This category of planning priorities 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 2025 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 human impacts to disturb the landscape and ecological function are relatively high.  The CBI Terrestrial Landscape Intactness model result is partitioned at the mean, and the high category is shown in this GIS layer. Values of the dataset that lie above 0.3 are considered highly intact and considered higher-implication land; values of the dataset that are less than or equal to 0.3 are considered lower-implication land.  More information about this layer and its use in electric system planning is found in the 2023 Land Use Screens Staff Report in the CEC Energy Planning Library, as well as the information on the original model output from CBI below: 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 ).