Licensed and Unlicensed Cultivation Across Ban and Permit Jurisdictions

Findings
Takeaways
Recommendations
Methods
Resources

Project Overview

This project aimed to assess unlicensed cannabis production and its spatial distribution over time, to compare these assessments with licensed market development, and to investigate the factors that affect (or do not affect) variation in unlicensed production across space and time.

Findings

Broken out by objectives we have rendered the following:

Provide empirical assessments of California’s unlicensed cultivation amounts and geography over time

Provide empirical assessments of California’s unlicensed cultivation amounts and geography over time
  • Unlicensed cultivation expanded rapidly after legalization (2018-20) but has since receded to 2018 levels.
  • Cultivation moved from hillier, remote areas into flatter areas (2018-20) and then back toward remote, hillier areas (2020-24).
  • Participation in unlicensed cultivation was broad initially (2018-20) but has since become the domain of people in tenuous socio-economic situations.
  • Unlicensed cultivation has migrated from public to private lands because of milder consequences.
  • Unlicensed cultivators avoided fire-prone areas from 2018-2022 but have since moved back into these areas (2022-24).
  • There has been a consistent trend from outdoor to mixed-light cultivation.
  • Unlicensed indoor cultivation has grown at a steadier rate than outdoor/mixed light since 2021.

Identify policy and non-policy factors influencing extent of unlicensed cultivation:

  • Presence of licensed cultivation in a given area was the most consistent deterrent of unlicensed production.
  • Bans were not consistent or powerful indicators of unlicensed cultivation growth or decline.
  • Perceived intensity of enforcement was an initial deterrent (2018-20) but this effect diminished (2020-22) and reversed (2022-24), becoming correlated with increasing unlicensed cultivation.
  • Civil policies and enforcement (e.g. fines, landlord liability, hemp policies) became more efficacious over time.
  • Troubles with permitting programs barred many would-be cultivators from licensure, thus ballooning participation in unlicensed cultivation.
  • Bans, particularly when combined with a heavy enforcement reputation, created “whack-a-mole” movement of cultivation.
  • Market forces (specifically wholesale price declines) drove unlicensed cultivators out of operation and into more remote landscapes.

Compare licensed and unlicensed production

  • Growth of licensed cultivation was more consistent than unlicensed cultivation.
  • Licensed cultivation area increased more rapidly in new cultivation counties like Santa Barbara and decreased in legacy counties like Mendocino.
  • Unlicensed cultivation is responsive to changes in presence of licensed farms.

Assess potential environmental impacts of unlicensed cultivation in ban and permit counties

Over time, environmentally sensitive counties, especially those with permit programs, saw reduced unlicensed cultivation relative to less sensitive counties.

View All Findings

Key Takeaways

  • Promoting and maintaining a large network of licensed farms is the most effective way of deterring unlicensed cultivation.
  • Permitting programs are more effective than bans (particularly intensively-enforced bans) in addressing environmental harms.
  • Eradication-oriented enforcement has declining efficacy, specifically as persistent unlicensed cultivation winnows down to those with few other livelihood alternatives.
  • Civil regulatory policies (e.g. fines, landlord liability rules) show efficacy over time.
  • Unlicensed cultivation boomed (2018-20) busted (2020-22), and arrived at an equilibrium similar to 2018 levels (2022-24).
  • Licensed and unlicensed cultivation are geographically diverging into remote, cheaper areas (unlicensed) and flatter, more proximate, less environmentally sensitive areas (licensed).
  • Economic considerations (e.g. wholesale prices, barriers to licensure, alternative livelihood or land use possibilities) strongly mediate the extent and character of unlicensed cultivation.
  • Cultivation has moved (2022-24) toward areas with bans, strong enforcement reputations, and conservative voters, likely because of economic and/or regulatory pressures.
  • Integration of cannabis into regulatory and civic systems creates norms and fosters behaviors, even among unlicensed cultivators, that are socially and ecologically beneficial.
Read More on Takeaways

Policy Recommendations

State Licensing

Maximize quantity of licensed cultivators and owner-occupied farms statewide.

Local Permits

Create statewide small-farm carve-outs or ministerial pathways for localities to permit farms.

Personal Grows

Ensure personal cultivation is affordable and feasible throughout the state.

Enforcement

Integrate research into enforcement responses and resource requests around unlicensed cultivation.

Research

Support research on the economic and social predicaments of unlicensed cultivators.

Fines & Consequences

Eliminate exceptional penalties regarding cannabis agriculture and integrate cannabis into existing agricultural processes.

Track-and-Trace

Revisit California’s Track-and-Trace Program (CTTP) to minimize human error and enhance traceability.

Research Methods

Policy Review

For each California county, we created a planning code summary by analyzing cannabis ordinances, zoning and nuisance provisions, enforcement policies, and related county and Sheriff’s office materials. For permit counties, we also reviewed environmental documents and Grand Jury investigations. The summaries outline key regulatory features, including permitting and cultivation limits, CEQA pathways, and enforcement approaches in permit counties, and penalties and liability frameworks in ban counties.

CannaVision Mapping

CannaVision is a computer vision model developed by the State Water Resources Control Board (SWRCB) to map outdoor and mixed-light cannabis cultivation using aerial imagery and object detection techniques. The model was trained on a large labeled dataset of aerial imagery and applied to produce the outcome variables used in this analysis. Through a partnership with SWRCB, this project expanded the geographic range over which CannaVision could be reliably applied, strengthening its performance beyond its original area of use.

Spatial Modeling

Using CannaVision mapping data, we examined factors associated with the expansion or contraction of unlicensed cannabis cultivation, identifying key physical, policy, and socio-political variables that influenced where cultivation increased or decreased. We also analyzed how cultivation hotspots shifted within counties over time to understand the persistence or movement of activity. Additionally, we assessed potential environmental impacts by comparing changes in cultivation to county-level ecological sensitivity, including salmonid habitat, stream density, and undeveloped land, with trends evaluated separately for permit and ban counties.

Ethnographic Case Studies

We conducted ethnographic case studies in six counties selected to balance permit and ban jurisdictions, geographic and ecological diversity, and variation in policy approaches, focusing on areas with dramatic changes in unlicensed cultivation. Guided by predictive model outputs, the team carried out in-depth interviews with over 100 stakeholders and analyzed historical documents to understand policy implementation, local dynamics, and contextual factors. These case studies aimed to identify which local policies were most effective at reducing unlicensed cultivation and its environmental impacts.

Licensed Market Data Analysis

We analyzed licensed cannabis production and supply chain movement using METRC harvest data and the California Track-and-Trace Program (CTTP) transfer manifests. Harvest data provided insight into plant counts, number of harvests, and production weights across license types and regions, while CTTP transfer manifests allowed us to track how cannabis moved through the licensed market, including origins, destinations, and facility types. Our analysis focused on regional trends, the top counties for transfers, and other counties of interest, emphasizing the flow of cannabis through the supply chain rather than just production volumes.

Indoor Cultivation Estimation

The study leveraged the distinctive energy usage patterns of indoor cannabis cultivation, driven by high-intensity lighting and consistent light/dark cycles during flowering, to identify unlicensed operations. Using data from licensed commercial sites, warrant-based inspections, and media-reported residential cases, the team developed representative energy profiles for both commercial and residential cultivation. These profiles trained a machine learning model, which was applied to broader energy datasets to estimate the incidence and geographic distribution of unlicensed indoor cannabis cultivation across California.
Read About Our Methods, Data and Results

Resources

Acknowledgements

This report and accompanying materials are the product of 30 months of work by Michael Polson (PI), Amanda Reiman (Co-PI), Chris Dillis, Joanna Hossack, Seth Larosa, Margiana Petersen-Rockney, Kwabena Owusu Sarfo, and Jeremy Sorgen. Thank you to Van Butsic for his work initiating and supporting this project.

We are deeply grateful to the individuals who generously shared their time, knowledge, experiences, and understanding with us. We also thank the representatives at the Department of Cannabis Control, METRC, the State Water Resources Control Board, PG&E, and SoCal Edison who responded to our requests and questions.

We also want to acknowledge the time and efforts of the University of California, Berkeley students, whose work as research assistants helped us further our analysis of the findings. Undergraduate research assistants spent countless hours conducting background research, writing, and working with GIS. The work of undergraduates greatly assisted us: Anhika Marie Bui, Cate Carlson, Rebekah Derris Murphy, Iroha Harada, Mia Hsu Puzzo, Emily Ma, Daniel Rodriguez, Alessandra Soberanes, McCree Tang, Martina Anne Arendain, Martina Arendain, Peri Zoe Yildirim-Stanley, Ryan Jen Wong, Alexa Marie Weiss, Hannah Welke, and Xiaoya Yuan, Audrey Theresa Shao, Hennessy Jones, Danicka G Sailer, Ellie Suh, Noah Alexander Menz, and Vincent Xuan Nghiem.

A special thank you to Pheng Lor for his administrative and organizational support.

Finally, we would like to recognize the institutional and administrative support provided by the Department of Environmental Science, Policy & Management at the University of California system and the Cannabis Research Center.

The University of California, Berkeley, submits this Final Report in fulfillment of contract #93284, “Licensed and Unlicensed Cultivation Across Ban and Permit Jurisdictions,” under the grant provided by the California Department of Cannabis Control.