Improving spatiotemporal data fusion method in multiband images by distributing variates
Abstract Several spatiotemporal data fusion methods have been developed to generate continuous fine-resolution satellite imagery using widely available datasets. This study introduces the Residual Distribution-based Spatiotemporal Data Fusion Method (RDSFM), designed to enhance fusion accuracy. RDSF...
Saved in:
| Main Authors: | Yihua Jin, Zhenhao Yin, Weihong Zhu, Dongkun Lee |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-05016-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
MosaicFormer: A Novel Approach to Remote Sensing Spatiotemporal Data Fusion for Lake Water Monitors
by: Dongxue Zheng, et al.
Published: (2025-03-01) -
Ice drift in Peter the Great Bay
by: Vyacheslav A. Dubina, et al.
Published: (2014-09-01) -
A Spatially‐Distributed Machine Learning Approach for Fractional Snow Covered Area Estimation
by: Shalini Mahanthege, et al.
Published: (2024-11-01) -
Spatiotemporal Fusion of Multi-Temporal MODIS and Landsat-8/9 Imagery for Enhanced Daily 30 m NDVI Reconstruction: A Case Study of the Shiyang River Basin Cropland (2022)
by: Peiwen Mu, et al.
Published: (2025-04-01) -
A VCA Combined MHSA-CNN for Aero-Engine Hot Jet Remote Sensing Mixed Spectral Feature Extraction
by: Zhenping Kang, et al.
Published: (2025-03-01)