@Article{Cāmara:2020:SeBiEa,
author = "C{\^a}mara, Gilberto",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "On the semantics of big Earth observation data for land
classification",
journal = "Journal of Spatial Information Science",
year = "2020",
volume = "20",
pages = "21--34",
keywords = "big data, Earth observation, geospatial semantics, LUCC, land-use
change.",
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. I argue for sound theories when working with
big data. After revising existing classification schemes such as
FAO's Land Cover Classification System (LCCS), I conclude that
LCCS and similar proposals cannot capture the complexity of
landscape dynamics. I then investigate concepts that are being
used for analyzing satellite image time series; I show these
concepts to be instances of events. Therefore, for continuous
monitoring of land change, event recognition needs to replace
object identification as the prevailing paradigm. The paper
concludes by showing how event semantics can improve data-driven
methods to fulfil the potential of big data.",
doi = "10.5311/JOSIS.2020.20.645",
url = "http://dx.doi.org/10.5311/JOSIS.2020.20.645",
issn = "1948-660X",
language = "en",
targetfile = "camara_semantics.pdf",
urlaccessdate = "19 abr. 2024"
}