10.5281/zenodo.3873143
https://zenodo.org/records/3873143
oai:zenodo.org:3873143
Camara, Gilberto
Gilberto
Camara
0000-0002-3681-487X
INPE (National Institute for Space Research), Brazil
On the Semantics of Big Earth Observation Data (talk)
Zenodo
2020
Big earth observation data, Land use science, Satellite image time series, Crop expansion, Brazilian Amazonia biome, Brazilian Cerrado biome,Tropical deforestation
2020-06-02
Presentation
10.5281/zenodo.3873142
Creative Commons Attribution 4.0 International
Satellite images are the most extensive source of data about our environment; they provide essential information about global challenges. Since petabytes of imagery are accessible, researchers can now track changes continuously. To work with big Earth observation data, scientists are developing data-driven and theory-limited methods. However, numbers do not speak for themselves. Data-driven approaches without robust theories can lead to results that will not advance our knowledge. We need sound theories to deal with big data without drowning in it.
In this talk, we argue that current ontologies and descriptive schemas used in image analysis cannot capture the complexity of landscape dynamics unveiled by big data. These schemas lack expressive power. Existing ontologies for land classification are object-centered; to work with big data, we need to include occurrents. For continuous monitoring of land change, event recognition needs to replace object identification as the prevailing paradigm. The presentation explains how event semantics can improve data-driven methods to fulfill the potential of big data.