica en la nube

Análisis de cinco plataformas, vía navegador, para crear mapas y compartirlos.

Biotic factors and occurrence of Lutzomyia longipalpis in endemic area of visceral leishmaniasis, Mato Grosso do Sul, Brazil

The relationships between environmental exposure to risk agents and health conditions have been studied with the aid of remote sensing imagery, a tool particularly useful in the study of vegetation cover. This study aims to evaluate the influence of environmental variables on the spatial distribution of the abundance of Lutzomyia longipalpis and the reported canine and human visceral leishmaniasis (VL) cases at an urban area of Campo Grande, state of Mato Grosso do Sul. The sandfly captures were performed in 13 residences that were selected by raffle considering four residences or collection station for buffer. These buffers were generated from the central house with about 50, 100 and 200 m from it in an endemic area of VL. The abundance of sandflies and human and canine cases were georreferenced using the GIS software PCI Geomatica. The normalized difference vegetation index (NDVI) and percentage of land covered by vegetation were the environmental variables extracted from a remote sensing IKONOS-2 image. The average NDVI was considered as the complexity of habitat and the standard deviation as the heterogeneity of habitat. One thousand three hundred sixty-seven specimens were collected during the catch. We found a significant positive linear correlation between the abundance of sandflies and the percentage of vegetation cover and average NDVI. However, there was no significant association between habitat heterogeneity and the abundance of these flies.