ABSTRACT With the rapid development of the tourism industry, monitoring and protecting the environment of tourist destinations are facing increasingly severe challenges. Traditional environmental monitoring methods often rely on ground surveys, which suffer from problems such as incomplete data acquisition, slow response speed, and insufficient analytical capabilities, making it difficult to respond to complex ecological environment changes effectively. This article combined Support Vector Machine (SVM) and computer image processing technology to improve the efficiency and accuracy of environmental monitoring in tourist destinations. The image data collected in this article came from multiple areas within City A and was obtained between 2020 and 2022. The data type was remote sensing images. Vector machines were used to classify and analyse extracted data, achieving real-time monitoring and evaluation of environmental changes. The research results showed that this method performed well in identifying vegetation cover changes and monitoring water quality, significantly improving the timeliness of ecological data. The response speed increased from 403.5mbps to 582.1mbps. At the same time, the vegetation coverage rate in Area B of City A increased from 40%-70% to over 80%. This study provides a new technological path for environmental monitoring and protection in tourist destinations, which improves the comprehensive efficiency of monitoring and provides scientific data support for managers, thereby promoting the sustainable development of tourist destinations.
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