An Experimental Study of the Accuracy and Change Detection Potential of Blending Time Series Remote Sensing Images with Spatiotemporal Fusion
Over one hundred spatiotemporal fusion algorithms have been proposed, but convolutional neural networks trained with large amounts of data for spatiotemporal fusion have not shown significant advantages. In addition, no attention has been paid to whether fused images can be used for change detection...
Main Authors: | Jingbo Wei, Lei Chen, Zhou Chen, Yukun Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/15/15/3763 |
Similar Items
-
A Sensor Bias Correction Method for Reducing the Uncertainty in the Spatiotemporal Fusion of Remote Sensing Images
by: Hongwei Zhang, et al.
Published: (2022-07-01) -
Explicit and stepwise models for spatiotemporal fusion of remote sensing images with deep neural networks
by: Yaobin Ma, et al.
Published: (2021-12-01) -
Assessing the Accuracy of Landsat-MODIS NDVI Fusion with Limited Input Data: A Strategy for Base Data Selection
by: Yiting Wang, et al.
Published: (2021-01-01) -
Rice crop phenology mapping at high spatial and temporal resolution using downscaled MODIS time-series
by: Alex O. Onojeghuo, et al.
Published: (2018-09-01) -
Estimating Riverine Total Suspended Solids From Spatiotemporal Satellite Sensor Fusion
by: Elisa Friedmann, et al.
Published: (2024-01-01)