996 resultados para geospatial analysis
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A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.
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Utilizing remote sensing methods to assess landscape-scale ecological change are rapidly becoming a dominant force in the natural sciences. Powerful and robust non-parametric statistical methods are also actively being developed to compliment the unique characteristics of remotely sensed data. The focus of this research is to utilize these powerful, robust remote sensing and statistical approaches to shed light on woody plant encroachment into native grasslands--a troubling ecological phenomenon occurring throughout the world. Specifically, this research investigates western juniper encroachment within the sage-steppe ecosystem of the western USA. Western juniper trees are native to the intermountain west and are ecologically important by means of providing structural diversity and habitat for many species. However, after nearly 150 years of post-European settlement changes to this threatened ecosystem, natural ecological processes such as fire regimes no longer limit the range of western juniper to rocky refugia and other areas protected from short fire return intervals that are historically common to the region. Consequently, sage-steppe communities with high juniper densities exhibit negative impacts, such as reduced structural diversity, degraded wildlife habitat and ultimately the loss of biodiversity. Much of today's sage-steppe ecosystem is transitioning to juniper woodlands. Additionally, the majority of western juniper woodlands have not reached their full potential in both range and density. The first section of this research investigates the biophysical drivers responsible for juniper expansion patterns observed in the sage-steppe ecosystem. The second section is a comprehensive accuracy assessment of classification methods used to identify juniper tree cover from multispectral 1 m spatial resolution aerial imagery.
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Manual and low-tech well drilling techniques have potential to assist in reaching the United Nations' millennium development goal for water in sub-Saharan Africa. This study used publicly available geospatial data in a regression tree analysis to predict groundwater depth in the Zinder region of Niger to identify suitable areas for manual well drilling. Regression trees were developed and tested on a database for 3681 wells in the Zinder region. A tree with 17 terminal leaves provided a range of ground water depth estimates that were appropriate for manual drilling, though much of the tree's complexity was associated with depths that were beyond manual methods. A natural log transformation of groundwater depth was tested to see if rescaling dataset variance would result in finer distinctions for regions of shallow groundwater. The RMSE for a log-transformed tree with only 10 terminal leaves was almost half that of the untransformed 17 leaf tree for groundwater depths less than 10 m. This analysis indicated important groundwater relationships for commonly available maps of geology, soils, elevation, and enhanced vegetation index from the MODIS satellite imaging system.
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Background. Cytomegalovirus (CMV) is a common cause of birth defects and hearing loss in infants and opportunistic infections in the immunocompromised. Previous studies have found higher CMV seroprevalence rates among minorities and among persons with lower socioeconomic status. No studies have investigated the geographic distribution of CMV and its relationship to age, race, and poverty in the community. Methods. We identified patients from 6 North Carolina counties who were tested in the Duke University Health System for CMV immunoglobulin G. We performed spatial statistical analyses to analyze the distributions of seropositive and seronegative individuals. Results. Of 1884 subjects, 90% were either white or African American. Cytomegalovirus seropositivity was significantly more common among African Americans (73% vs 42%; odds ratio, 3.31; 95% confidence interval, 2.7-4.1), and this disparity persisted across the life span. We identified clusters of high and low CMV odds, both of which were largely explained by race. Clusters of high CMV odds were found in communities with high proportions of African Americans. Conclusions. Cytomegalovirus seropositivity is geographically clustered, and its distribution is strongly determined by a community's racial composition. African American communities have high prevalence rates of CMV infection, and there may be a disparate burden of CMV-associated morbidity in these communities.
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Quantitative measures of polygon shapes and orientation are important elements of geospatial analysis. These kinds of measures are particularly valuable in the case of lakes, where shape and orientation patterns can help identifying the geomorphological agents behind lake formation and evolution. However, the lack of built-in tools in commercial geographic information system (GIS) software packages designed for this kind of analysis has meant that many researchers often must rely on tools and workarounds that are not always accurate. Here, an easy-to-use method to measure rectangularity R, ellipticity E, and orientation O is developed. In addition, a new rectangularity vs. ellipticity index, REi, is defined. Following a step-by-step process, it is shown how these measures and index can be easily calculated using a combination of GIS built-in functions. The identification of shapes and estimation of orientations performed by this method is applied to the case study of the geometric and oriented lakes of the Llanos de Moxos, in the Bolivian Amazon, where shape and orientation have been the two most important elements studied to infer possible formation mechanisms. It is shown that, thanks to these new indexes, shape and orientation patterns are unveiled, which would have been hard to identify otherwise.
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Os riscos de propagação de doenças com expressão epidémica ou pandémica, são, hoje, fenómenos que determinam insegurança na população e que autoridades de saúde procuram analisar, reduzir e comunicar. De forma a monitorizar e gerir os mecanismos de controlo, têm vindo a ser desenvolvidas a nível regional, nacional e continental infra-estruturas de gestão da Saúde Pública. Tais infra-estruturas recorrem normalmente a pesquisas e análises de dados alfanuméricos, compilados e armazenados em arquivos locais e centrais por hospitais e outros serviços de saúde, sendo a sua disponibilização e tratamento muito limitados B área geográfica onde são registados. Com o crescimento dos serviços disponíveis na Internet aumentou também a capacidade de partilha de conhecimentos e de informação, possibilitando uma apreciação mais frequente e abrangente de situações anómalas de Saúde Pública. Paralelamente, a análise e gesão desses dados numa perspectiva espacial, através de Sistemas de Informação Geográfica, tem vindo a ganhar consistência em inúmeras situações como, por exemplo, a contenção da propagação de epidemias. Este trabalho apresenta esses novos dispositivos já ensaiados em Portugal.
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Spatial analysis and social network analysis typically take into consideration social processes in specific contexts of geographical or network space. The research in political science increasingly strives to model heterogeneity and spatial dependence. To better understand and geographically model the relationship between “non-political” events, streaming data from social networks, and political climate was the primary objective of the current study. Geographic information systems (GIS) are useful tools in the organization and analysis of streaming data from social networks. In this study, geographical and statistical analysis were combined in order to define the temporal and spatial nature of the data eminating from the popular social network Twitter during the 2014 FIFA World Cup. The study spans the entire globe because Twitter’s geotagging function, the fundamental data that makes this study possible, is not limited to a geographic area. By examining the public reactions to an inherenlty non-political event, this study serves to illuminate broader questions about social behavior and spatial dependence. From a practical perspective, the analyses demonstrate how the discussion of political topics fluсtuate according to football matches. Tableau and Rapidminer, in addition to a set basic statistical methods, were applied to find patterns in the social behavior in space and time in different geographic regions. It was found some insight into the relationship between an ostensibly non-political event – the World Cup - and public opinion transmitted by social media. The methodology could serve as a prototype for future studies and guide policy makers in governmental and non-governmental organizations in gauging the public opinion in certain geographic locations.
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Finland’s rural landscape has gone through remarkable changes from the 1950’s, due to agricultural developments. Changed farming practices have influenced especially traditional landscape management, and modifications in the arable land structure and grasslands transitions are notable. The review of the previous studies reveal the importance of the rural landscape composition and structure to species and landscape diversity, whereas including the relevance in presence of the open ditches, size of the field and meadow patches, topology of the natural and agricultural landscape. This land-change study includes applying remote sensed data from two time series and empirical geospatial analysis in Geographic Information Systems (GIS). The aims of this retrospective research is to detect agricultural landscape use and land cover change (LULCC) dynamics and discuss the consequences of agricultural intensification to landscape structure covering from the aspects of landscape ecology. Measurements of LULC are derived directly from pre-processed aerial images by a variety of analytical procedures, including statistical methods and image interpretation. The methodological challenges are confronted in the process of landscape classification and combining change detection approaches with landscape indices. Particular importance is paid on detecting agricultural landscape features at a small scale, demanding comprehensive understanding of such agroecosystems. Topological properties of the classified arable land and valley are determined in order to provide insight and emphasize the aspect the field edges in the agricultural landscape as important habitat. Change detection dynamics are presented with change matrix and additional calculations of gain, loss, swap, net change, change rate and tendencies are made. Transition’s possibility is computed following Markov’s probability model and presented with matrix, as well. Thesis’s spatial aspect is revealed with illustrative maps providing knowledge of location of the classified landscape categories and location of the dynamics of the changes occurred. It was assured that in Rekijoki valley’s landscape, remarkable changes in landscape has occurred. Landscape diversity has been strongly influenced by modern agricultural landscape change, as NP of open ditches has decreased and the MPS of the arable plot has decreased. Overall change in the diversity of the landscape is determined with the decrease of SHDI. Valley landscape considered as traditional land use area has experienced major transitional changes, as meadows class has lost almost one third of the area due to afforestation. Also, remarkable transitions have occurred from forest to meadow and arable land to built area. Boundaries measurement between modern and traditional landscape has indicated noticeable proportional increase in arable land-forest edge type and decrease in arable land-meadow edge type. Probability calculations predict higher future changes for traditional landscape, but also for arable land turning into built area.
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SEXTANTE es un marco para el desarrollo de algoritmos dedicados al procesamiento de información geográficamente referenciada, que actualmente cuenta con más de doscientos algoritmos que son capaces de operar sobre datos vectoriales, alfanuméricos y raster. Por otra parte, GearScape es un sistema de información geográfico orientado al geoprocesamiento, que dispone de un lenguaje declarativo que permite el desarrollo de geoprocesos sin necesidad de herramientas de desarrollo complejas. Dicho lenguaje está basado en el estándar SQL y extendido mediante la norma OGC para el acceso a fenómenos simples. Al ser un lenguaje mucho más simple que los lenguajes de programación imperativos (java, .net, python, etc.) la creación de geoprocesos es también más simple, más fácil de documentar, menos propensa a bugs y además la ejecución es optimizada de manera automática mediante el uso de índices y otras técnicas. La posibilidad de describir cadenas de operaciones complejas tiene también valor a modo de documentación: es posible escribir todos los pasos para la resolución de un determinado problema y poder recuperarlo tiempo después, reutilizarlo fácilmente, comunicárselo a otra persona, etc. En definitiva, el lenguaje de geoprocesamiento de GearScape permite "hablar" de geoprocesos. La integración de SEXTANTE en GearScape tiene un doble objetivo. Por una parte se pretende proporcionar la posibilidad de usar cualquiera de los algoritmos con la interfaz habitual de SEXTANTE. Por la otra, se pretende añadir al lenguaje de geoprocesamiento de GearScape la posibilidad de utilizar algoritmos de SEXTANTE. De esta manera, cualquier problema que se resuelva mediante la utilización de varios de estos algoritmes puede ser descrito con el lenguaje de geoprocesamiento de GearScape. A las ventajas del lenguaje de GearScape para la definición de geoprocesos, se añade el abanico de geoprocesos disponible en SEXTANTE, por lo que el lenguaje de geoprocesamiento de GearScape nos permite "hablar" utilizando vocabulario de SEXTANTE
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In different regions of Brazil, population growth and economic development can degrade water quality, compromising watershed health and human supply. Because of its ability to combine spatial and temporal data in the same environment and to create water resources management (WRM) models, the Geographical Information System (GIS) is a powerful tool for managing water resources, preventing floods and estimating water supply. This paper discusses the integration between GIS and hydrological models and presents a case study relating to the upper section of the Paraíba do Sul Basin (Sao Paulo State portion), situated in the Southeast of Brazil. The case study presented in this paper has a database suitable for the basin's dimensions, including digitized topographic maps at a 50,000 scale. From an ArcGIS®/ArcHydro Framework Data Model, a geometric network was created to produce different raster products. This first grid derived from the digital elevation model grid (DEM) is the flow direction map followed by flow accumulation, stream and catchment maps. The next steps in this research are to include the different multipurpose reservoirs situated along the Paraíba do Sul River and to incorporate rainfall time series data in ArcHydro to build a hydrologic data model within a GIS environment in order to produce a comprehensive spatial-temporal model.
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Pós-graduação em Engenharia Mecânica - FEG
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Pós-graduação em Medicina Veterinária - FCAV
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The Ecosystem Approach to Fisheries represents the most recent research line in the international context, showing interest both towards the whole community and toward the identification and protection of all the “critical habitats” in which marine resources complete their life cycles. Using data coming from trawl surveys performed in the Northern and Central Adriatic from 1996 to 2010, this study provides the first attempt to appraise the status of the whole demersal community. It took into account not only fishery target species but also by-catch and discharge species by the use of a suite of biological indicators both at population and multi-specific level, allowing to have a global picture of the status of the demersal system. This study underlined the decline of extremely important species for the Adriatic fishery in recent years; adverse impact on catches is expected for these species in the coming years, since also minimum values of recruits recently were recorded. Both the excessive exploitation and environmental factors affected availability of resources. Moreover both distribution and nursery areas of the most important resources were pinpointed by means of geostatistical methods. The geospatial analysis also confirmed the presence of relevant recruitment areas in the North and Central Adriatic for several commercial species, as reported in the literature. The morphological and oceanographic features, the relevant rivers inflow together with the mosaic pattern of biocenoses with different food availability affected the location of the observed relevant nursery areas.