Geographical Education
FU Yingchun, DENG Haoran, ZHUO Penghui, JIA Mingjing, DING Hu, BAI Nana, ZENG Lingwen, XUE Yufei, SUN Jia, CI Ren
This paper presents the design and development of a virtual simulation experiment system tailored to the educational needs concerning the formation and vegetation management of wind-sand landforms in the Yarlung Tsangpo River (referred to as Yar River) valley. The system adheres to the principles of comprehensiveness and inquiry-based learning in geography, as well as the interactivity and enjoyment of experiments, aiming to enhance students' theoretical knowledge, field practice skills, innovative thinking, and environmental awareness. By employing virtual simulation technology to create an immersive learning environment, students can safely and controllably simulate wind-sand landform surveys and unmanned aerial vehicle (UAV) remote sensing data collection. They can also integrate surface albedo, soil moisture, and vegetation indices to construct remote sensing inversion models and estimate surface sandification levels. Building on this, the system introduces the simulation of wind-sand landform management strategies through vegetation spatial configuration. The curriculum design integrates multidisciplinary knowledge from geography, ecology, and remote sensing technology, which is conducive to fostering the cultivation of students' comprehensive thinking abilities. This experiment constructs a teaching model that combines field data-driven and immersive virtual simulation technology for the sandification and management issues of plateau river valleys, providing rich learning resources and an autonomous learning evaluation system. It encourages students' independent inquiry and innovative attempts. With technological advancements, the virtual simulation experiment system is expected to promote the development of geography teaching towards a more efficient and open direction and contribute to the construction of online and offline integrated geography internship course application models.