Gilberto Camara - INPE  Clodoveu Davis - UFMG  Fred Fonseca - Penn State

Potential contributors are strongly encouraged to read the report of the workshop Spatial Data Infrastructures for the Sustainability of the Brazilian Amazon: Integrating People, Information, and Models.

Important Dates

•     Manuscript submission period begins March 15th and ends June 1st 2009
       Manuscripts should be submitted through the journal's website.
       When submitting choose "Brazilian Amazon Special Issue" as the manuscript type.
       Please register yourself and the and submit at
        https://www.editorialmanager.com/esin/
   Please also email fredfonseca@ist.psu.edu informing that you have submitted your    manuscript.   

Guest Editors

• Fred Fonseca – Penn State University, U.S.A.

• Clodoveu Davis – Federal University of Minas Gerais (UFMG), Brazil

• Gilberto Camara – National Institute for Space Research (INPE), Brazil

Background

One of the most important research topics today is related to Global Change: “How is the Earth’s environment changing and what are the consequences for human civilization?” The science areas necessary to address this question are so many that only a solid interdisciplinary approach can succeed. One of the attempts to understand Global Change in an interdisciplinary way is what is called today Sustainability Science. Sustainability science purports to understand, integrate, and model nature and society. Since most of the interventions on the environment are human choices, we need modeling tools that capture the representation of the world as seen and modified by human beings.

Sustainability Science is a prime example of how necessary are the tools and methods for information integration across multiple sources, considering various views of the world, and across various scales. Such level of integration has been examined, in the context of GIScience, mainly in two interconnected research topics: semantics and spatial data infrastructures (SDI). While the former deals with subjects of a more theoretical and conceptual nature, the latter seems to be particularly relevant when one considers the breadth of scope and physical size of the various sources of relevant data. In fact, a data-centric view is probably insufficient, considering the important challenges that exist in modeling and analysis. It is necessary also to envision geoprocessing services and information services based on SDIs. The availability of large amounts of spatial (and temporal) data, distributed throughout the Internet, challenges us to find more efficient ways to tap into those information resources to produce a better understanding of the complex issues related to environmental change.

When approaching the idea of a SDI for integrated scientific understanding of the Brazilian Amazon, there are two competing perspectives. One approach is to view SDI as an automated map data distribution system. In this case, SDI implementation focuses on distribution of data from existing sources on an “as-is” basis. The alternative is to view SDI as an enabler for understanding space. In this case, a SDI does not only deliver maps, but acts as an architecture for disseminating spatial information globally, with associated metadata on quality, uncertainty, lineage, and semantic descriptions, providing means for an effective understanding of the complex interactions between people and nature.

So, in order to be able to integrate knowledge on the Brazilian Amazon sustainability-related processes, do we need more information or more people? Or is it necessary to have better models and more computing power? We are interested in contributions that integrate both people and the technology aspects of information and models. Below are some potential topics for the special issue.

Topics

• Can the monitoring of the Amazon be “wikified”, i.e., can volunteers closely monitor environmental issues by working in their free time over freely-available geographic data? What kind of tools would they need? Can volunteers be able to obtain, analyze, and identify change vectors from online data sources? Can the quality of this volunteer work be assessed? How can people be motivated to contribute? Is it possible to approach real-time monitoring if there are enough volunteers?
• How can we obtain a better understanding of the environment and model the interactions between man and nature in a meaningful and useful way?
•  What are the options for modeling human activity that affect the environment? Some of the theoretical options are agent-based models, game theory, understanding human choices, complexity theory, spaces of variable geometry, scale, networks, and interactions at a distance.
• How to represent human free will in the computer, so that we are able to model the interactions between nature and society, and to measure the impact of governmental policies?
• What is the impact of human actions in different geographical scales?
• How can we build geographical visualization systems that help public policy makers and societal stakeholders? How do good GIS user interfaces help planners and decision makers?
• How can a planner build scenarios for the Amazon using spatial decision support systems, considering factors such as demand for agricultural commodities and for energy?
• How can economic factors be expressed spatially? How does the spatial expression of markets contribute to public policies that promote sustainability? What are the relations between markets and sustainability at various spatial scales?