Footprint of recycled water subsidies downwind of Lake Michigan

Continental evaporation is a significant and dynamic flux within the atmospheric water budget, but few methods provide robust observational constraints on the large-scale hydroclimatological and hydroecological impacts of this ‘recycled-water' flux. We demonstrate a geospatial analysis that provides such information, using stable isotope data to map the distribution of recycled water in shallow aquifers downwind from Lake Michigan. The δ2H and δ18O values of groundwater in the study region decrease from south to north, as expected based on meridional gradients in climate and precipitation isotope ratios. In contrast, deuterium excess (d = δ2H − 8 × δ18O) values exhibit a significant zonal gradient and finer-scale spatially patterned variation. Local d maxima occur in the northwest and southwest corners of the Lower Peninsula of Michigan, where ‘lake-effect' precipitation events are abundant. We apply a published model that describes the effect of recycling from lakes on atmospheric vapor d values to estimate that up to 32% of recharge into individual aquifers may be derived from recycled Lake Michigan water. Applying the model to geostatistical surfaces representing mean d values, we estimate that between 10% and 18% of the vapor evaporated from Lake Michigan is re-precipitated within downwind areas of the Lake Michigan drainage basin. Our approach provides previously unavailable observational constraints on regional land-atmosphere water fluxes in the Great Lakes Basin and elucidates patterns in recycled-water fluxes that may influence the biogeography of the region. As new instruments and networks facilitate enhanced spatial monitoring of environmental water isotopes, similar analyses can be widely applied to calibrate and validate water cycle models and improve projections of regional hydroecological change involving the coupled lake-atmosphere-land system. Read More: http://www.esajournals.org/doi/abs/10.1890/ES12-00062.1

Is the development of infectious keratoconjunctivitis in Alpine ibex and Alpine chamois influenced by topographic features?

Infectious keratoconjunctivitis (IKC) caused by Mycoplasma conjunctivae is a widespread ocular affection of free-ranging Caprinae in the Alpine arc. Along with host and pathogen characteristics, it has been hypothesized that environmental factors such as UV light are involved in the onset and course of the disease. This study aimed at evaluating the role of topographic features as predisposing or aggravating factors for IKC in Alpine chamois (Rupicapra rupicapra rupicapra) and Alpine ibex (Capra ibex ibex). Geospatial analysis was performed to assess the effect of aspect (northness) and elevation on the severity of the disease as well as on the mycoplasmal load in the eyes of affected animals, using data from 723 ibex and chamois (583 healthy animals, 105 IKC-affected animals, and 35 asymptomatic carriers of M. conjunctivae), all sampled in the Swiss Alps between 2008 and 2010. An influence of northness was not found, except that ibex with moderate and severe signs of IKC seem to prefer more north-oriented slopes than individuals without corneal lesions, possibly hinting at a sunlight sensitivity consequent to the disease. In contrast, results suggest that elevation influences the disease course in both ibex and chamois, which could be due to altitude-associated environmental conditions such as UV radiation, cold, and dryness. The results of this study support the hypothesis that environmental factors may play a role in the pathogenesis of IKC.

Mejora de la movilidad urbana sostenible en el municipio de Madrid : aplicación del análisis geoespacial en la ampliación de la red de suministro de combustibles alternativos.

Este Trabajo Fin de Grado trata de dar respuesta a un problema de movilidad sostenible en el municipio de Madrid. Mediante las herramientas de análisis geoespacial de los Sistemas de Información Geográfica (SIG) se buscan soluciones para la ampliación de la red de estaciones de suministro de combustibles alternativos como el Gas Licuado de Petróleo (GLP), Gas Natural Comprimido (GNC) y electricidad. Los resultados obtenidos determinan las posibles ubicaciones de los nuevos puntos atendiendo a criterios específicos según el tipo de combustible. Estas soluciones procuran que se alcancen las medidas impuestas por las directivas europeas en la materia de las Smart Cities. Además, con este Trabajo se muestran las capacidades de gestión de los SIG en el ámbito urbano y sus posibles aplicaciones. ABSTRACT: This Final Project answers the problem of sustainable mobility in the city of Madrid. By means of geospatial analysis tools of Geographic Information Systems (GIS) solutions are searched to extend the supply stations network for alternative fuels like Liquefied Petroleum Gas (LPG), Compressed Natural Gas (CNG) and electricity. The final results are the best possible locations of new items according to specific criteria depending on the type of fuel. These solutions seek to the measures imposed by the European directives are reached in the field of Smart Cities. In addition, This Final Project shows management capabilities of GIS in urban areas and their possible application.

WATER RESOURCES, HEALTH, AND THE SUSTAINABILITY OF INTERVENTIONS TO ACHIEVE WATER AND SANITATION TARGETS OF THE MILLENNIUM DEVELOPMENT GOALS IN A CHANGING WORLD

This dissertation addresses sustainability of rapid provision of safe water and sanitation required to meet the Millennium Development Goals. Review of health-related literature and global statistics demonstrates engineers' role in achieving the MDGs. This review is followed by analyses relating to social, environmental, and health aspects of meeting MDG targets. Analysis of national indicators showed that inadequate investment, poor or nonexistent policies and governance are challenges to global sanitation coverage in addition to lack of financial resources and gender disparity. Although water availability was not found to be a challenge globally, geospatial analysis demonstrated that water availability is a potentially significant barrier for up to 46 million people living in urban areas and relying on already degraded water resources for environmental income. A daily water balance model incorporating the National Resources Conservation Services curve number method in Bolivian watersheds showed that local water stress is linked to climate change because of reduced recharge. Agricultural expansion in the region slightly exacerbates recharge reductions. Although runoff changes will range from -17% to 14%, recharge rates will decrease under all climate scenarios evaluated (-14% to -27%). Increasing sewer coverage may place stress on the readily accessible natural springs, but increased demand can be sustained if other sources of water supply are developed. This analysis provides a method for hydrological analysis in data scarce regions. Data required for the model were either obtained from publicly available data products or by conducting field work using low-cost methods feasible for local participants. Lastly, a methodology was developed to evaluate public health impacts of increased household water access resulting from domestic rainwater harvesting, incorporating knowledge of water requirements of sanitation and hygiene technologies. In 37 West African cities, domestic rainwater harvesting has the potential to reduce diarrheal disease burden by 9%, if implemented alone with 400 L storage. If implemented in conjunction with point of use treatment, this reduction could increase to 16%. The methodology will contribute to cost-effectiveness evaluations of interventions as well as evaluations of potential disease burden resulting from reduced water supply, such as reductions observed in the Bolivian communities.

Exploratory geospatial data analysis using self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Urban sprawl analysis and modeling in Asmara, Eritreia: Application of Geospatial Tools

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

Spatio-temporal land use/land cover changes analysis and monitoring in the Valencia Municipality, Spain

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Urban land use change analysis and modelling: a case study of Setubal-Sesimbra, Portugal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Land use/ land cover change and its impact on soil erosion process in Begnas Tal Rupa Tal watershed using geospatial tools, Kaski district, Nepal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Geospatial database generation from digital newspapers: use case for risk and disaster domains.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

A qualitive reasoning approach for improving query results for sketch based queries by topological analysis of spatial aggregation

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.