基于GF-2影像的三种旅游景区资源识别方法比较研究——以野三坡国家公园为例

CONVERTER Pub Date : 2021-07-10 DOI:10.17762/converter.190
Zhe Jia, Anchen Qin
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引用次数: 1

摘要

在对景区资源进行科学鉴定和评价的基础上,制定规划管理对国家公园旅游业的可持续发展具有重要意义。本文以GF-2高分辨率遥感影像为数据源,以野三坡国家公园为研究区域。采用基于像素的MLC、NN、SVM三种分类方法对景区资源进行识别,采用系统抽样法评价3种方法对景区资源分类精度进行识别,有效提高了分类精度评价的客观性和准确性。结果表明,GF-2图像中采用的三种分类方法均满足景区资源识别的精度要求,是一种有效的景区资源识别方法。由于地貌特征不同,侵蚀张谷地貌-百里峡景区采用MLC分类,花岗岩断裂构造峡谷地貌-龙门观景区采用NN分类,溶洞泉地貌-玉谷洞景区采用SVM分类,综合精度最高。结果表明,该方法可应用于大尺度、高分辨率的景区资源识别,为景区资源分析和当地旅游业可持续发展提供更精细的数据支持。
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A Comparative Research on Three Identification Methods of Scenic Resources of Tourism Based on GF-2 Image: A Case Study of Yesanpo National Park
Based on the scientific identification and evaluation of scenic resources, the formulation of planning and management is of great significance to the sustainable development of tourism in national parks. This paper uses GF-2 high-resolution remote sensing images as the data source, and the Yesanpo National Park as the research area. It uses pixel-based MLC, NN, and SVM three classification methods to identify scenic resources, and adopts the system sampling method evaluation 3 methods to identify the classification accuracy of scenic resources, effectively improving the objectivity and accuracy of classification accuracy evaluation. The results show that the three classification methods used in GF-2 images meet the accuracy requirements of scenic resource identification, which is an effective method to identify scenic resources. Due to different geomorphic features, the erosion Zhanggu landform-Baili Xia scenic areas uses MLC classification, and granite fracture structure The canyon landform-LongmenTianguan scenic areas uses NN classification, and the karst cave spring landform-Yugu Dong scenic areas uses SVM classification with the highest overall accuracy. The results show that the proposed method can be applied to the identification of large-scale, high-resolution scenic resources, and provide more refined data support for scenic resource analysis and sustainable development of local tourism.
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