Zobrazeno 1 - 3
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pro vyhledávání: '"d'Andrimont, Rapha��l"'
Street-level imagery holds a significant potential to scale-up in-situ data collection. This is enabled by combining the use of cheap high quality cameras with recent advances in deep learning compute solutions to derive relevant thematic information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2b0b0c3bd14b471734344e31cc13754
http://arxiv.org/abs/2112.09190
http://arxiv.org/abs/2112.09190
Publikováno v:
Ecological Informatics. 70:101757
Approximate distance estimation can be used to determine fundamental landscape properties including complexity and openness. We show that variations in the skyline of landscape photos can be used to estimate distances to trees on the horizon. A metho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a95fb8eadbbad87d0c33ae09fd4c96b
https://doi.org/10.1016/j.ecoinf.2022.101757
https://doi.org/10.1016/j.ecoinf.2022.101757
Autor:
d'Andrimont, Rapha��l, Yordanov, Momchil, Martinez-Sanchez, Laura, Eiselt, Beatrice, Palmieri, Alessandra, Dominici, Paolo, Gallego, Javier, Reuter, Hannes Isaak, Joebges, Christian, Lemoine, Guido, van der Velde, Marijn
Accurately characterizing land surface changes with Earth Observation requires geo-localized ground truth. In the European Union (EU), a tri-annual surveyed sample of land cover and land use has been collected since 2006 under the Land Use/Cover Area
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03aee907313dee38621701872556b583
http://arxiv.org/abs/2005.05272
http://arxiv.org/abs/2005.05272