Dimitris Kavroudakis

Agritourism networks: empirical evidence from two case studies in Greece

This study investigates the characteristics of informal agritourism-related networks within destinations with the help of social network analysis by measuring macro and meso structural aspects of networks in two tourist destinations in Greece with different geographic characteristics: an island-Lesvos (in North Eastern Aegean) and a continental locality-Plastiras Lake (central part of Greece). The main objective is to illustrate and discuss quantitative and qualitative aspects of these networks with selected actors who are linked (directly or indirectly) with the agritourism sector through personal in-depth and semi-structured interviews. The quantitative aspects include: quantity of links, spatial extent of networks, type of relationship, its “thickness”, the duration of the relationship, issues of seasonality as well as satisfaction of the cooperation. The qualitative aspects include the type of relationship of the actors over the link and who (if anyone) has “control” over this relationship. The main findings indicate that the examined networks are partially affected by the geographic characteristics of the case studies and they are very similar in terms of absolute numbers and network metrics. Although research on networks has been an emerging and promising approach, qualitative characteristics of informal networks seem to be integral for understanding networks and planning tourism policies.

SimEducation: A Dynamic Spatial Microsimulation Model for Understanding Educational Inequalities

Spatial microsimulation models can be used to produce small area output for a deeper understanding of inequality. Dynamic spatial microsimulation models can be used to model transitions such as leaving home, entering school, university, the labour market, etc. This chapter presents a dynamic spatial microsimulation approach to the analysis of educational inequalities. The method simulates individual units (potential students) over a period of time. This chapter describes a model that utilises the BHPS dataset to build a dynamic spatial microsimulation model for the analysis of social and spatial inequalities in educational attainment. Educational attainment is particularly suitable for the development and application of a dynamic spatial microsimulation model given the influence that education has on a person’s life outcomes. The dynamic spatial microsimulation model described in this chapter has been used in a case study to analyse social and spatial inequalities in higher education entry and attainment.

Introduction: The Practice of Spatial Analysis

The chapter provides a broad-brush introduction to the subject of spatial analysis as a general backdrop to the discussion of the individual chapters of this volume. It first offers a range of definitions of spatial analysis from the human geography viewpoint mainly, which reflect its historical evolution. Then, it discusses the practice of spatial analysis in terms of broad streams of methods and techniques that have developed over time, in several of which Prof. Kanaroglou has contributed important research. Next, it presents the individual contributions and closes with a discussion of their main features, organized in terms of theory, methods/techniques, applications, and policy relevance, which point to the respective open issues that future research is called to address to enhance the role of spatial analysis in contemporary data-rich, technologically advanced, and decision-intensive contexts.

Location—Allocation Modeling for Emergency Evacuations in the Aegean Sea

Insular regions play an important role in Eastern Mediterranean, mostly attributed to their geographical, environmental, social and economic peculiarities. Greek islands in the Aegean Sea are such an example, being attractive tourism destinations with a varying permanent population both island- and season-specific. Such a seasonality of islands’ population, coupled with problems related to their geographical fragmentation, challenges local decision-making regarding, among others, health service provision. This chapter analyzes the spatial distribution of national aero-evacuation means, such as helicopters, in order to inform the debate about de-centralized services of emergency evacuations in island complexes of the Aegean Sea. After discussing potential use of Geographical Datasets for smart decision-making regarding emergency evacuation procedures, the focus of the paper is on a location-allocation model of helicopter bases in the islands of the Aegean Sea. The results of this work aim at shedding some light on the spatial optimization of the helicopter bases in the area; and discussing the trade-off conditions of emergency evacuation services in such a fragmented geographical space. Finally, after utilizing a number of large scale geographical simulations for allocating aero-evacuation bases, the usefulness of spatial analytics for taking more informed decisions is illustrated, especially in areas where dynamic seasonality of population throughout the year challenges health service provision.

Spatial Patterns of Accessibility Between Islands of the North and South Aegean Regions and Attica

Accessibility is an important determinant of socio-economic development at all spatial levels because it critically affects the operations and success of economic activities. Measures of accessibility are frequently used to support development policy-making and spatial planning. The spatial sciences provide several quantitative approaches to assess accessibility and identify over- and under-served areas. This chapter contributes to the broader issue of quantifying accessibility by analyzing the spatial patterns of accessibility in the case of a very fragmented geographical space; the islands of the North and South Aegean Sea Regions, Greece. Following a preliminary spatial analysis of: transportation route frequency, passengers/population, two graph theory metrics and mean ticket cost, clustering methods, enhanced by introducing local indices of spatial association, are employed to determine possible groupings of islands and delineate spatial clusters based on their accessibility. “Hot spots” of accessibility in the study area are identified, suggesting that accessibility is more spatially clustered than would be expected under a random model.

A Decision-Making Approach for Improving Organizations’ Cloud Forensic Readiness

Cloud forensic investigation involves a number of different people and requires a lot of effort to resolve an incident. In order for an organization to have better chances to succeed in the investigation, it needs to be well-prepared. Hence, the organization needs to develop cloud forensic readiness. This paper introduces a decision-making approach to calculate the forensic readiness and the compliance level of an organization, and in parallel to classify the unimplemented tasks in a cloud service. The specific approach is based on a decision-based algorithm, the organization’s forensic compliance and a number of decision-making criteria.

Geographical Analysis of Emergency Evacuations in the Aegean Sea: Towards the Utilization of Big Data Analytics

Island areas in the Mediterranean constitute an important cultural and natural resource as well as spatial entities upon which dynamic activities, such as tourism, take place. The annual seasonality of tourist flows and the spatial fragmentation of activities in island areas place certain burdens that call for a dynamic approach in decision-making as to the provision of various services, e.g. health services, based on relevant spatially-related data analysis. The availability of health services as well as the specialized medical personnel determines in a certain extent the quality of health provision in island areas. The National Center of Emergency Evacuations in Greece (EKAB) provides the means for emergency health evacuation from the Greek islands to specialized hospitals in the mainland whenever necessary, playing thus a crucial role for the improvement of quality of life in the Aegean archipelago. The focus of this work is on improving emergency evacuation service provision of EKAB in Greek islands by analyzing population and transportation data for providing input to more “smart” health provision decision-making processes. After examining the current and potential future demand for health services through population data, the effectiveness of Big Data (BD) analytics utilization is explored in support of optimal allocation of EKAB resources, maximization of supply and minimization of possible evacuation time. The introduction of BD analytics in regional decision-making processes may enhance potential for tailored-made planning, faster and informed decision-making as well as scenarios’ testing, service monitoring and more effective forecasting.

Spatial Micro Level Analysis of Building Structures in Samos Island

Decision-making at the regional level has become more complex over the last years, requiring advanced tools to cope with dynamic environments and processes; and a thorough analysis of spatial entities in finer scale for better understanding of the dynamics and underlying processes. The focus of this paper is on the contribution of fine scale datasets in policy making by use of Spatial Micro Level Analysis of building-structures data. This approach enables the exploration of the spatial pattern in finer scale, setting the ground for a better insight in micro level dynamics. The proposed approach was applied in an insular area—Samos, Greece—in an effort to study two defining issues of islands’ territory development in the Aegean Sea nowadays, namely informal settlements’ expansion as well as spatial distribution of fire events, which are closely linked to pressures exerted on such areas by current development patterns as well as climate change impacts. The scope of this work is to illuminate underlying mechanisms of attraction/repulsion of informal housing; and identify the relationship between points of fire ignition and populated areas. Output of such an approach can feed decision-making processes and support more “smart” policy directions for coping with challenges of both island territory development and fire-related risks.

Multivariate Variogram and Madogram: Tools for Quantifying Diversity/ Dissimilarity in Spatiotemporal Data

Global and local (site specific) multivariate variogram and madogram measures of attribute spatial (dis)similarity are linked to multivariate extensions of Geary’s and Gini’s indices of spatial association. These measures are then employed for elucidating spatiotemporal patterns in monthly sea surface temperature and chlorophyll-a concentration data over the North Aegean Sea in Greece, derived, respectively, from NOAA’s Advanced Very High Resolution Radiometer (AVHRR) sensor and NASA’s Sea-Viewing Wide Field-of-view Sensor (SeaWiFS).