المؤلفون: Angelini, M. E., Heuvelink, Gérard B. M., Lagacherie, Philippe

المساهمون: Instituto Nacional de Tecnología Agropecuaria (INTA), World Soil Information (ISRIC), Wageningen University and Research Wageningen (WUR), Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), This work was carried out within the ArtiSol project. The authors gratefully acknowledge the financial support forthis project provided by the Occitanie Region and theEuropean Fund for Regional Development (ERDF).

المصدر: ISSN: 1351-0754.

مصطلحات موضوعية: accuracy estimation, cokriging, digital soil mapping, high-resolution map, stochastic simulation, [SDV]Life Sciences [q-bio], [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, geo

العلاقة: https://hal.inrae.fr/hal-04056095Test

الإتاحة: https://doi.org/10.1111/ejss.13345Test
https://hal.inrae.fr/hal-04056095Test

المؤلفون: Turek, Maria Eliza, Poggio, Laura, Batjes, Niels H., Armindo, Robson André, de Jong van Lier, Quirijn, de Sousa, Luis, Heuvelink, Gerard B.M.

المصدر: International Soil and Water Conservation Research 11 (2023) 2 ; ISSN: 2095-6339

مصطلحات موضوعية: Digital soil mapping, Pedometrics, Soil hydraulic properties, SoilGrids, geo, envir

العلاقة: https://research.wur.nl/en/publications/global-mapping-of-volumetric-water-retention-at-100-330-and-15000Test

الإتاحة: https://research.wur.nl/en/publications/global-mapping-of-volumetric-water-retention-at-100-330-and-15000Test

المؤلفون: Heuvelink, G. B. M., Webster, R.

مصطلحات موضوعية: Digital soil mapping, Geostatistics, Kriging, Machine learning, Pedometrics, Soil, geo, envir

العلاقة: https://repository.rothamsted.ac.uk/download/58b2698dce40bde5655bcc8db85b97be757adb1ad6254877764fce948d198152/392039/1-s2.0-S2211675322000264-main.pdfTest; https://repository.rothamsted.ac.uk/item/988yz/spatial-statistics-and-soil-mapping-a-blossoming-partnership-under-pressureTest

الإتاحة: https://repository.rothamsted.ac.uk/download/58b2698dce40bde5655bcc8db85b97be757adb1ad6254877764fce948d198152/392039/1-s2.0-S2211675322000264-main.pdfTest
https://repository.rothamsted.ac.uk/item/988yz/spatial-statistics-and-soil-mapping-a-blossoming-partnership-under-pressureTest

المؤلفون: Steinbuch, Luc, Brus, Dick J., Heuvelink, Gerard B.M.

المصدر: European Journal of Soil Science 73 (2022) 1 ; ISSN: 1351-0754

مصطلحات موضوعية: Bayesian statistics, digital soil mapping, generalized linear model, geoRglm, model-based geostatistics, spatial statistics, stat, geo

العلاقة: https://library.wur.nl/WebQuery/wurpubs/585413Test

الإتاحة: https://library.wur.nl/WebQuery/wurpubs/585413Test

المؤلفون: Chen, Songchao, Mulder, Vera Leatitia, Heuvelink, Gerard B.M., Poggio, Laura, Caubet, Manon, Román Dobarco, Mercedes, Walter, Christian, Arrouays, Dominique

المصدر: Geoderma 366 (2020) ; ISSN: 0016-7061

مصطلحات موضوعية: Bias-corrected Variance Weighted, Data-poor countries, Digital soil mapping, Sample size requirement, Soil organic carbon, envir, geo

العلاقة: https://research.wur.nl/en/publications/model-averaging-for-mapping-topsoil-organic-carbon-in-franceTest

الإتاحة: https://research.wur.nl/en/publications/model-averaging-for-mapping-topsoil-organic-carbon-in-franceTest

المؤلفون: Samuel Rosa, A., Heuvelink, G.B.M., Vasques, G.M., Anjos, L.H.C.

المصدر: Geoderma 243-244 (2015) ; ISSN: 0016-7061

مصطلحات موضوعية: Digital soil mapping, Linear mixed model, auxiliary information, model accuracy, soil mapping cost, variable selection, geo, envir

العلاقة: https://research.wur.nl/en/publications/do-more-detailed-environmental-covariates-deliver-more-accurate-sTest

الإتاحة: https://research.wur.nl/en/publications/do-more-detailed-environmental-covariates-deliver-more-accurate-sTest

المؤلفون: Collard, F., Kempen, B., Heuvelink, G.B.M., Sabi, N.P.A., Richer de Forge, A.C., Lehmann, S., Nehlig, P., Arrouays, D.

المصدر: Geoderma Regional 1 (2014) ; ISSN: 2352-0094

مصطلحات موضوعية: Classification trees, Digital soil mapping, France, Multinomial logistic regression, Probability sampling, Random forest, Validation, geo, envir

العلاقة: https://research.wur.nl/en/publications/refining-a-reconnaissance-soil-map-by-calibrating-regression-modeTest

الإتاحة: https://research.wur.nl/en/publications/refining-a-reconnaissance-soil-map-by-calibrating-regression-modeTest