LSP (Logic Score Preference) Method For Ready-To-Build Areas and Ready-To-Build Environments as an Early Warning and Disaster Mitigation System

In recent decades, large urban areas worldwide have faced the challenge of balancing urban growth with environmental preservation. Population growth and economic development significantly impact urban conditions, environmental quality, social equity, and national welfare. Large-scale housing development ideally aims to create a harmonious and optimal environment. Consequently, optimizing land use at the city level must consider the efficiency and effectiveness of building new residential areas. This study utilizes a Geographic Information System (GIS) to analyze optimization and limiting functions based on optimization principles to derive a typical model for various urban areas. The research aims to integrate the Logical Score Preference (LSP) method for evaluating land suitability for Ready-to-Build Areas (KASIBA) and Ready-to-Build Environments (LISIBA) with the City Spatial Plan (RTRK). This integration is crucial for controlling environmental degradation in accordance with environmental carrying capacity, thereby contributing to GIS-based Sustainable Development Goals. The research methodology employs a survey with an EAC approach for formal thematic and correlative information. The results demonstrate the development of a suitability evaluation class map model for KASIBA and LISIBA that aligns with environmental carrying capacity. Rules and regulations are analyzed using the LSP method. The integration of land evaluation and GIS provides a robust foundation for addressing land spatial suitability. The analytical process, functioning as a multi-criteria decision-making approach, establishes a preference scale among a set of alternatives. The application of existing GIS-based Multi-Criteria Evaluation (MCE) methods in agricultural land suitability assessment often struggles to incorporate a large number of diverse criteria (more than 10 criteria) and to address the broader logic of human decision-making.