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A global gridded data set on tillage - R-code

Cite as:

Porwollik, Vera; Rolinski, Susanne; Müller, Christoph (2018): A global gridded data set on tillage - R-code. V. 1.0. GFZ Data Services. http://doi.org/10.5880/PIK.2018.013

Status

I   N       R   E   V   I   E   W : Porwollik, Vera; Rolinski, Susanne; Müller, Christoph (2018): A global gridded data set on tillage - R-code. V. 1.0. GFZ Data Services. http://doi.org/10.5880/PIK.2018.013

Abstract

Tillage is a central element in agricultural soil management and has direct and indirect effects on processes in the biosphere. Effects of agricultural soil management can be assessed by soil, crop, and ecosystem models but global assessments are hampered by lack of information on soil management systems. This study presents a classification of globally relevant tillage practices and a global spatially explicit data set on the distribution of tillage practices for around the year 2005.

This source code complements the dataset on the global gridded tillage system mapping described in Porwollik et al. (2018, http://doi.org/10.5880/PIK.2018.012). It shall help interested people in understanding the findings on the global gridded tillage system mapping. The code, programmed in R, can be used for reproducing and build upon for scenarios including the expansion of sustainable soil management practices as CA. Both, the data set and the R-code are described in detail in Porwollik et al. (2018, ESSD). The code is written in the statistical software 'R' using the 'raster', 'fields', and 'ncdf4' packages.

We present the mapping result of six tillage systems for 42 crop types and potentially suitable Conservation Agriculture area as variables:
1 = conventional annual tillage
2 = traditional annual tillage
3 = reduced tillage
4 = Conservation Agriculture
5 = rotational tillage
6 = traditional rotational tillage
7 = potential suitable Conservation Agriculture area

Reference system: WGS84
Geographic extent: Longitude (min, max) (-180, 180), Latitude (min, max) (-56, 84)
Resolution: 5 arc-minutes
Time period covered: around the year 2005
Type: NetCDF

Dataset sources (with indication of reference):
1. Grid cell allocation key to country: IFPRI/IIASA (2017, cell5m_allockey_xy.dbf.zip)
2. Crop-specific physical cropland: IFPRI/IIASA (2017, spam2005v3r1_global_phys_area.geotiff.zip)
3. SoilGrids depth to bedrock: Hengl et al. (2014)
4. Aridity index: FAO (2015)
5. Conservation Agriculture area: FAO (2016)
6. Income level: World Bank (2017)
7. Field size: Fritz et al. (2015)
8. Water erosion: Nachtergaele et al. (2011)

Dataset Contact

  • Porwollik, Vera (PhD candidate) ; Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany;

Contributors

Heinke, Jens

Keywords

tillage, plowing, soil management, gridded data, Conservation Agriculture, ploughing

GCMD Science Keywords

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          • givenName: Vera
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          • affiliation: Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany
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          • affiliation: Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany
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        • title (xml:lang=en): A global gridded data set on tillage - R-code
      • publisher: GFZ Data Services
      • publicationYear: 2018
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        • subject: plowing
        • subject: soil management
        • subject: gridded data
        • subject: Conservation Agriculture
        • subject: ploughing
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          • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0001-5256-0024
          • affiliation: Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany
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        • date (dateType=Created): 2018-10-01
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      • language: en
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      • Entry_Title: A global gridded data set on tillage - R-code
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        • Dataset_Title: A global gridded data set on tillage - R-code
        • Dataset_Release_Date: 2018
        • Dataset_Release_Place: Potsdam, Germany
        • Dataset_Publisher: GFZ Data Services
        • Online_Resource: http://dx.doi.org/10.5880/PIK.2018.013
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        • Topic: AGRICULTURE
        • Term: AGRICULTURAL PLANT SCIENCE
        • Variable_Level_1: CROPPING SYSTEMS
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        • Category: EARTH SCIENCE
        • Topic: AGRICULTURE
        • Term: SOILS
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      • Keyword: tillage
      • Keyword: plowing
      • Keyword: soil management
      • Keyword: gridded data
      • Keyword: Conservation Agriculture
      • Keyword: ploughing
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          • Last_Name: Deutsches GeoForschungsZentrum GFZ
      • Summary
        • Abstract: Tillage is a central element in agricultural soil management and has direct and indirect effects on processes in the biosphere. Effects of agricultural soil management can be assessed by soil, crop, and ecosystem models but global assessments are hampered by lack of information on soil management systems. This study presents a classification of globally relevant tillage practices and a global spatially explicit data set on the distribution of tillage practices for around the year 2005. This source code complements the dataset on the global gridded tillage system mapping described in Porwollik et al. (2018, http://doi.org/10.5880/PIK.2018.012). It shall help interested people in understanding the findings on the global gridded tillage system mapping. The code, programmed in R, can be used for reproducing and build upon for scenarios including the expansion of sustainable soil management practices as CA. Both, the data set and the R-code are described in detail in Porwollik et al. (2018, ESSD). The code is written in the statistical software 'R' using the 'raster', 'fields', and 'ncdf4' packages. We present the mapping result of six tillage systems for 42 crop types and potentially suitable Conservation Agriculture area as variables: 1 = conventional annual tillage 2 = traditional annual tillage 3 = reduced tillage 4 = Conservation Agriculture 5 = rotational tillage 6 = traditional rotational tillage 7 = potential suitable Conservation Agriculture area Reference system: WGS84 Geographic extent: Longitude (min, max) (-180, 180), Latitude (min, max) (-56, 84) Resolution: 5 arc-minutes Time period covered: around the year 2005 Type: NetCDF Dataset sources (with indication of reference): 1. Grid cell allocation key to country: IFPRI/IIASA (2017, cell5m_allockey_xy.dbf.zip) 2. Crop-specific physical cropland: IFPRI/IIASA (2017, spam2005v3r1_global_phys_area.geotiff.zip) 3. SoilGrids depth to bedrock: Hengl et al. (2014) 4. Aridity index: FAO (2015) 5. Conservation Agriculture area: FAO (2016) 6. Income level: World Bank (2017) 7. Field size: Fritz et al. (2015) 8. Water erosion: Nachtergaele et al. (2011)
      • Metadata_Name: DIF
      • Metadata_Version: 9.8.2
  • escidoc:  /  download xml
    • resource
      • title (xml:lang=en): A global gridded data set on tillage - R-code
      • date (dateType=Valid): 2005
      • date (dateType=Created): 2018-10-01
      • creator
        • creatorName: Porwollik, Vera
        • givenName: Vera
        • familyName: Porwollik
        • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0001-5866-8538
        • affiliation: Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany
      • creator
        • creatorName: Rolinski, Susanne
        • givenName: Susanne
        • familyName: Rolinski
        • affiliation: Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany
      • creator
        • creatorName: Müller, Christoph
        • givenName: Christoph
        • familyName: Müller
        • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0002-9491-3550
        • affiliation: Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany

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    License: MIT Licence

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