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spatial analyses annual land use covers  (Agri-Food Laboratories)

 
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    Agri-Food Laboratories spatial analyses annual land use covers
    Spatial Analyses Annual Land Use Covers, supplied by Agri-Food Laboratories, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/kriging/aafc+decadal+land+semi+use/pm41081619-94-0-9
    Average 86 stars, based on 1 article reviews
    spatial analyses annual land use covers - by Bioz Stars, 2026-11
    86/100 stars

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    The workflow of the improved tensor completion algorithm under the C2F framework. The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary <t>Kriging</t> <t>interpolation</t> method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).
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    The workflow of the improved tensor completion algorithm under the C2F framework. The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Journal: Scientific Reports

    Article Title: A prediction model for soil heavy metal content based on improved tensor completion

    doi: 10.1038/s41598-025-07565-7

    Figure Lengend Snippet: The workflow of the improved tensor completion algorithm under the C2F framework. The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Article Snippet: The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Techniques: Generated, Software

    Kriging interpolation results for different metals. The interpolation results in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Journal: Scientific Reports

    Article Title: A prediction model for soil heavy metal content based on improved tensor completion

    doi: 10.1038/s41598-025-07565-7

    Figure Lengend Snippet: Kriging interpolation results for different metals. The interpolation results in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Article Snippet: The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Techniques: Generated, Software

    As completion process. The original heatmap in Fig. 3 are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Journal: Scientific Reports

    Article Title: A prediction model for soil heavy metal content based on improved tensor completion

    doi: 10.1038/s41598-025-07565-7

    Figure Lengend Snippet: As completion process. The original heatmap in Fig. 3 are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Article Snippet: The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Techniques: Generated, Software