,This category of planning priorities in the CEC 2023 Land-Use Screens provides an estimate of terrestrial landscape condition based on the extent to which human impacts such as agriculture, urban development, natural resource extraction, and invasive species have disrupted the landscape across the State of California. It is based on the open-source logic modeling framework Environmental Evaluation Modeling System (EEMS) developed by Conservation Biology Institute (CBI). This multicriteria evaluation model result, last updated in 2016 and resolved at 1-kilometer square, spans values ranging from -1 to 1. The higher end of the spectrum indicates areas that are relatively intact based on the more than 30 input variables, and values in the lower end of the spectrum indicate where these human impacts to disturb the landscape and ecological function are relatively high.1,In the adapted version of the CBI Terrestrial Landscape Intactness given here, the dataset is partitioned into high and low categories based on the mean. Values of the dataset that lie above 0.3 are considered highly intact and are used as an exclusion. Values of the dataset that are less than or equal to 0.3 are allowed to remain in consideration for resource potential. Applying the partition at the mean allows for lands that are relatively more intact than disturbed to be considered for resource potential. The high category of landscape intactness given by this dataset is used as an exclusion in both the Core and SB 100 Terrestrial Climate Resilience Study screens.,This layer is featured in the CEC 2023 Land-Use Screens for Electric System Planning data viewer.,More information about this layer and its use in electric system planning is available in the Land Use Screens Staff Report in the CEC Energy Planning Library.,[1] Degagne, R., J. Brice, M. Gough, T. Sheehan, and J. Strittholt. 2016. “Terrestrial Landscape Intactness 1 kilometer, California.” Conservation Biology Institute.https://databasin.org/datasets/e3ee00e8d94a4de58082fdbc91248a65/,

,This category of planning priorities in the CEC 2023 Land-Use Screens provides an estimate of terrestrial landscape condition based on the extent to which human impacts such as agriculture, urban development, natural resource extraction, and invasive species have disrupted the landscape across the State of California. It is based on the open-source logic modeling framework Environmental Evaluation Modeling System (EEMS) developed by Conservation Biology Institute (CBI). This multicriteria evaluation model result, last updated in 2016 and resolved at 1-kilometer square, spans values ranging from -1 to 1. The higher end of the spectrum indicates areas that are relatively intact based on the more than 30 input variables, and values in the lower end of the spectrum indicate where these human impacts to disturb the landscape and ecological function are relatively high.1,In the adapted version of the CBI Terrestrial Landscape Intactness given here, the dataset is partitioned into high and low categories based on the mean. Values of the dataset that lie above 0.3 are considered highly intact and are used as an exclusion. Values of the dataset that are less than or equal to 0.3 are allowed to remain in consideration for resource potential. Applying the partition at the mean allows for lands that are relatively more intact than disturbed to be considered for resource potential. The high category of landscape intactness given by this dataset is used as an exclusion in both the Core and SB 100 Terrestrial Climate Resilience Study screens.,This layer is featured in the CEC 2023 Land-Use Screens for Electric System Planning data viewer.,More information about this layer and its use in electric system planning is available in the Land Use Screens Staff Report in the CEC Energy Planning Library.,[1] Degagne, R., J. Brice, M. Gough, T. Sheehan, and J. Strittholt. 2016. “Terrestrial Landscape Intactness 1 kilometer, California.” Conservation Biology Institute.https://databasin.org/datasets/e3ee00e8d94a4de58082fdbc91248a65/,

,This dataset provides an estimate of terrestrial landscape intactness, (i.e. condition), based on the extent to which human impacts such as agriculture, urban development, natural resource extraction, and invasive species have disrupted the landscape across the State of California. Terrestrial intactness values are high in areas where these impacts are low. This dataset, updated April 2025, is the most recent version created for CAL FIRE using the open-source logic modeling framework Environmental Evaluation Modeling System (EEMS). Spatially-explicit logic modeling hierarchically integrates numerous and diverse datasets into composite layers, quantifying information in a continuous rather than binary fashion. This technique yields accessible decision-support products that agencies can use to craft scientifically-rigorous management strategies. The analysis was carried out at 1 sq. km resolution.The California Statewide Landscape Intactness model integrates data from many different sources: agriculture development (from FRAP Vegetation, and CDL Cropscape), urban development (from LANDFIRE EVT and NLCD Impervious Surfaces), polluted areas (from NHD treatment ponds and EPA Superfund and Brownfield sites), linear development (OHV routes from owlsheadgps.com, roads from TIGER (broken down by type), utility lines, railroads, and pipelines from various state and BLM sources), point development (communication towers from the FCC), energy and mining development (from the state’s Office of Mine Reclamation mine dataset, larger mine footprints, state geothermal wells, USGS wind turbines, solar footprints, renewable projects in development, oil refineries and state oil/gas wells), planned clear cuts from Statewide Timber Harvest Plans, invasive vegetation (compiled from multiple sources including LANDFIRE EVT and USGS INHABIT), and measures of natural vegetation fragmentation. Input data range in currency from 2011-2024; the majority of data portray the more recent condition of the landscape. Results apply to terrestrial areas only. (Water bodies are omitted from the final dataset.) Online interactive maps showing the intactness model’s input data, intermediate layers, and final results can be explored via the Conservation Biology Institute’s platforms EEMS Online and Data Basin.Caution is warranted in interpreting this dataset because it provides a single estimate of terrestrial intactness based on available data. The degree of terrestrial intactness likely varies for a particular species or conservation element and may depend on additional factors or thresholds not included in this model. This model should be taken as a general measure of intactness that can serve as a template for evaluating across many species at the ecoregion scale, and provides a framework within which species-specific parameters can be incorporated for more detailed analyses.Work funded by the California Department of Forestry and Fire Protection ( CAL FIRE ), Fire and Resource Assessment Program ( FRAP ).,

,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,,

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,,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.,

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