@inproceedings{fdi:010075958,
  title = {{E}nrichment of trajectories with environmental data, and standardization of tagging data using {N}et{CDF}},
  author = {{N}ieblas, {A}.{E}. and {B}arde, {J}ulien and {B}ernard, {S}. and {I}mzilen, {T}aha and {K}erzerho, {V}. and {R}ouyer, {S}. and {B}onhommeau, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{G}eolocalisation and trajectory analysis can aid in understanding the ecological processes driving an organism. {B}y associating satellite-derived environmental data with individual trajectories of electronically-tagged organisms, it could be possible to define environmental characteristics of the tagged species' functional habitats (i.e., reproduction, nutrition). {T}hese data can also help identify biotic envelopes or predict the effects of climate change on marine species distributions. {T}he objective of the present work, undertaken as a collaboration between {IFREMER} and {IRD}, is to standardize electronic tag data files into network common data format ({N}et{CDF}) format, following the standards defined within the {POPSTAR} project for tag data (doi http://dx.doi.org/10.13155/34980), and enrich the positional data with satellite-derived surface environment data (e.g., sea surface temperature, salinity, sea level) and model-derived environment data at observed depths (e.g., temperature, salinity, currents). {W}e accounted for positional uncertainty using 95%, 75%, and 50% uncertainty polygons around the estimated positions of individuals. {W}e summarised environmental conditions within these uncertainty polygons using the mean, minimum, maximum, quantiles, and standard deviation of the selected enrichment parameter. {W}e generated generic codes to enable the automatic enrichment of position data from points and polygons. {F}urthermore, we developed algorithms to convert the enriched data into {N}et{CDF} format for subsequent visualisation and analysis.},
  keywords = {{ATLANTIQUE} ; {OCEAN} {INDIEN}},
  numero = {{IOTC}–2018–{WPDCS}14–25_{R}ev1},
  pages = {12  multigr.},
  booktitle = {},
  year = {2018},
  URL = {https://www.documentation.ird.fr/hor/fdi:010075958},
}