高分辨率影像解译理论与应用方法中的一些研究问题

Interpretation Theory and Application Method Development for Information Extraction from High Resolution Remotely Sensed Data

近年来,不断发展的遥感技术使遥感数据呈现出高空间分辨率、高光谱分辨率和高时间采集频率的特点。卫星图像空间分辨率已经提高到0.6m级,而航空遥感数字影像分辨率高达0.1m以上。光谱分辨率高达3—4nm。不断发展的高分辨率遥感数据能够提高信息提取和监测精度,并拓展遥感数据的应用范围。目前,国外已经加快对高分辨率图像,特别是高空间分辨率影像,在城市环境、精准农业、交通及道路设施、林业测量、军事目标识别和灾害评估中的应用。但是总的情况是自动化程度不高。介绍高空间分辨率影像信息提取、高光谱和偏振影像信息提取、影像数据融合和高分辨率遥感变化探测等方面迫切需要研究的一些科学问题及其意义。建议建立图像知识库,改善数据共享环境,为有志于从事这方面研究的学者提供参考。

Under the constant advancement of remote sensing technology, more and more high spatial and spectral resolution and high time frequency data are becoming available. The spatial resolution of satellite data is approaching 0.6m while for aerial imagery it is better than 0. 1m. The spectral resolution of data can be as high as 3-4nm. These developments not only greatly increased our capability and accuracy in information extraction and monitoring but also opened new application opportunities. Existing research activities have focused on how to increase the utilization efficiency of high resolution data, particularly for high spatial resolution data in a wide range of applications such as urban environment, precision agriculture, transportation and road infrastructure, forest inventory, artificial targets recognition and disaster risk assessment. However, the overall level of automation is still low. In this paper, we introduce some of the bottleneck problems and research questions related to information extraction from high spatial resolution imagery, and high spectral resolution and polar imagery, data fusion, and high spatial resolution image change detection. We suggest that an image base and a corresponding relevant knowledge base be built to improve data sharing and to facilitate investigations in this field.