Fig 1.
Framework used in computing suitability indices for neglected and underutilised crop species in South Africa (developed by the authors).
Table 1.
Factors used to delineate land suitability maps for neglected and underutilised crop species.
Table 2.
The fundamentals for pairwise comparison [49].
Table 3.
Pairwise comparison matrix.
Table 4.
Characteristics of sorghum [63], cowpea [63], taro [64] and amaranth [65].
Table 5.
Suitability indices for the different suitability classes [68].
Fig 2.
Suitability map for sorghum production in South Africa computed using MCDA-AHP and OWA operators [Source, South African Quaternary Catchments database, (https://doi.org/10.6084/m9.figshare.13179881), in ArcGIS 10.5].
Fig 3.
Suitability map for cowpea production in South Africa computed using MCDA-AHP and OWA operators [Source, South African Quaternary Catchments database, (https://doi.org/10.6084/m9.figshare.13179881), in ArcGIS 10.5].
Fig 4.
Suitability map for taro production in South Africa computed using MCDA-AHP and OWA operators [Source, South African Quaternary Catchments database, (https://doi.org/10.6084/m9.figshare.13179881), in ArcGIS 10.5].
Fig 5.
Suitability map for amaranth production in South Africa computed using MCDA-AHP and OWA operators.
[Source, South African Quaternary Catchments database, (https://doi.org/10.6084/m9.figshare.13179881), in ArcGIS 10.5].
Fig 6.
Average water requirement satisfactory indices for a period of 1981 to 2017 in cropping lands in South Africa.
[Source, Famine Early Warning Systems Network, (https://earlywarning.usgs.gov/fews, and from USGS Earth Explorer https://earthexplorer.usgs.gov/ and from USGS Earth Explorer https://earthexplorer.usgs.gov/), in ArcGIS 10.5].
Fig 7.
The Receiver Operating Characteristic (ROC), used to generate the Area Under the curve (AUC) which is used for model validation of the logistic regression model for spatial prediction of (a) sorghum, (b) cowpea, (c) amaranth and (d) taro.