刍议服务于深度学习研究的林业遥感数据集建设

Construction of Forestry Remote Sensing Dataset for Deep Learning

林业遥感数据集是林草行业开展深度学习研究的重要基础,更是林草资源实现自动化、智能化和动态化精准监测的重要保障。文中分析了自然图像和遥感图像数据集建设现状与方法,通过对深度学习算法在林业专题信息识别和分类中最新研究成果的阐述,表明建立林业遥感专用数据集的必要性和紧迫性;基于人工智能在图像处理领域的发展经验,提出林草业遥感影像数据集的建设思路和原则。

Forestry remote sensing dataset is the important basis for the forestry and grassland sector to carry out deep learning, and also the vital guarantee for the automatic, intelligent and dynamic monitoring of grassland and forest resources. This paper analyzes the status and methods of the natural images and remote sensing image dataset construction, and then expounds the necessity and urgency of building special forestry remote sensing dataset by introducing the latest research achievements in using the deep learning algorithms for special forestry information recognition and classification. At the end, the paper proposes the ideas and principles to construct the forestry and grassland remote sensing image dataset based on the development of artificial intelligence in image processing field.