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We will develop SMART-SLEUTH, an advanced spatially explicit modeling framework designed to augment the current SLEUTH model with sophisticated smart-growth capabilities. Based on the latest version of SLEUTH, we will create an open-source GIS-enabled software package that will implement SMART-SLEUTH with advanced modules and tools for evaluating, predicting, and visualizing smart growth scenarios and outcomes. In this software package, a more user friendly Graphic User Interface (GUI), a multi-level automatic calibration approach built on machine learning algorithms, and new spatial landscape metrics for quantifying land change patterns will provide enhanced support for complex model configuration, calibration,...
Categories: Data,
Project;
Tags: 2013,
2014,
2015,
ANTHROPOGENIC/HUMAN INFLUENCED ECOSYSTEMS,
Academics & scientific researchers, All tags...
Applications and Tools,
Conservation NGOs,
Conservation Planning,
Data Acquisition and Development,
Datasets/Database,
Federal resource managers,
LCC,
LCC Network Science Catalog,
MODELS,
Methodology/Protocol,
Project,
Regional & county planners,
Report,
South Atlantic Landscape Conservation Cooperative,
State agencies,
TERRESTRIAL ECOSYSTEMS,
completed,
structure,
structure,
transportation,
transportation, Fewer tags
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Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3.0) that can probabilistically predict urban growth while simulating human migration and other responses to flooding, essentially depicting the geography of impact and response. Accounting for human migration reduced total amounts of projected developed land exposed to flooding by 2050 by 5%–24%, depending on flood hazard zone (50%–0.2% annual probability). We simulated various “what-if” scenarios and found managed retreat...
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