413 citations · 756 across the 8 of their papers we have counts for
8 papers
Weakly Supervised Cloud Detection Combining Spectral Features and Multi-Scale Deep Network
Shaocong Zhu, Zhiwei Li, Xinghua Li +1
Clouds significantly affect the quality of optical satellite images, which seriously limits their precise application. Recently, deep learning has been widely applied to cloud dete…
An attention mechanism based convolutional network for satellite precipitation downscaling over China
Yinghong Jing, Liupeng Lin, Xinghua Li +2
Precipitation is a key part of hydrological circulation and is a sensitive indicator of climate change. The Integrated Multi-satellitE Retrievals for the Global Precipitation Measu…
Fully Polarimetric SAR and Single-Polarization SAR Image Fusion Network
Liupeng Lin, Jie Li, Huanfeng Shen +3
The data fusion technology aims to aggregate the characteristics of different data and obtain products with multiple data advantages. To solves the problem of reduced resolution of…
Long time-series NDVI reconstruction in cloud-prone regions via spatio-temporal tensor completion
Dong Chu, Huanfeng Shen, Xiaobin Guan +4
The applications of Normalized Difference Vegetation Index (NDVI) time-series data are inevitably hampered by cloud-induced gaps and noise. Although numerous reconstruction methods…
Spatially Continuous and High-resolution Land Surface Temperature: A Review of Reconstruction and Spatiotemporal Fusion Techniques
Penghai Wu, Zhixiang Yin, Chao Zeng +6
Remotely sensed, spatially continuous and high spatiotemporal resolution (hereafter referred to as high resolution) land surface temperature (LST) is a key parameter for studying t…
Missing Data Reconstruction in Remote Sensing image with a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network
Qiang Zhang, Qiangqiang Yuan, Chao Zeng +2
Because of the internal malfunction of satellite sensors and poor atmospheric conditions such as thick cloud, the acquired remote sensing data often suffer from missing information…
A 33-year NPP monitoring study in southwest China by the fusion of multi-source remote sensing and station data
Xiaobin Guan, Huanfeng Shen, Wenxia Gan +4
Knowledge of regional net primary productivity (NPP) is important for the systematic understanding of the global carbon cycle. In this study, multi-source data were employed to con…
Correction of "Cloud Removal By Fusing Multi-Source and Multi-Temporal Images"
Chengyue Zhang, Zhiwei Li, Qing Cheng +2
Remote sensing images often suffer from cloud cover. Cloud removal is required in many applications of remote sensing images. Multitemporal-based methods are popular and effective…