Advancing Land Change Modeling Opportunities and Research Requirements (2014) / Chapter Skim
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A recent explosion in the number and types of new land observations and monitoring data, model approaches, and computational infrastructure has ushered in a new generation of LCMs that are capable of new applications associated with human-environment systems in increasing detail. A wide variety of modeling approaches has been developed, each with different strengths, weaknesses, and applications.
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with land change modeling to improve land-change model outputs to better fulfill scien tific and decision making requirements. a committee to describe various LCM approaches, suggest guidance for their appropriate application, and describe ways to improve the integration of observation strategies into the models (see Box S.1 for the complete committee charge)
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Sector-Based Economic approach uses partial and general equilibrium structural models to represent supply and demand for land by economic sectors within regions based on overall economic activity and trade, 4. Spatially Disaggregate Economic approach estimates structural or reduced form econometric models to identify the causal relationships influencing the spatial equilibrium in land systems, and 5.
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IMPROVING LAND CHANGE MODELS New observations, improvements in modeling capability and computer infrastructure, and advances in understanding the theoretical and social context of land change have created opportunities to improve LCMs to support research and decision making on current and future land change. Opportunities are grouped into five categories: (1)
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Improved capture and processing of remotely sensed data A variety of developments in Earth observations have the potential to spur advances in land change modeling. Data collected at finer resolutions, coupled with object-based image analysis tools, offer the opportunity to develop models
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. Creative uses of satellite measurements like the nighttime lights products to estimate human settlement densities, energy use, and economic activity provide opportunities to develop spatially, temporally, and thematically richer inputs to LCMs.
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Greater volumes of distributed data storage provide opportunities to incorporate data over larger areas and at finer resolutions into the next generation of models. Opportunities for Infrastructure to Support Land Change Modeling Progress in land-change modeling is partially impeded by the continued reinvention of modeling environments, frameworks, and platforms by various research groups.
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Some of these practices are established but not always followed, while others require more research to test and establish. Sensitivity analysis is an established procedure whereby the investigator examines the variation in model output due to specific amounts of variation in model input, parameter values, or structure.
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Taking advantage of a wider range of Earth observation data types to enhance their spatial and temporal detail and the categories of information they represent, future LCMs can integrate these with data on the human attitudes, preferences, and behaviors related to land change, both from traditional and a growing number of novel sources for social data. Highly interconnected data systems, well-documented model and software code, and a well functioning community of land-change modelers can support the scientific enterprise to advance these goals.
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