With the development of society and the improvement of people's living standards, ecotourism based on forest ecological environment has become an urgent need of urban and rural people. Forest leisure tourism is different from traditional sightseeing tourism. The differences between them are not only reflected in consumption purpose, consumption behavior, consumption grade and consumption form, but also reflected in the differences between tourism products, service system and service quality demand. Therefore, in order to develop forest leisure tourism, we must first fully understand the objective status quo of the leisure tourism market and the real needs of the market, and correctly judge the basic characteristics of the current forest leisure tourism market. At present, the competition of tourism market is upgraded from the competition of tourism price and tourism product to the competition of tourism brand. However, the resource utilization efficiency of forest park tourism is insufficient, and the internal management and external marketing are difficult to adapt to the changes of the market, thus the image and attraction of forest park tourism need to be improved urgently. Therefore, based on remote sensing image analysis and neural computing model, this paper constructs a forest ecotourism evaluation scheme. We designed the novel cloud-based mobile edge computing model to construct the efficient scenario for the prediction. The experimental results show that the model proposed in this paper can effectively evaluate the development plan of forest eco-tourism.

随着社会的发展和人民生活水平的提高，以森林生态环境为基础的生态旅游已成为城乡人民的迫切需求。森林休闲旅游不同于传统的观光旅游。它们之间的差异不仅体现在消费目的、消费行为、消费档次和消费形式上，还体现在旅游产品、服务体系和服务质量需求上的差异。因此，发展森林休闲旅游，首先要充分认识休闲旅游市场的客观现状和市场的真实需求，正确判断当前森林休闲旅游市场的基本特征。目前，旅游市场的竞争由旅游价格和旅游产品的竞争升级为旅游品牌的竞争。但森林公园旅游资源利用效率不足，内部管理和外部营销难以适应市场变化，森林公园旅游形象和吸引力亟待提升。因此，本文基于遥感图像分析和神经计算模型，构建了森林生态旅游评价方案。我们设计了新颖的基于云的移动边缘计算模型来构建有效的预测场景。实验结果表明，本文提出的模型能够有效地评价森林生态旅游的发展规划。