Name
Abstract | ||
|---|---|---|
In this paper, we present a new approach to the fusion of Sentinel 1 (S1) and Sentinel 2 (S2) data for land cover mapping. The proposed solution aims at improving methods based on Sentinel 2 data, that are unusable in case of cloud cover. This goal is achieved by using S1 data to generate S2-like segmentation maps to be used to integrate S2 acquisitions forbidden by cloud cover. In particular, we propose for the first time in remote sensing a multi-temporal W-Net approach for the segmentation of Interferometric Wide swath mode (IW) Sentinel-1 data collected along ascending/descending orbit to discriminate rice, water, and bare soil. The quantitative assessment of segmentation accuracy shows an improvement of 0.18 and 0.25 in terms of accuracy and F1-score by applying the proposed multi-temporal procedure with respect to the previous single-date approach. Advantages and disadvantages of the proposed W-Net based solution have been tested in the National Park of Albufera, Valencia, and we show a performance gain in terms of the classical metrics used in segmentation tasks and the computational time. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3390/s20102969 | SENSORS |
Keywords | DocType | Volume |
synthetic aperture radar,image segmentation,rice monitoring,convolutional neural network,data fusion,time-series analysis,sentinel data | Journal | 20 |
Issue | ISSN | Citations |
10 | 1424-8220 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Massimiliano Gargiulo | 1 | 4 | 1.20 |
| Domenico A G Dell'Aglio | 2 | 0 | 0.34 |
| Antonio Iodice | 3 | 453 | 73.07 |
| Daniele Riccio | 4 | 781 | 118.99 |
| Giuseppe Ruello | 5 | 164 | 36.57 |