面向新工科的人工智能与测绘课程融合教改思考与实践

Thinking and Practice of Integrated Teaching Reform of Artificial Intelligence and Surveying and Mapping Courses for the New Engineering

人工智能技术的迅速发展,推动了其他领域的技术变革,测绘作为与人工智能密切相关的学科也开启了技术交叉。在遥感与测绘大数据时代,转型赋能的知识储备与技术在学术与产业界中交替升级,将人工智能新技术融入测绘课程教学可加快测绘行业的发展进程。以遥感科学与技术专业的《计算机视觉与模式识别》课程为例,通过实践项目将计算机视觉、信号处理和传统测绘理论与方法高度融合,在新工科与新基建背景下,将人工智能技术与测绘行业需求相结合,探索学科交叉的教学模式。理论与实践教学案例和经验表明,交叉学科的创新和跨学科思维的建立对于培养解决实际问题的多元化人才至关重要。

The rapid development of artificial intelligence technology has driven technological transformations in various fields.As a discipline closely related to artificial intelligence,surveying and mapping has also embarked on cross-technological integration.In the era of remote sensing and surveying big data,the knowledge reserves and technologies empowered by transformation are being alternately upgraded in academia and industry.Integrating new artificial intelligence technologies into surveying and mapping curriculum can accelerate the development of surveying and mapping industry.Taking the Computer Vision and Pattern Recognition course in the field of remote sensing science and technology as an example,we combined computer vision,signal processing and traditional surveying and mapping theories and methods through practical projects.In the context of new engineering and new infrastructure,we integrated artificial intelligence technology with the demands of surveying and mapping industry,and explored teaching models that involve interdisciplinary approaches.Theoretical and practical teaching cases and experiences demonstrate the significance of interdisciplinary innovation and the establishment of interdisciplinary thinking in cultivating diversified talents capable of solving practical problems.