Automated Organization ProfileFacultad de Ingeniería Agrícola, Universidad de Concepción
Facultad de Ingeniería Agrícola, Universidad de Concepción
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 4.1 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
In Earth observation, data fusion is important to generate high temporal and spatial resolution images. Nevertheless, existing research on data fusion primarily concentrates on merging two sources of data (mostly MODIS and Landsat). Therefore, we offer the community a new benchmark dataset for evaluating data fusion using new European sensors (Sentinel-2 and Sentinel-3).The dataset is composed of three different sites located in different parts of the world to ensure the diversity of the ecosystem. The two components of the dataset are collected from operating missions ( Sentinel-2 and Sentinel-3). We also provide 10 bands for Sentinel-2 ranging from blue to SWIR, 4 bands at 10m resolution and 6 at 20m resolution. For Sentinel-3 16 bands are provided with a spatial resolution of 300m. The multiple bands allow for different applications for this dataset such as testing data fusion methods, etc.
Authors
- Boumahdi, Meryeme ;
- García-Pedrero, Angel ;
- Lillo-Saavedra, Mario ;
- Gonzalo-Martin, Consuelo
In Earth observation, data fusion is important to generate high temporal and spatial resolution images. Nevertheless, existing research on data fusion primarily concentrates on merging two sources of data (mostly MODIS and Landsat). Therefore, we offer the community a new benchmark dataset for evaluating data fusion using new European sensors (Sentinel-2 and Sentinel-3).The dataset is composed of three different sites located in different parts of the world to ensure the diversity of the ecosystem. The two components of the dataset are collected from operating missions ( Sentinel-2 and Sentinel-3). We also provide 10 bands for Sentinel-2 ranging from blue to SWIR, 4 bands at 10m resolution and 6 at 20m resolution. For Sentinel-3 16 bands are provided with a spatial resolution of 300m. The multiple bands allow for different applications for this dataset such as testing data fusion methods, etc.
Authors
- Boumahdi, Meryeme ;
- García-Pedrero, Angel ;
- Lillo-Saavedra, Mario ;
- Gonzalo-Martin, Consuelo
In Earth observation, data fusion is important to generate high temporal and spatial resolution images. Nevertheless, existing research on data fusion primarily concentrates on merging two sources of data (mostly MODIS and Landsat). Therefore, we offer the community a new benchmark dataset for evaluating data fusion using new European sensors (Sentinel-2 and Sentinel-3).The dataset is composed of three different sites located in different parts of the world to ensure the diversity of the ecosystem. The two components of the dataset are collected from operating missions ( Sentinel-2 and Sentinel-3). We also provide 10 bands for Sentinel-2 ranging from blue to SWIR, 4 bands at 10m resolution and 6 at 20m resolution. For Sentinel-3 16 bands are provided with a spatial resolution of 300m. The multiple bands allow for different applications for this dataset such as testing data fusion methods, etc.
Authors
- Boumahdi, Meryeme ;
- García-Pedrero, Angel ;
- Lillo-Saavedra, Mario ;
- Gonzalo-Martin, Consuelo