3873143
doi
10.5281/zenodo.3873143
oai:zenodo.org:3873143
On the Semantics of Big Earth Observation Data (talk)
Camara, Gilberto
INPE (National Institute for Space Research), Brazil
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Big earth observation data, Land use science, Satellite image time series, Crop expansion, Brazilian Amazonia biome, Brazilian Cerrado biome,Tropical deforestation
<p>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 <em>data-driven and theory-limited</em> 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.</p>
<p>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, <em>event recognition</em> needs to replace <em>object identification</em> as the prevailing paradigm. The presentation explains how <em>event semantics</em> can improve data-driven methods to fulfill the potential of big data.</p>
Zenodo
2020-06-02
info:eu-repo/semantics/lecture
3873142
1591136300.112142
17954261
md5:654e6a85e2a9a13c042371c87313c77c
https://zenodo.org/records/3873143/files/Semantics_BigEOData.pdf
public
10.5281/zenodo.3873142
isVersionOf
doi