数智时代地理数据科学课程“轻量级模拟实验”设计与实践

Design and Practice of “Lightweight Simulation Experiments” for Geography Data Analysis Courses in the Digital and Intelligent Era

  • 摘要: 数智时代下,对地观测技术快速发展,地理时空大数据持续增长,推动地理学理论革新与产业升级。地理数据科学课程是培育地理专业人才计算思维与实践能力的核心课程。随着大数据与人工智能技术深度融合,传统实验教学弊端愈发突出,呈现数据维度单一、技能训练体系不完整、跨学科结合薄弱等困境。为此,该文构建基于物联网传感矩阵的轻量级模拟实验模式,搭建光照、温度、湿度、风速多要素地理环境实时采集系统,依托 Arduino 开发平台,完成传感采集、云端存储、算法分析全流程实践教学训练。该实验模式可为地理数据科学课程实践教学提供可行方案,夯实地理学数字化教学技术基础,为高校地理类课程教学改革优化提供参考,提升复合型创新地理人才培养质量。

     

    Abstract: In the intelligent digital era, the rapid development of earth observation technology and the continuous growth of geospatial big data have promoted theoretical innovation and industrial upgrading in geography. As a core course, Geospatial Data Science cultivates computational thinking and practical abilities of geography majors.With the deep integration of big data and artificial intelligence, traditional experiments suffer from single data dimension, incomplete skill training system and weak cross-disciplinary combination. Accordingly, this paper proposes a lightweight simulation experiment mode based on Internet of Things sensor matrix. A real-time multi-element geographic environment collection system covering light, temperature, humidity and wind is constructed, and the whole-process training from sensor terminal, cloud terminal to algorithm terminal is realized via the Arduino framework. This mode provides feasible schemes for practical teaching, supports digital transformation of geography education, and offers references for curriculum reform, so as to improve the cultivation quality of interdisciplinary innovative geography talents.

     

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