Tourism Ecological Security of Cultural Landscape Heritage: Dynamic Assessment and Prediction Using an Improved DPSIR-TOPSIS-RBF Framework

Against the backdrop of global sustainable development and ecological civilization construction, tourism ecological security at cultural landscape heritage sites faces both opportunities and challenges. This study constructs a cultural landscape heritage tourism ecological security (CLHTES) evaluation system based on the Driver–Pressure–State–Impact–Response (DPSIR) framework. It dynamically assesses CLHTES in the Yangtze River Delta Integrated Demonstration Zone (YRDIDZ) from 2014 to 2023 using the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and linear stretching transformation, identifies obstacle factors with the obstacle degree model, and predicts CLHTES trends for 2024–2030 using a radial basis function (RBF) neural network. Results show that: (1) The CLHTES index in the YRDIDZ presented a three-stage fluctuating upward trend during 2014–2023, with medium-clustered security levels and divergent evolution across the DPSIR criteria layers; (2) CLHTES obstacles feature a multi-level differentiated structure, with rising barriers in D and P layers, the R layer as the future core obstacle, and high-frequency barriers concentrated in cultural and social indicators; (3) Under the assumption of structural continuity in current trajectories, the conditional trend projection suggests that the CLHTES index of the YRDIDZ may sustain a general upward tendency during 2024–2030, with a possibility of approaching Level Ⅶ after 2028; however, these projections should be interpreted as exploratory and scenario-like rather than as robust forecasts, given the short annual series and the absence of exogenous disturbance variables. This study explores tourism-ecology interactions from a social-ecological complex system perspective, supporting synergistic tourism development and ecological protection of cultural landscape heritage.