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Mapping Soil Properties With Satellite Data Using Machine Learning Approaches - EP3895067

The patent EP3895067 was granted to Climate on Sep 11, 2024. The application was originally filed on Dec 9, 2019 under application number EP19896354A. The patent is currently recorded with a legal status of "Granted And Under Opposition".

EP3895067

CLIMATE
Application Number
EP19896354A
Filing Date
Dec 9, 2019
Status
Granted And Under Opposition
Aug 8, 2024
Publication Date
Sep 11, 2024
External Links
Slate, Register, Google Patents

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YARA ASAJun 11, 2025AWA SWEDENADMISSIBLE

Patent Citations (14) New

Patent citations refer to prior patents cited during different phases such as opposition or international search.

Citation PhasePublication Number
INTERNATIONAL-SEARCH-REPORTUS2011055220
INTERNATIONAL-SEARCH-REPORTUS2018146624
INTERNATIONAL-SEARCH-REPORTUS9135505
OPPOSITIONUS10028451
OPPOSITIONUS2011055220
OPPOSITIONUS2012201415
OPPOSITIONUS2018146624
OPPOSITIONUS9135505
OPPOSITIONWO2017053127
OPPOSITIONWO2017189337
OPPOSITIONWO2019032648
SEARCHUS10028451
SEARCHWO2017053127
SEARCHWO2019032648

Non-Patent Literature (NPL) Citations (4) New

NPL citations refer to non-patent references such as research papers, articles, or other publications cited during examination or opposition phases.

Citation PhaseReference Text
OPPOSITION- D11 - US 62/778,268 (submitted to the IB on 29.12.2019)
OPPOSITION- Hengl Tomislav , Robert A. Macmillan, "Predictive Soil Mapping with R - Index ", Predictive Soil Mapping with R, Wageningen, Netherlands, OpenGeoHub foundation, (20190317), pages 1 - 14, ISBN 978-0-359-30635-0, XP093287411
OPPOSITION- Hengl Tomislav, Mendes De Jesus Jorge, Heuvelink Gerard B. M., Ruiperez Gonzalez Maria, Kilibarda Milan, Blagotić Aleksandar, Shangguan Wei, Wright Marvin N., Geng Xiaoyuan, Bauer-Marschallinger Bernhard, Guevara Mario Antonio, Vargas Rodrigo, Macmillan Robert A., Batjes Niels H., Leenaars Johan G. B., Ribeiro Eloi, Wheeler Ichsani, Mantel Stephan, Kempen Bas, "SoilGrids250m: Global gridded soil information based on machine learning", PLOS ONE, US , (20170216), vol. 12, no. 2, doi:10.1371/journal.pone.0169748, ISSN 1932-6203, pages 1 - 40, XP093287156
OPPOSITION- Nussbaum Madlene, Spiess Kay, Baltensweiler Andri, Grob Urs, Keller Armin, Greiner Lucie, Schaepman Michael E., Papritz Andreas, "Evaluation of digital soil mapping approaches with large sets of environmental covariates", SOIL, (20180101), vol. 4, no. 1, doi:10.5194/soil-4-1-2018, ISSN 2199-398X, pages 1 - 22, XP093287412

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