The Dynamic Monitoring of Tourism Environment of Emeishan Mountain Based on High Score Remote Sensing Iimage and Image Fusion
Yongxing SuniD, Jianing GaoiD, Jiarong LiiD, Yanqiong CheniD
Abstract
Sustainable tourism is widely advocated as a low-impact development strategy that promotes economic growth while preserving ecological integrity. However, empirical evidence increasingly reveals complex environmental trade-offs associated with tourism expansion, particularly in ecologically sensitive heritage sites. Mount Emeishan, a UNESCO World Cultural and Natural Heritage Site in China, exemplifies a destination where tourism has driven regional socio-economic development through culturally meaningful product innovation. Yet, this growth has also imposed significant ecological pressures, particularly in waste management, where hazardous waste accumulation correlates strongly with increasing visitor numbers--posing a growing threat to local ecosystem stability. To address these challenges, this study proposes a dynamic environmental monitoring framework integrating high-resolution remote sensing imagery (HR-RSI) and advanced image fusion techniques (IFT). The primary objective is to develop a systematic, data-driven methodology for assessing and mitigating tourism-induced environmental degradation, thereby supporting sustainable management of the Emeishan National Park. Empirical evaluation of the framework demonstrated a system stability rate of 88%, representing a 12.7% statistically significant improvement (p<0.05) over traditional monitoring systems under a sample size of 100 test cases. Through the synthesis of multi-source remote sensing data, the study quantitatively assessed the impacts of tourism activities on key environmental indicators, including vegetation cover, land use dynamics, and water quality. Results revealed a noticeable decline in vegetation coverage and significant land use transitions, particularly in high-traffic zones. Furthermore, elevated water pollution risks were observed during peak tourist seasons, underscoring the seasonal nature of tourism-related environmental stressors. These findings provide robust scientific support for policy-makers and tourism authorities in formulating evidence-based environmental protection strategies and adaptive resource management policies. The integration of HR-RSI and IFT offers a scalable and replicable approach for monitoring environmental impacts in heritage-rich, tourism-intensive regions, contributing to the global discourse on sustainable tourism and ecological resilience.
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