publication . Article . Other literature type . Preprint . 2020

On the semantics of big Earth observation data for land classification

Camara, Gilberto;
Open Access English
  • Published: 16 May 2020 Journal: Journal of Spatial Information Science (issn: 1948-660X, Copyright policy)
  • Publisher: University of Maine
Abstract
This paper discusses the challenges of using big Earth observation data for land classification. The approach taken is to consider pure data-driven methods to be insufficient to represent continuous change. We argue for sound theories when working with big data. After revising existing classification schemes such as FAO's Land Cover Classification System (LCCS), we conclude that LCCS and similar proposals cannot capture the complexity of landscape dynamics. We then investigate concepts that are being used for analyzing satellite image time series; we show these concepts to be instances of events. Therefore, for continuous monitoring of land change, event recogni...
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doi: 10.5311/josis.2020.20.645 , 10.5281/zenodo.3830792 , 10.5281/zenodo.3830791
Subjects
free text keywords: big data, earth observation, geospatial semantics, lucc, land-use change, Geography (General), G1-922, Big data, Earth observation, Geospatial semantics, LUCC, Land-use change, Information retrieval, Computer science, Semantics
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Article . 2020
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Other literature type . 2020
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Article . 2020
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