Land Change Science is an emerging field of study, aimed at understanding interactions among human systems and the terrestrial biosphere, atmosphere and other Earth systems as mediated through human use of land. Advances in LCS are needed to better quantify, predict, mediate, and adapt to global climate change, biodiversity loss, and other consequences of land use and land cover change.

Despite vigorous efforts by a broad array of social and natural scientists, the cross-scale synthesis of multidisciplinary observations, models and theories on coupled human and natural systems (CHANS) that are required to advance LCS has yet to emerge. A major obstacle is the tremendous challenge in global integration and synthesis of local and regional CHANS case studies. This project will accelerate the emergence of new global workflows in land change science through GLOBE: an online collaboration environment combining quantitative real-time global relevance assessment, geovisualization, social-computational structures and machine learning algorithms. This will be accomplished in collaboration with international LCS institutions and experts, enabling researchers and institutions to rapidly share, compare, and synthesize local and regional studies by combining these with global datasets for human and environmental variables using a combination of machine learning, advanced visualization, semantic analysis and social networking.

The project has four core objectives that will be achieved through three integrated activities, as follows:

Objective 1: Create an online collaboration environment leveraging real-time global relevance analysis, geovisualization and social-computational knowledge generation towards the generation and sharing of new global workflows for land change science. Objective 2: Understand how to build effective social media tools organized around structured and informal scientific workflows. Objective 3: Develop evaluation methods and metrics and use them to demonstrate the utility of workflow-based social media tools in the context of scientists testing LCS hypotheses. Objective 4: Leverage GLOBE to characterize and optimize global knowledge generation in LCS.

To achieve these goals, this team will engage in the following activities:

Activity 1: Develop the social-computational infrastructure for GLOBE. Activity 2: Establish GLOBE as a means for social-computational knowledge generation. Characterize, share and optimize knowledge generation workflows for global synthesis and collaboration across CHANS studies and data collections. Activity 3: Test hypotheses and identify new research opportunities.

To understand anthropogenic global changes in the Earth system, scientists must generalize globally from observations made locally and regionally. This project will make fundamental hypotheses on the nature of human interactions with earth systems more readily testable by scientific methods, enabling major advances in land-change science and theory. Moreover, this project will engage the computing and social sciences in developing interactive online tools for scientific collaboration and data synthesis that will help identify knowledge gaps in LCS science. The tools will result in new ways of visualizing, communicating, connecting, comparing and synthesizing observations and models of land change processes at global, regional and local scales. Empirical investigation of GLOBE in use will advance our understanding of scientific collaboration more generally.

Broader impacts This project will develop, enhance and support long-term research collaborations across a broad set of scientific disciplines. It will support education and skill building for interdisciplinary collaboration by seasoned faculty, postdoctoral researchers, graduate students and undergraduate students. The project will design, host and disseminate advanced tools for cross-scale data and knowledge sharing, synthesis, and design of globally representative observing systems. By creating a new environment for sharing and integrating local knowledge, data and ideas across the social, biological and geophysical sciences, land change science will have greater potential to inform the sustainable stewardship of earth systems.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
1125210
Program Officer
Anita J. LaSalle
Project Start
Project End
Budget Start
2011-09-15
Budget End
2015-08-31
Support Year
Fiscal Year
2011
Total Cost
$1,852,988
Indirect Cost
Name
University of Maryland Baltimore County
Department
Type
DUNS #
City
Baltimore
State
MD
Country
United States
Zip Code
21250