APPLICATION OF REMOTE SENSING IN AQUATIC ECOSYSTEMS

I utilized state the art remote sensing and GIS (Geographical Information System) techniques to study large scale biological, physical and ecological processes of coastal, nearshore, and offshore waters of Lake Michigan and Lake Superior. These processes ranged from chlorophyll a and primary production time series analysies in Lake Michigan to coastal stamp sand threats on Buffalo Reef in Lake Superior. I used SeaWiFS (Sea-viewing Wide Field-of-view Sensor) satellite imagery to trace various biological, chemical and optical water properties of Lake Michigan during the past decade and to investigate the collapse of early spring primary production. Using spatial analysis techniques, I was able to connect these changes to some important biological processes of the lake (quagga mussels filtration). In a separate study on Lake Superior, using LiDAR (Light Detection and Ranging) and aerial photos, we examined natural coastal erosion in Grand Traverse Bay, Michigan, and discussed a variety of geological features that influence general sediment accumulation patterns and interactions with migrating tailings from legacy mining. These sediments are moving southwesterly towards Buffalo Reef, creating a threat to the lake trout and lake whitefish breeding ground.

Prevalencia e incidencia de cáncer en habitantes de Sibaté, y georeferenciación de casos 2010-2014

Introducción: El Cáncer es prevenible en algunos casos, si se evita la exposición a sustancias cancerígenas en el medio ambiente. En Colombia, Cundinamarca es uno de los departamentos con mayores incrementos en la tasa de mortalidad y en el municipio de Sibaté, habitantes han manifestado preocupación por el incremento de la enfermedad. En el campo de la salud ambiental mundial, la georreferenciación aplicada al estudio de fenómenos en salud, ha tenido éxito con resultados válidos. El estudio propuso usar herramientas de información geográfica, para generar análisis de tiempo y espacio que hicieran visible el comportamiento del cáncer en Sibaté y sustentaran hipótesis de influencias ambientales sobre concentraciones de casos. Objetivo: Obtener incidencia y prevalencia de casos de cáncer en habitantes de Sibaté y georreferenciar los casos en un periodo de 5 años, con base en indagación de registros. Metodología: Estudio exploratorio descriptivo de corte transversal,sobre todos los diagnósticos de cáncer entre los años 2010 a 2014, encontrados en los archivos de la Secretaria de Salud municipal. Se incluyeron unicamente quienes tuvieron residencia permanente en el municipio y fueron diagnosticados con cáncer entre los años de 2010 a 2104. Sobre cada caso se obtuvo género, edad, estrato socioeconómico, nivel académico, ocupación y estado civil. Para el análisis de tiempo se usó la fecha de diagnóstico y para el análisis de espacio, la dirección de residencia, tipo de cáncer y coordenada geográfica. Se generaron coordenadas geográficas con un equipo GPS Garmin y se crearon mapas con los puntos de la ubicación de las viviendas de los pacientes. Se proceso la información, con Epi Info 7 Resultados: Se encontraron 107 casos de cáncer registrados en la Secretaria de Salud de Sibaté, 66 mujeres, 41 hombres. Sin división de género, el 30.93% de la población presento cáncer del sistema reproductor, el 18,56% digestivo y el 17,53% tegumentario. Se presentaron 2 grandes casos de agrupaciones espaciales en el territorio estudiado, una en el Barrio Pablo Neruda con 12 (21,05%) casos y en el casco Urbano de Sibaté con 38 (66,67%) casos. Conclusión: Se corroboro que el análisis geográfico con variables espacio temporales y de exposición, puede ser la herramienta para generar hipótesis sobre asociaciones de casos de cáncer con factores ambientales.

STAR Modeling of Pulmonary Tuberculosis Delay-Time in Diagnosis

Understanding what characterizes patients who suffer great delays in diagnosis of pulmonary tuberculosis is of great importance when establishing screening strategies to better control TB. Greater delays in diagnosis imply a higher chance for susceptible individuals to become infected by a bacilliferous patient. A Structured Additive Regression model is attempted in this study in order to potentially contribute to a better characterization of bacilliferous prevalence in Portugal. The main findings suggest the existence of significant regional differences in Portugal, with the fact of being female and/or alcohol dependent contributing to an increased delay-time in diagnosis, while being dependent on intravenous drugs and/or being diagnosed with HIV are factors that increase the chance of an earlier diagnosis of pulmonary TB. A decrease in 2010 to 77% on treatment success in Portugal underlines the importance of conducting more research aimed at better TB control strategies.

SISTEMA DE INFORMACIÓN GEOGRÁFICA PARA EL ANÁLISIS ESPACIAL DE LA PESQUERÍA ARTESANAL ASENTADA EN LA PENÍNSULA DE ARAYA, ESTADO SUCRE – VENEZUELA

Se desarrolló un Sistema de Información Geográfica (SIG) automatizado para el análisis espacial de las capturas, del esfuerzo pesquero, de la abundancia estimada de especies mediante el índice de Captura por Unidad de Esfuerzo (CPUE) y de su relación con algunos factores ambientales (profundidad, tipo de fondo y temperatura superficial del mar) de la esquería artesanal asentada en la península de Araya, Estado Sucre, República de Venezuela. Este programa automatizado, denominado SIGPAR, fue desarrollado utilizando el lenguaje Microsoft® Visual Basic 6 y la respectiva librería del software SIG Idrisi®, a cuyo menú principal fue agregado un nuevo módulo que facilita la interacción con los usuarios.Palabras claves: Sistema de Información Geográfica (SIG); pesquería artesanal; Península de Araya, Venezuela.AbstractA Geographic Information System (GIS) application software was developed for the spatial analysis of fishing catches, the estimated abundance of species by the Catch per Unit Effort (CPUE) index, and its relationship with various environmental factors (depth, type of bottom, and surface temperature of the sea) of the artisanal fishery based in the Peninsula of Araya, State of Sucre, in Venezuela. This application, named SIGPAR, was developed using Microsoft® Visual Basic 6 and IDRISI®. A menu button was added to the GIS software IDRISI® for convenience of users.Key Words: Geographic Information System (GIS), Artisanal Fisheries, Araya, Venezuela.

SISTEMAS DE INFORMACIÓN GEOGRÁFICA COMO HERRAMIENTA PARA EVALUAR LA APORTACIÓN ANTROPICA DE MERCURIO EN SUELOS

Este trabajo evalúa el contendido y la variabilidad espacial de mercurio en suelos agrícolas de Islas Baleares y Canarias utilizando técnicas integradas en los sistemas de información geográfica. El propósito de este estudio ha sido valorar el contenido y distribución del mercurio en el suelo y distinguir la contribución considerada como natural, y procedente del aporte de la roca de origen, de la inducida por actividades humanas, considerada como contaminante. El SIG se muestra comouna tecnología capaz de localizar fuentes de contaminación y proporcionar el alcance de éstos. Los mapas generados con la relación de Hg_suelo/Hg_roca han permitido cuantificar las entradas de este metal en el suelo y evaluar el enriquecimiento de mercurio en el mismo. Valores excesivamente elevados encontrados en un área de la Isla de Mallorca son atribuibles a las emisiones de una planta eléctrica de carbón cercana.PALABRAS CLAVE: Análisis espacial, SIG, geostadística, mercurio, contaminación de suelos.ABSTRACTThis study assesses Hg concentration and the spatial variability of mercury in agricultural soils of the Balearic and Canary Islands using integrated techniques of geographic information systems. The purpose of this study was to characterize in quantitative terms the mercury concentrations and to distinguish “natural” mercury contribution from that of human-induced contamination. GIS is shown to be technologically capable of locating sources of pollution and assessing their scope. The top soil/rock mercury content maps showed a high level of mercury in the same areas. Excessively high Hg values found in an area of the island of Mallorca are attributable to emissions from a coalfired power plant nearby.KEYWORDS: Spatial analysis, GIS, geostatistic, mercury, soil contamination

EVALUACIÓN DE HÁBITAT POTENCIAL PARA LA DANTA CENTROAMERICANA (TAPIRUS BAIRDII) EN EL CORREDOR BIOLÓGICO SAN JUAN-LA SELVA, COSTA RICA

La danta centroamericana (Tapirus bairdii) es el mamífero terrestre de mayor tamaño en el Neotrópico. Es un importante dispersor de semillas que contribuye al enriquecimiento de especies en los bosques donde habita. Varios estudios ecológicos han permitido conocer esta especie discreta; sin embargo, su distribución y el tamaño de sus poblaciones permanece sensiblemente desconocido fuera de las áreas silvestres protegidas. El propósito de esta investigación consistió en proponer una metodología de análisis geo-espacial sencilla que permitiera realizar una evaluación rápida del hábitat potencial para la danta centroamericana. Se seleccionaron siete variables de la ecología de la danta centroamericana, las cuales fueron evaluadas en el Corredor Biológico San Juan-La Selva, mediante un sistema de información geográfica (SIG). Estimamos la población de dantas con un rango de 69 a 208 individuos. Esto es una manera barata de determinar la viabilidad del hábitat de la danta cuando existe información confiable sobre los procesos dinámicos de los ecosistemas presentes en el área del estudio.Palabras clave: Tapiridae, danta centroamericana, Tapirus bairdii, evaluación de hábitat, analisis geo-espacial, Corredor Biológico San Juan-La Selva, Costa RicaAbstract: Baird’s Tapir (Tapirus bairdii) is the largest terrestrial mammal in the Neotropics. It is an important seed disperser that contributes to the enrichment of species in the forests where it lives. Several ecological studies on this species have generated knowledge about this discreet species; nevertheless, its distribution and the size of its populations outside protected wildlife areas sensibly remain unknown. The purpose of this investigation consisted in proposing a simple methodology of geo-space analysis that allowed realizing a fast evaluation of the potential habitat for Baird’s Tapir. Seven variables of the ecology of Baird’s Tapir were selected, which were evaluated in the San Juan-La Selva Biological Corridor, using a geographical information system (GIS) program. We estimated the tapir population to range from 69 to 208 individuals. This is an inexpensive way to assess Tapir’s habitat viability when there is a strong knowledge about the dynamic processes from the ecosystems present in the study area.Key Words: Tapiridae, Baird’s Tapir, Tapirus bairdii, habitat viability assessment, geo-spatial analysis, San Juan-La Selva Biological Corridor, Costa Rica

HACIA UNA GEOGRAFÍA DE REDES: UN NUEVO PARADIGMA DE ANÁLISIS ESPACIAL ALTERNATIVO AL ENFOQUE REGIONAL

En este artículo se pretende rescatar el análisis de redes independientemente del enfoque aureolar, destacando sus virtudes en un mundo globalizado, en donde cada vez más el concepto de distancia es sustituido por de tiempo, hasta llegar al extremo de que el costo, de algunos productos o la información, ya no depende de la distancia como el caso de las tarifas planas de Internet. Se aborda un enfoque teórico metodológico que cuestiona  el  análisis  regional,  debido  a  que,  éste  enfoque  en  algunos  aspectos  ya  no puede  resolver  los  problemas  que  la  sociedad  actual  demanda.   En  el  espacio  red,la noción de  localización absoluta pierde vigencia, mientras se refuerza  la  importancia de la  conexión  a  las  redes. Las metodologías  propuestas,  podrían mejorar  la  ejecución  y operación  de  las  redes    presentes  en  los planes  de  ordenamiento  del  territorio,  tan  en boga, en nuestro país. Abstract:In  this article  it  is  tried  to rescue  the analysis of networks  independently of the approach  to  aureole, emphasizing  its  virtues  in a globalized world,  in where more and more the distance concept is replaced by the time, until arriving at the end of which the cost, no  longer depends on  the distance as  the case of  the  flat  tariffs of Internet. A theoretical/ methodological approach  that questions  the regional analysis, because,  this one approach  in some aspects no longer can solve the problems that the present society demand.  In  the  space  network,  the  notion  of  absolute  location  loses  use  while  the importance  of  the  connection  to  the  networks  is  reinforced.  The  proposed methodologies  could  improve  the  boarding  of  the  present  networks  in  the  regulating plans, so in rows, our country.

GEOGRAFÍA CULTURAL E IDENTIDAD TERRITORIAL: EL CASO DE LA COMUNIDAD DE CABUYA, DISTRITO DE CÓBANO, PUNTARENAS, 2009

El artículo hace referencia a un encuadre teórico desde la geografía cultural, a partir de una sistematización de fuentes bibliográficas seleccionadas, para explicar el análisis espacial a escala local integrando la variable “identidad territorial”. Con tal propósito se elaboró un instrumento que permite identificar dónde es posible señalar rasgos de identidad territorial en la población de Cabuya, con el fin de que la información recopilada sea utilizada como insumo de intervención, en el proceso de participación ciudadana en los talleres que realiza la Universidad Nacional (UNA) para elaborar un plan estratégico en dicha comunidad. ABSTRACT The article refers to a theoretical framework from cultural geography, referring to a bibliographical system of selected sources that explain the spatial analysis to local scale integrating the variable “territorial identity”. With this in mind, we developed a tool to identify, where possible, features of territorial identity in the population of Cabuya so that the compiled information could be used as an input of intervention in the process of citizen participation in workshops conducted by Universidad Nacional to develop a strategic plan for the community of Cabuya.

Design of a preliminary error impact analysis model for spatial safety assessment of earthmoving operations

Regardless of technology benefits, safety planners still face difficulties explaining errors related to the use of different technologies and evaluating how the errors impact the performance of safety decision making. This paper presents a preliminary error impact analysis testbed to model object identification and tracking errors caused by image-based devices and algorithms and to analyze the impact of the errors for spatial safety assessment of earthmoving and surface mining activities. More specifically, this research designed a testbed to model workspaces for earthmoving operations, to simulate safety-related violations, and to apply different object identification and tracking errors on the data collected and processed for spatial safety assessment. Three different cases were analyzed based on actual earthmoving operations conducted at a limestone quarry. Using the testbed, the impacts of the errors were investigated for the safety planning purpose.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

Environmental and economic evaluation of N fertilizer rates in a maize crop in Italy : a spatial and temporal analysis using crop models

Crop simulation models have the potential to assess the risk associated with the selection of a specific N fertilizer rate, by integrating the effects of soil-crop interactions on crop growth under different pedo-climatic and management conditions. The objective of this study was to simulate the environmental and economic impact (nitrate leaching and N2O emissions) of a spatially variable N fertilizer application in an irrigated maize field in Italy. The validated SALUS model was run with 5 nitrogen rates scenarios, 50, 100, 150, 200, and 250 kg N ha−1, with the latter being the N fertilization adopted by the farmer. The long-term (25 years) simulations were performed on two previously identified spatially and temporally stable zones, a high yielding and low yielding zone. The simulation results showed that N fertilizer rate can be reduced without affecting yield and net return. The marginal net return was on average higher for the high yield zone, with values ranging from 1550 to 2650 € ha−1 for the 200 N and 1485 to 2875 € ha−1 for the 250 N. N leaching varied between 16.4 and 19.3 kg N ha−1 for the 200 N and the 250 N in the high yield zone. In the low yield zone, the 250 N had a significantly higher N leaching. N2O emissions varied between 0.28 kg N2O ha−1 for the 50 kg N ha−1 rate to a maximum of 1.41 kg N2O ha−1 for the 250 kg N ha−1 rate.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.