气候变化领域集成服务门户(CCPortal): Virtual image pair-based spatio-temporal fusion

CCPortal

DOI	10.1016/j.rse.2020.112009
	Virtual image pair-based spatio-temporal fusion
	Wang Q.; Tang Y.; Tong X.; Atkinson P.M.
发表日期	2020
ISSN	00344257
卷号	249
英文摘要	Spatio-temporal fusion is a technique used to produce images with both fine spatial and temporal resolution. Generally, the principle of existing spatio-temporal fusion methods can be characterized by a unified framework of prediction based on two parts: (i) the known fine spatial resolution images (e.g., Landsat images), and (ii) the fine spatial resolution increment predicted from the available coarse spatial resolution increment (i.e., a downscaling process), that is, the difference between the coarse spatial resolution images (e.g., MODIS images) acquired at the known and prediction times. Owing to seasonal changes and land cover changes, there always exist large differences between images acquired at different times, resulting in a large increment and, further, great uncertainty in downscaling. In this paper, a virtual image pair-based spatio-temporal fusion (VIPSTF) approach was proposed to deal with this problem. VIPSTF is based on the concept of a virtual image pair (VIP), which is produced based on the available, known MODIS-Landsat image pairs. We demonstrate theoretically that compared to the known image pairs, the VIP is closer to the data at the prediction time. The VIP can capture more fine spatial resolution information directly from known images and reduce the challenge in downscaling. VIPSTF is a flexible framework suitable for existing spatial weighting- and spatial unmixing-based methods, and two versions VIPSTF-SW and VIPSTF-SU are, thus, developed. Experimental results on a heterogeneous site and a site experiencing land cover type changes show that both spatial weighting- and spatial unmixing-based methods can be enhanced by VIPSTF, and the advantage is particularly noticeable when the observed image pairs are temporally far from the prediction time. Moreover, VIPSTF is free of the need for image pair selection and robust to the use of multiple image pairs. VIPSTF is also computationally faster than the original methods when using multiple image pairs. The concept of VIP provides a new insight to enhance spatio-temporal fusion by making fuller use of the observed image pairs and reducing the uncertainty of estimating the fine spatial resolution increment. © 2020 Elsevier Inc.
英文关键词	Downscaling; Spatio-temporal fusion; Time-series images; Virtual image pair (VIP)
语种	英语
scopus关键词	Forecasting; Image acquisition; Image fusion; Image resolution; Radiometers; Uncertainty analysis; Downscaling process; Flexible framework; Land-cover change; Spatial and temporal resolutions; Spatial resolution; Spatial resolution images; Spatio-temporal fusions; Unified framework; Image enhancement; downscaling; image analysis; land cover; Landsat; MODIS; prediction; satellite imagery; spatial resolution; spatiotemporal analysis
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179177
作者单位	College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, 200092, China; Faculty of Science and Technology, Lancaster University, Lancaster, LA1 4YR, United Kingdom; Geography and Environment, University of Southampton, Highfield, Southampton, SO17 1BJ, United Kingdom
推荐引用方式 GB/T 7714	Wang Q.,Tang Y.,Tong X.,et al. Virtual image pair-based spatio-temporal fusion[J],2020,249.
APA	Wang Q.,Tang Y.,Tong X.,&Atkinson P.M..(2020).Virtual image pair-based spatio-temporal fusion.Remote Sensing of Environment,249.
MLA	Wang Q.,et al."Virtual image pair-based spatio-temporal fusion".Remote Sensing of Environment 249(2020).