Geospatial relation captioning for high-spatial-resolution images by using an attention-based neural network. Issue 16 (18th August 2019)

• Record Type: Journal Article
• Authors: Chen, Jie; Han, Yarong; Wan, Li; Zhou, Xing; Deng, Min
• Is Part Of: International journal of remote sensing. Volume 40:Issue 16(2019)
• Page Start: 6482
• Page End: 6498
• Publication Date: 2019-08-18
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2019.1594439
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: High-spatial-resolution (HSR) remote sensing images serve as carriers of geographic information. Exploring geo-objects and their geospatial relations is fundamental in understanding HSR remote sensing images. To this end, this study proposes an intelligent semantic understanding method for HSR remote sensing images via geospatial relation captions. Firstly, we propose a method of geospatial relation expression to convey the topological, directional and distance relations of geo-objects in HSR images. Secondly, on the basis of images and their geospatial relation captions, an image dataset is constructed for model training. Finally, geospatial relation captioning is implemented for HSR images by using an attention-based deep neural network model. Experimental results demonstrate that the proposed captioning method can effectively provide geospatial semantics for HSR image understanding.