,,For lands used to produce crops, CEC developed a suitability model to simultaneously evaluate several factors that impact an area’s relative implication for croplands. In the CEC land use screens, implication is defined as a possible significance or a likely consequence of an action. For example, planning for energy infrastructure development in areas with more factors that support high-value croplands has implications for opportunities to preserve agricultural land. The variables used in the CEC Cropland Index Model contain information on soil quality (CA Revised Storie Index, Electrical Conductivity, and Sodium Adsorption Ratio), farmland designations (Prime Farmland, Unique Farmland and Farmland of Statewide Importance), and current existence of crops (as indicated by the California Statewide Crop Mapping). The CEC Cropland Index Model does not include statewide information for grazing lands or rangelands, and it is only applied to solar technology.,Each input data layer is transformed onto a common scale and weighted according to each dataset’s relative importance. The result is a summation of the input data layers into a single-gridded map. This final model output provides a numerically weighted index of importance for croplands at a given location. The classified version of the model output, given in this dataset, partitions the CEC Cropland Index Model at the mean into areas of high and low implication. The high implication area is used as an exclusion in the CEC Land Use Screens for solar technology. These regions have a relatively higher implication for cropland than the lower implication region.,The table below provides data sources that the CEC Cropland Index Model relies on. For a complete description of the model and its use in the 2023 CEC Land-Use Screens, please refer to the Land Use Screens Staff Report in the CEC Energy Planning Library.,

,,For lands used to produce crops, CEC developed a suitability model to simultaneously evaluate several factors that impact an area’s relative implication for croplands. In the CEC land use screens, implication is defined as a possible significance or a likely consequence of an action. For example, planning for energy infrastructure development in areas with more factors that support high-value croplands has implications for opportunities to preserve agricultural land. The variables used in the CEC Cropland Index Model contain information on soil quality (CA Revised Storie Index, Electrical Conductivity, and Sodium Adsorption Ratio), farmland designations (Prime Farmland, Unique Farmland and Farmland of Statewide Importance), and current existence of crops (as indicated by the California Statewide Crop Mapping). The CEC Cropland Index Model does not include statewide information for grazing lands or rangelands, and it is only applied to solar technology.,Each input data layer is transformed onto a common scale and weighted according to each dataset’s relative importance. The result is a summation of the input data layers into a single-gridded map. This final model output provides a numerically weighted index of importance for croplands at a given location. The classified version of the model output, given in this dataset, partitions the CEC Cropland Index Model at the mean into areas of high and low implication. The high implication area is used as an exclusion in the CEC Land Use Screens for solar technology. These regions have a relatively higher implication for cropland than the lower implication region.,The table below provides data sources that the CEC Cropland Index Model relies on. For a complete description of the model and its use in the 2023 CEC Land-Use Screens, please refer to the Land Use Screens Staff Report in the CEC Energy Planning Library.,

,Cropland Index,,The Cropland Index evaluates lands used to produce crops based on the following input datasets: Revised Storie Index, California Important Farmland data, Electrical Conductivity (EC), and Sodium Adsorption Ratio (SAR). Together, these input layers were used in a suitability model to generate this raster. High values are associated with better Croplands,,

,Cropland Index,,The Cropland Index evaluates lands used to produce crops based on the following input datasets: Revised Storie Index, California Important Farmland data, Electrical Conductivity (EC), and Sodium Adsorption Ratio (SAR). Together, these input layers were used in a suitability model to generate this raster. High values are associated with better Croplands,,

,

,

,

,

,

,