A Review of Land Cover Change Modeling for Precision Conservation and Green Infrastructure Planning
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Abstract
As global urbanization and climate change intensify, the need for targeted, data-driven spatial planning has become paramount. This paper reviews the evolution of Land Use and Land Cover Change (LUCC) modeling and its pivotal role in advancing Precision Conservation and Green Infrastructure (GI) planning. We trace the methodological trajectory from traditional statistical models to modern hybrid frameworks and machine learning approaches, illustrating how these tools enable a shift from reactive to proactive environmental management. By integrating LUCC simulations with connectivity theories and ecosystem service assessments, planners can identify critical habitats and optimize the placement of GI to maximize ecological resilience. However, challenges such as data granularity, model interpretability ("black box" issues), and the gap between raster outputs and parcel-based policy persist. We conclude that the future of resilient landscapes depends on transdisciplinary collaboration and the development of "Digital Twins" to provide real-time decision support for sustainable urban and rural development.
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