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Assessing the impact of sampling strategy in random forest-based predicting of soil nutrients: a study case from northern Morocco

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F22%3A92304" target="_blank" >RIV/60460709:41210/22:92304 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.tandfonline.com/doi/full/10.1080/10106049.2022.2048091" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/10106049.2022.2048091</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/10106049.2022.2048091" target="_blank" >10.1080/10106049.2022.2048091</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Assessing the impact of sampling strategy in random forest-based predicting of soil nutrients: a study case from northern Morocco

  • Original language description

    In this work, we tested different combinations of sampling strategies, random sampling and conditioned Latin Hypercube sampling and sample ratios to predict soil phosporus and potassium contents, previously estimated using dtandard laboratory protocols. Other environmental covariates, used as input data for prediction, were obtained from different sources (multispectral Landsat-OLI 8 image, WorldClim database, ISRIC soil database, and ASTER-GDEM). Our findings showed that random sampling was suitable for predicting phosphorus, while the conditioned Latin Hypercube sampling was suitable for predicting potassium. Furthermore, we observed that when the sample ratio increased from 10 to 25%, model accuracy improved in random sampling and cLHS for phosphorus and potassium prediction. However, before generalizing these findings, we recommend that further studies be conducted under different conditions (climate, soil types and parent materials) and testing other sample ratios to determine the best sampling strategy with the optimum ratio to predict soil nutrients better.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    40104 - Soil science

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Geocarto Imnternational

  • ISSN

    1010-6049

  • e-ISSN

    1010-6049

  • Volume of the periodical

    37

  • Issue of the periodical within the volume

    26

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    14

  • Pages from-to

    11209-11222

  • UT code for WoS article

    000769901700001

  • EID of the result in the Scopus database

    2-s2.0-85126724711