Results 21 to 30 of about 1,146,451 (358)

Geographically Weighted Spatial Unmixing for Spatiotemporal Fusion [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2022
Spatiotemporal fusion is a technique applied to create images with both fine spatial and temporal resolutions by blending images with different spatial and temporal resolutions. Spatial unmixing (SU) is a widely used approach for spatiotemporal fusion, which requires only the minimum number of input images.
Kaidi Peng, Qunming Wang, Yijie Tang, Xiaohua Tong, Peter M. Atkinson   +4 more
openaire   +2 more sources

Spatiotemporal Fusion With Only Two Remote Sensing Images as Input

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Spatiotemporal data fusion is an effective way of generating a dense time series with a high spatial resolution. Traditionally, the spatiotemporal fusion models, especially the popular ones such as the spatial and temporal adaptive reflectance fusion ...
Jingan Wu, Qing Cheng, Huifang Li, Shuang Li, Xiaobin Guan, Huanfeng Shen   +5 more
doaj   +1 more source

Adaptive-SFSDAF for Spatiotemporal Image Fusion that Selectively Uses Class Abundance Change Information

Remote Sensing, 2020
Many spatiotemporal image fusion methods in remote sensing have been developed to blend highly resolved spatial images and highly resolved temporal images to solve the problem of a trade-off between the spatial and temporal resolution from a single ...
Shuwei Hou, Wenfang Sun, Baolong Guo, Cheng Li, Xiaobo Li, Yingzhao Shao, Jianhua Zhang   +6 more
doaj   +1 more source

MSNet: A Multi-Stream Fusion Network for Remote Sensing Spatiotemporal Fusion Based on Transformer and Convolution

Remote Sensing, 2021
Remote sensing products with high temporal and spatial resolution can be hardly obtained under the constrains of existing technology and cost.
Weisheng Li, Dongwen Cao, Yidong Peng, Chao Yang   +3 more
doaj   +1 more source

Comparison of Five Spatio-Temporal Satellite Image Fusion Models over Landscapes with Various Spatial Heterogeneity and Temporal Variation [PDF]

, 2019
In recent years, many spatial and temporal satellite image fusion (STIF) methods have been developed to solve the problems of trade-off between spatial and temporal resolution of satellite sensors.
Chen, Xiuwan, Im, Jungho, Ke, Yinghai, Liu, Maolin, Yin, Qi   +4 more
core   +1 more source

Spatiotemporal Fusion of Formosat-2 and Landsat-8 Satellite Images: A Comparison of “Super Resolution-Then-Blend” and “Blend-Then-Super Resolution” Approaches

Remote Sensing, 2021
The spatiotemporal fusion technique has the advantages of generating time-series images with high-spatial and high-temporal resolution from coarse-resolution to fine-resolution images.
Tee-Ann Teo, Yu-Ju Fu
doaj   +1 more source

Spatiotemporal Fusion in Remote Sensing

, 2020
Remote sensing images and techniques are powerful tools to investigate earth’s surface. Data quality is the key to enhance remote sensing applications and obtaining clear and noise-free set of data is very difficult in most situations due to the varying acquisition (e.g., atmosphere and season), sensor and platform (e.g., satellite angles and sensor ...
Hessah, Albanwan,, Rongjun, Qin,
openaire   +4 more sources

A Comprehensive Flexible Spatiotemporal DAta Fusion Method (CFSDAF) for Generating High Spatiotemporal Resolution Land Surface Temperature in Urban Area

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Spatiotemporal fusion of land surface temperature (LST) has a vital significance in studying the temporal and spatial variation of urban heat islands.
Chenlie Shi, Ninglian Wang, Quan Zhang, Zhuang Liu, Xinming Zhu   +4 more
doaj   +1 more source

An Improved Spatiotemporal Data Fusion Method Using Surface Heterogeneity Information Based on ESTARFM

Remote Sensing, 2020
The use of the spatiotemporal data fusion method as an effective data interpolation method has received extensive attention in remote sensing (RS) academia.
Mengxue Liu, Xiangnan Liu, Xiaobin Dong, Bingyu Zhao, Xinyu Zou, Ling Wu, Hejie Wei   +6 more
doaj   +1 more source

A Novel Deep Learning-Based Spatiotemporal Fusion Method for Combining Satellite Images with Different Resolutions Using a Two-Stream Convolutional Neural Network

Remote Sensing, 2020
Spatiotemporal fusion is considered a feasible and cost-effective way to solve the trade-off between the spatial and temporal resolution of satellite sensors.
Duo Jia, Changqing Song, Changxiu Cheng, Shi Shen, Lixin Ning, Chun Hui   +5 more
doaj   +1 more source