Chances and Challenges for Development of Surveying and Remote Sensing in the Age of Artificial Intelligence
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摘要: 人工智能技术迅猛发展将对各行各业造成巨大影响。测绘遥感是一个与人工智能密切相关的领域，在人工智能领域迅速发展的大环境下，测绘遥感学科既有很好的发展机遇，也面临很大的学科危机。首先介绍了人工智能的范畴和与测绘遥感相关的领域，然后介绍了人工智能两大热门领域——机器视觉和机器学习在摄影测量与遥感领域的应用进展，最后介绍了基于时空大数据的认知与推理研究进展，展示了测绘遥感的时空大数据在自然和社会感知、认知与推理的应用前景，希望测绘遥感学科在人工智能时代获得大发展。Abstract: Artificial intelligence(AI) will affect various fields and professions. Geoinformatics and remote sensing are closed the field of artificial intelligence. Our discipline will have a good development chance, also face a big challenge. This paper firstly introduces the domain of AI and the fields related geoinformatics and remote sensing, then presents the progresses of photogrammetry and remote sen-sing applications based on computing vision and machine learning. Finally, some research progresses involved perceive and reasoning based on space-time big data have revealed the application prospect in sensing, perceive and reasoning for the nature and society based on space-time data from geoinforma-tics and remote sensing. A desire is to push the quick development of geoinformatics and remote sen-sing in AI era.
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图 1 采用区域网平差方法为火星机器人导航定位
Figure 1. Using Block Adjustment to Navigate and Locate the Mars Robot
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图 2 武汉大学研制的无人驾驶汽车与室内智能机器人
Figure 2. The Automated Vehicle and the Indoors Intelligent Robot Designed by Wuhan University
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图 3 深度学习方法应用于点云数据滤波，自动提取数字高程模型
Figure 3. Deep Learning Applied in Point Cloud Data Filtering and Auto Extraction of DEM
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图 4 物理世界、人类社会和信息空间的关系
Figure 4. Relationship of Physical World, Human Society and Information Space
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图 5 长江流域天空地对地观测传感网示意图
Figure 5. Diagram of the Airborne and Spaceborne Earth Observation Sensor Web in Changjiang Region
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图 6 根据移动手机的位置信息揭示深圳市民主要活动区域、中心和社区边界
Figure 6. A Revealing Shenzhen Citizens' Main Live Region of Mobile Phones and the Border of Community According to the Location Information
表 1 使用深度学习的影像内容检索方法与传统方法的精度比较
Table 1 Accuracy Comparison Between the Way Using Deep Learning of Image Content Retrieval and the Traditional Ways
类别 DCNN LBP-HF EFT-HOG 查全率 精度 查全率 精度 查全率 精度 油罐 0.947 2 0.987 6 0.717 9 0.605 4 0.827 6 0.808 2 飞机 0.946 7 0.988 3 0.725 8 0.611 1 0.832 1 0.804 7 立交桥 0.947 2 0.930 1 0.664 6 0.584 9 0.786 2 0.761 5 田径场 0.954 4 0.922 0 0.666 7 0.571 6 0.775 7 0.741 9 
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