气候变化领域集成服务门户(CCPortal): Blocks-removed spatial unmixing for downscaling MODIS images

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DOI	10.1016/j.rse.2021.112325
	Blocks-removed spatial unmixing for downscaling MODIS images
	Wang Q.; Peng K.; Tang Y.; Tong X.; Atkinson P.M.
发表日期	2021
ISSN	00344257
卷号	256
英文摘要	The Terra/Aqua MODerate resolution Imaging Spectroradiometer (MODIS) data have been used widely for global monitoring of the Earth's surface due to their daily fine temporal resolution. The spatial resolution of MODIS time-series (i.e., 500 m), however, is too coarse for local monitoring. A feasible solution to this problem is to downscale the coarse MODIS images, thus creating time-series images with both fine spatial and temporal resolutions. Generally, the downscaling of MODIS images can be achieved by fusing them with fine spatial resolution images (e.g., Landsat images) using spatio-temporal fusion methods. Among the families of spatio-temporal fusion methods, spatial unmixing-based methods have been applied widely owing to their lighter dependence on the available fine spatial resolution images. However, all techniques within this class of method suffer from the same serious problem, that is, the block effect, which reduces the prediction accuracy of spatio-temporal fusion. To our knowledge, almost no solution has been developed to tackle this issue directly. To address this need, this paper proposes a blocks-removed spatial unmixing (SU-BR) method, which removes the blocky artifacts by including a new constraint constructed based on spatial continuity. SU-BR provides a flexible framework suitable for any existing spatial unmixing-based spatio-temporal fusion method. Experimental results on a heterogeneous region, a homogeneous region and a region experiencing land cover changes show that SU-BR removes the blocks effectively and increases the prediction accuracy obviously in all three regions. SU-BR also outperforms two popular spatio-temporal fusion methods. SU-BR, thus, provides a crucial solution to overcome one of the longest standing challenges in spatio-temporal fusion. © 2021 Elsevier Inc.
英文关键词	Block effect; Downscaling; Image fusion; Landsat; MODIS; Spatial unmixing; Spatio-temporal fusion
语种	英语
scopus关键词	Image resolution; Radiometers; Time series; Heterogeneous region; Homogeneous regions; Moderate resolution imaging spectroradiometer datum; Prediction accuracy; Spatial and temporal resolutions; Spatial resolution images; Spatio-temporal fusions; Temporal resolution; Image fusion; accuracy assessment; feasibility study; Landsat; MODIS; prediction; spatial resolution; spatiotemporal analysis; time series
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/178932
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.,Peng K.,Tang Y.,et al. Blocks-removed spatial unmixing for downscaling MODIS images[J],2021,256.
APA	Wang Q.,Peng K.,Tang Y.,Tong X.,&Atkinson P.M..(2021).Blocks-removed spatial unmixing for downscaling MODIS images.Remote Sensing of Environment,256.
MLA	Wang Q.,et al."Blocks-removed spatial unmixing for downscaling MODIS images".Remote Sensing of Environment 256(2021).