| Full text | |
| Author(s): Show less - |
Jessie Santos Pletsch, Mikhaela Aloisia
;
Korting, Thales Sehn
;
de Oliveira, Willian Vieira
;
Sanches, Ieda Del'Arco
;
Fernandez, Victor Velazquez
;
Gama, Fabio Furlan
;
Sobral Escada, Maria Isabel
;
Misra, S
;
Gervasi, O
;
Murgante, B
;
Stankova, E
;
Korkhov, V
;
Torre, C
;
Rocha, AMAC
;
Taniar, D
;
Apduhan, BO
;
Tarantino, E
Total Authors: 17
|
| Document type: | Journal article |
| Source: | COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2019, PT IV; v. 11622, p. 14-pg., 2019-01-01. |
| Abstract | |
Copernicus is the World's largest single Earth Observation (EO) programme, whose satellite constellations are planned to be launched between 2014 and 2025. Among the constellations, Sentinel-1 (S-1) is a C-band SAR able to support land cover mapping. Although optical data are commonly used for land cover monitoring, the low availability of cloud-free scenes along the year hinders the mapping process. In such a way, S-1 presents an important source of data, able of providing all-weather and day-and-night imagery of EO. In this study, we investigate the potential of using S-1 data to distinguish targets in Remote Sensing images in three different Brazilian biomes, Amazon, Cerrado, and Atlantic Forest. Based on that, we proposed a methodology to classify SAR images, which was validated considering a different area from the ones used for sampling purposes. The results showed that through S-1 data, it is possible to detect mainly water and urban area targets, with overall accuracy of 0.90, evidencing that our approach is reproducible in other regions. (AU) | |
| FAPESP's process: | 17/24086-2 - Management of metadata from remote sensing big data |
| Grantee: | Thales Sehn Körting |
| Support Opportunities: | Regular Research Grants |