An economic analysis of woodfuel management in the Sahel : the case of Chad

The woodlands in some parts of the Sahel are effectively an open-access resource. Under open access, fuelwood cutters have no incentive to allow for benefits that might accrue if the wooded area were managed rather than mined. Those benefits include sustainable streams of fuelwood, fruits, and other tree products, browse for cattle, and ecological services such as nitrogen fixation and erosion prevention. To remedy this problem, some Sahelian areas have moved to give communities effective control of local woodland resources. To make it easier to analyze the economic cost of such supply-side interventions, the authors present an economic framework and computational method for assessing policy impacts on the cost of woodfuel supplies, and the spatial distribution of biomass, in a particular Sahelian woodland setting. They use spatial data on standing stock and on the costs of transport to market to model a supply curve of fuel to a fuel-consuming location. given an exogenously specified demand, the model simulates, period by period, the extraction, regeneration, and transport of wood fuels. It also permits easy calculation of the dynamic cost of woodfuel depletion. They apply the model to evaluate the benefits and ecological impacts of various scenarios for woodland management around the city of N'Djamena in Chad.Markets and Market Access,Economic Theory&Research,Environmental Economics&Policies,Labor Policies,Agricultural Knowledge&Information Systems,Economic Theory&Research,Environmental Economics&Policies,Access to Markets,Markets and Market Access,Geographical Information Systems

Access control systems for geo-spatial data and applications

Data security is today an important requirement in various applications because of the stringent need to ensure confidentiality, integrity, and availability of information. Comprehensive solutions to data security are quite complicated and require the integration of different tools and techniques as well as specific organizational processes. In such a context, a fundamental role is played by the access control system (ACS) that establishes which subjects are authorized to perform which operations on which objects. Subjects are individuals or programs or other entities requiring access to the protected resources. When dealing with protection of information, the resources of interest are typically objects that record information, such as files in an operating system, tuples in a relational database, or a complex object in an object database. Because of its relevance in the context of solutions for information security, access control has been extensively investigated for database management systems (DBMSs) [6], digital libraries [3, 14], and multimedia applications [24]. Yet, the importance of the spatial dimension in access control has been highlighted only recently. We say that access control has a spatial dimension when the authorization to access a resource depends on position information.We broadly categorize spatially aware access control as object-driven, subject-driven, and hybrid based on whether the position information concerns objects, subjects, or both, respectively. In the former case, the spatial dimension is introduced because of the spatial nature of resources. For example, if the resources are georeferenced Earth images, then we can envisage an individual be allowed to only display images covering a certain region. The spatial dimension may also be required because of the spatial nature of subjects. This is the case of mobile individuals allowed to access a resource when located in a given area. For example, an individual may be authorized to view secret information only within a military base. Finally, position information may concern both objects and subjects like in the case of an individual authorized to display images of a region only within a military office. There is a wide range of applications which motivate spatially aware access control. The two challenging and contrasting applications we propose as examples 190 Maria Luisa Damiani and Elisa Bertino are the spatial data infrastructures (SDI) and location-based services (LBS). An SDI consists of the technological and organizational infrastructure which enables the sharing and coordinated maintenance of spatial data among multiple heterogeneous organizations, primarily public administrations, and government agencies. On the other side, LBS enable mobile users equipped with location-aware terminals to access information based on the position of terminals. These applications have different requirements on access control. In an SDI, typically, there is the need to account for various complex structured spatial data that may have multiple representations across different organizations. In an SDI, the access control is thus object-driven. Conversely, in LBS, there is the need to account for a dynamic and mobile user population which may request diversified services based on position. Access control is thus subject-driven or hybrid. However, despite the variety of requirements and the importance of spatial data protection in these and other applications, very few efforts have been devoted to the investigation of spatially aware access control models and systems. In this chapter, we pursue two main goals: the first is to present an overview of this emerging research area and in particular of requirements and research directions; the second is to analyze in more detail some research issues, focusing in particular on access control in LBS. We can expect LBS to be widely deployed in the near future when advanced wireless networks, such as mobile geosensor networks, and new positioning technologies, such as the Galileo satellite system will come into operation. In this perspective, access control will become increasingly important, especially for enabling selective access to services such as Enterprise LBS, which provide information services to mobile organizations, such as health care and fleet management enterprises. An access control model targeting mobile organizations is GEO-RBAC [4]. Such a model is based on the RBAC (role-based access control) standard and is compliant with Open Geospatial Consortium (OGC) standards with respect to the representation of the spatial dimension of the model. The main contributions of the chapter can be summarized as follows: \u2022 We provide an overview of the ongoing research in the field of spatially aware access control. \u2022 We show how the spatial dimension is interconnected with the security aspects in a specific access control model, that is, GEO-RBAC. \u2022 We outline relevant architectural issues related to the implementation of an ACS based on the GEO-RBAC model. In particular, we present possible strategies for security enforcement and the architecture of a decentralized ACS for large-scale LBS applications. The chapter is organized as follows. The next section provides some background knowledge on data security and in particular access control models. The subsequent section presents requirements for geospatial data security and then the state of the art. Afterward the GEO-RBAC model is introduced. In particular, we present the main concepts of the model defined in the basic layer of the model, the Core GEO-RBAC. Hence, architectural approaches supporting GEO-RBAC are presented. Open issues are finally reported in the concluding section along with directions for future work

Evaluating Coastal Landscape Response to Sea-Level Rise in the Northeastern United States - Approach and Methods

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online

Dynamic Geospatial Spectrum Modelling: Taxonomy, Options and Consequences

Much of the research in Dynamic Spectrum Access (DSA) has focused on opportunistic access in the temporal domain. While this has been quite useful in establishing the technical feasibility of DSA systems, it has missed large sections of the overall DSA problem space. In this paper, we argue that the spatio-temporal operating context of specific environments matters to the selection of the appropriate technology for learning context information. We identify twelve potential operating environments and compare four context awareness approaches (on-board sensing, databases, sensor networks, and cooperative sharing) for these environments. Since our point of view is overall system cost and efficiency, this analysis has utility for those regulators whose objectives are reducing system costs and enhancing system efficiency. We conclude that regulators should pay attention to the operating environment of DSA systems when determining which approaches to context learning to encourage

On the inability of existing security models to cope with data mobility in dynamic organizations

Modeling tools play an important role in identifying threats in traditional\ud IT systems, where the physical infrastructure and roles are assumed\ud to be static. In dynamic organizations, the mobility of data outside the\ud organizational perimeter causes an increased level of threats such as the\ud loss of confidential data and the loss of reputation. We show that current\ud modeling tools are not powerful enough to help the designer identify the\ud emerging threats due to mobility of data and change of roles, because they\ud do not include the mobility of IT systems nor the organizational dynamics\ud in the security model. Researchers have proposed security models that\ud particularly focus on data mobility and the dynamics of modern organizations,\ud such as frequent role changes of a person. We show that none\ud of the current security models simultaneously considers the data mobility\ud and organizational dynamics to a satisfactory extent. As a result, none\ud of the current security models effectively identifies the potential security\ud threats caused by data mobility in a dynamic organization

Modeling emergency management data by UML as an extension of geographic data sharing model: AST approach

Applying GIS functionality provides a powerful decision support in various application areas and the basis to integrate policies directed to citizens, business, and governments. The focus is changing toward integrating these functions to find optimal solutions to complex problems. As an integral part of this approach, geographic data sharing model for Turkey were developed as a new approach that enables using the data corporately and effectively. General features of this model are object-oriented model, based on ISO/TC211 standards and INSPIRE Data Specifications, describing nationwide unique object identifiers, and defining a mechanism to manage object changes through time. The model is fully described with Unified Modeling Language (UML) class diagram. This can be a starting point for geographic data providers in Turkey to create sector models like Emergency Management that has importance because of the increasing number of natural and man-made disasters. In emergency management, this sector model can provide the most appropriate data to many "Actors" that behave as emergency response organizations such as fire and medical departments. Actors work in "Sectors" such as fire department and urban security. Each sector is responsible for "Activities" such as traffic control, fighting dire, emission, and so on. "Tasks" such as registering incident, fire response, and evacuating area are performed by actors and part of activity. These tasks produce information for emergency response and require information based on the base data model. By this way, geographic data models of emergency response are designed and discussed with "Actor-Sector-Activity-Task" classes as an extension of the base model with some cases from Turkey