Name
Title | ||
|---|---|---|
Developing and evaluating the feasibility of a new spatiotemporal fusion framework to improve remote sensing reflectance and dynamic LAI monitoring |
Abstract | ||
|---|---|---|
•A new spatiotemporal fusion (STF) framework is developed to maximize the spatial and temporal resolution of Sentinel-2 Multispectral Imager (S2-MSI) images for fusing S2-MSI and MODIS images with a scale ratio of 46.•A new STF method, CA-STF, is proposed and validated to be competent to provide accurate spectral reflectance and capture temporal and abrupt changes for near real-time and post-growth applications.•CA-STF is especially advantageous when the images at the base and prediction dates are weakly correlated over long temporal intervals.•The new STF framework is demonstrated to be potential for improving dynamic LAI monitoring more accurately and detailly. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.compag.2022.107037 | Computers and Electronics in Agriculture |
Keywords | DocType | Volume |
Spatiotemporal fusion,SupReME algorithm,CACAO,Sentinel-2 Multispectral Imager (S2-MSI) | Journal | 198 |
ISSN | Citations | PageRank |
0168-1699 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Li | 1 | 0 | 0.34 |
| Wanlin Gao | 2 | 6 | 7.58 |
| Jing-dun Jia | 3 | 1 | 0.70 |
| Sha Tao | 4 | 0 | 0.68 |
| Yanzhao Ren | 5 | 0 | 1.01 |