Germana Manca

A new method for determining the population with walking access to transit

The use of geographic information systems in determining transit service areas has not progressed far beyond simple buffering operations even though there is widespread capability to analyze network walking distances in conjunction with demographic, cadastral, and land-use data sets. This article presents a method for determining the population with walking access to bus stop locations using the spatial and aspatial attributes of parcels and the network distances from parcels to bus stop locations. This parcel-network method avoids the well-known and unrealistic assumptions associated with the existing methods and reduces overestimation of the population with access to transit, resulting in improved spatial precision and superior inputs to transit service decision-making processes. Comparisons of the parcel-network method, the buffer method, and the network-ratio method are made in a study area within the Dallas metropolitan area. The novel integration of cadastral data with network analysis in our method holds promise for research in many areas of geographic information science.

Risk analysis for dengue suitability in Africa using the ArcGIS predictive analysis tools (PA tools).

BACKGROUND Risk maps identifying suitable locations for infection transmission are important for public health planning. Data on dengue infection rates are not readily available in most places where the disease is known to occur. METHODS A newly available add-in to Esris ArcGIS software package, the ArcGIS Predictive Analysis Toolset (PA Tools), was used to identify locations within Africa with environmental characteristics likely to be suitable for transmission of dengue virus. RESULTS A more accurate, robust, and localized (1 km × 1 km) dengue risk map for Africa was created based on bioclimatic layers, elevation data, high-resolution population data, and other environmental factors that a search of the peer-reviewed literature showed to be associated with dengue risk. Variables related to temperature, precipitation, elevation, and population density were identified as good predictors of dengue suitability. Areas of high dengue suitability occur primarily within West Africa and parts of Central Africa and East Africa, but even in these regions the suitability is not homogenous. CONCLUSION This risk mapping technique for an infection transmitted by Aedes mosquitoes draws on entomological, epidemiological, and geographic data. The method could be applied to other infectious diseases (such as Zika) in order to provide new insights for public health officials and others making decisions about where to increase disease surveillance activities and implement infection prevention and control efforts. The ability to map threats to human and animal health is important for tracking vectorborne and other emerging infectious diseases and modeling the likely impacts of climate change.

Fuzzy Analysis for Modeling Regional Delineation and Development: The Case of the Sardinian Mining Geopark

Although defining geographic regions for analysis can be a complex exercise, involving both physical and human geographic perspectives, employing both qualitative and quantitative data, and integrating a wide range of social, economic, and political factors, it is frequently a necessary exercise in the pursuit of regional development. This article presents a method for modeling and delineating regions with fuzzy analysis for the purpose of regional development. A review of the literature regarding fuzzy analysis is provided, which demonstrates that this method is both novel and necessary. An application of this method is described in the context of the Sardinian Geopark. The fuzzy clustering analysis demonstrates how combinations of factors can inform decisions regarding where and how to initiate or continue regional development efforts. Suggestions for improvements and extensions to this process are provided.

Damage Assessment of the 2011 Japanese Tsunami Using High-Resolution Satellite Data

Department of Geography and Geoinformation Science / George Mason University / Fairfax / VA / USAIntroductionOn 11 March 2011 at 05:46 UTC, a massive Mw 9.0underwater earthquake occurred 70 km off the easterncoast of Japan. The location of the earthquake was trian-gulated by the United States Geological Survey (USGS) to38.322 N 142.369 E, and the hypocentre was computedto 32 km beneath the surface. Figure 1 shows a map ofthe earthquakes that occurred between 1 and 10 March2011 (a) and between 11 and 31 March 2011 (b). Theearthquake of 11 March generated a tsunami that rapidlyhit the eastern coast of Japan and propagated across thePacific Ocean to the western coast of the Americas. Atsunami warning was issued by the National Oceanic andAtmospheric Agency (NOAA) affecting all countries withcoastline along the Pacific.

Assessing the methods needed for improved dengue mapping: a SWOT analysis.

Introduction Dengue fever, a mosquito-borne viral infection, is a growing threat to human health in tropical and subtropical areas worldwide. There is a demand from public officials for maps that capture the current distribution of dengue and maps that analyze risk factors to predict the future burden of disease. Methods To identify relevant articles, we searched Google Scholar, PubMed, BioMed Central, and WHOLIS (World Health Organization Library Database) for published articles with a specific set of dengue criteria between January 2002 and July 2013. Results After evaluating the currently available dengue models, we identified four key barriers to the creation of high-quality dengue maps: (1) data limitations related to the expense of diagnosing and reporting dengue cases in places where health information systems are underdeveloped; (2) issues related to the use of socioeconomic proxies in places with limited dengue incidence data; (3) mosquito ranges which may be changing as a result of climate changes; and (4) the challenges of mapping dengue events at a variety of scales. Conclusion An ideal dengue map will present endemic and epidemic dengue information from both rural and urban areas. Overcoming the current barriers requires expanded collaboration and data sharing by geographers, epidemiologists, and entomologists. Enhanced mapping techniques would allow for improved visualizations of dengue rates and risks.

Combined approach of a couple fire model with atmospheric releases: the case of the 2003 Glacier wildfires

Abstract A combined GIS and remote sensing approach is applied to map and model the Glacier National Park wildfires of the summer 2003. Numerical simulations were performed using the Clarke Fire Automaton Model, and the fire extents were associated with the atmospheric plumes, observed using remote sensing data from the MODerate resolution Imaging Spectro-radiometer and Total Ozone Mapping Spectrometer. The wildfire simulation results show a correlation between the predicted and the actual fires. Remote sensing data are used to quantify the optical dimming of the atmosphere caused by the fires. The observed atmospheric dimming is correlated both spatially and temporally, with the fire simulations. Such knowledge is crucial to build a coupled land-atmosphere fire model.

Waiting to Know the Future: A SLEUTH Model Forecast of Urban Growth with Real Data

ABSTRACT What is the true value of simulation modelling to urban growth? This article assesses the validity of an integrated approach, based on the SLEUTH Model and land-use planning theory, as used to create an eight-year forecast in 1998. With actual data on the extent of urbanization in 2006 now available, the authors find that the 1998 forecasts were accurate. The case study is located in Macomer, an inland municipality of Sardinia, Italy, an island in the central Mediterranean Sea. Noting that data collection is an essential first step of planning, the authors assess Macomers land-use history, geography, economy, and demographics as context for more integrated and holistic planning than has been undertaken in the region to date. The 1998 calibration and prediction of the Urban Growth Model, a component of SLEUTH, simulated Macomers urban growth for the following eight years and has been reviewed and statistically validated. With detailed geographical results, the authors confirm that the 1998 simul...

Modeling European agri-environmental measure of spatial impact in the region of Sardinia, Italy, through fuzzy clustering means

The aim of this paper is to demonstrate how a spatial fuzzy clustering mean expands the knowledge of the European agri-environmental initiative impact, named Measure 214, in the Sardinia Region. While sketching out the geographic area covered by the measure for analysis and investigation using fcm is a fruitful approach, their integration with social and economic factors is an essential step in understanding agricultural growth and how it is influenced by environmental policy. This integrated approach shows how agri-environmental measures tend to develop in the region and, geographically, describes the spatial effects. Fuzzy clustering analysis demonstrates how decisions, whether they are related to the pursuit of policies moving towards the agri-environmental initiatives of organic farming and sustainable agriculture, or whether they concern ways of financing the measure’s activities, belong to the sphere of information, able to influence the new phase of agri-environmental financing and to keep it going. The spatial expansion of the measure all over the Region can help identify where the measure has taken root and in which directions it should be steered to achieve sustainable agri-environmental development in the area. Furthermore, the fuzzy cluster analysis highlights the relevance of the results, showing the policy direction that clusters should take in order to improve the measure’s effectiveness.

Atmospheric releases during the 2003 glacier wildfires: Mapping, analysis and modeling

A combined GIS and remote sensing approach to map and model the large wildfires in the summer 2003 at Glacier National Park. Numerical simulations were performed using the Clarke cellular automaton fire model, and the fire extents were validated using remote sensing data from the MODIS instrument. The results show a good correlation between the predicted fires and the actual. In addition, remote sensing data from the MODIS and TOMS instruments are used to quantify the optical dimming of the atmosphere caused by the fires. Atmospheric dimming correlated both spatially and temporally with the amount of burned fuel computed by the Clarke model. The observed atmospheric dimming is correlated both spatially and temporally with the fire simulations. Such knowledge is crucial in order to build a coupled land-atmosphere fire model.