Connecticut Public Use Parcels

About this view: This hosted feature view represents a filtered subset of the statewide parcel and CAMA dataset described below. The subset was produced by executing a text‑based query on the Owner, State Use and State Use Description attributes of the authoritative parcel layer. The query identifies parcels where the fields contains includes text strings associated publicly or privately owned land dedicated to governmental, institutional, infrastructure, utility, transportation, educational, recreational, or other public-serving functions. Data may be missing for certain municipalities (see Ownership Suppression below). Publicly Owned Parcels Query: Owner (contains any of the following): state of (exclude “estate”), state of conn, conn state, connecticut historical commission, connecticut airport authority, airport authority, university of conn, city of, town of, united states of america, united states government (us government, u.s. government, u s government), postal serv, post office, passenger co, penn central, board of ed, school dist, connecticut housing finance authority, housing auth, port auth, water auth, water co, sewer auth, public works, or power co. State Use Description (contains any of the following): state, fed, gov, post, hosp, fire, pol, library, educ, museum, cemet, mun (muni, munic), util, row, highway, or auth. This list of search terms is not exhaustive. The GISO has identified minimal false positives with using the above search terms. Reach out at [e-mail] with any feedback. About the source: Pursuant to Section 7-100l of the Connecticut General Statutes, each municipality is required to transmit a digital parcel file and an accompanying assessor’s database file (known as a CAMA report), to its respective regional council of governments (COG) by May 1 annually. The dataset has combined the Parcels and Computer-Assisted Mass Appraisal (CAMA) data for 2025 into a single dataset. This dataset is designed to make it easier for stakeholders and the GIS community to use and access the information as a geospatial dataset. Included in this dataset are geometries for all 169 municipalities and attribution from the CAMA data for all but one municipality. These data were gathered from the CT municipalities by the COGs and then submitted to CT OPM. This dataset was created on September 2025 from data collected in 2024-2025. Data was processed using Python scripts and ArcGIS Pro for standardization and integration of the data. To learn more about Parcel and CAMA in CT visit our Parcels Page in the Geodata Portal. Coordinate system: This dataset is provided in NAD 83 Connecticut State Plane (2011) (EPSG 6434) projection. Ownership Suppression: The updated dataset includes parcel data for all towns across the state, with some towns featuring fully suppressed ownership information. In these instances, the owner’s name was replaced with the label "Current Owner," the co-owner’s name will be listed as "Current Co-Owner," and the mailing address will appear as the property address itself. For towns with fully suppressed ownership data, please note that no "Suppression" field was included in the submission to confirm these details and this labeling approach was implemented as the solution. New Data Fields: The new dataset introduces the “Property Zip” and “Mailing Zip” fields, which will display the zip codes for the owner and property. Service URL: In 2024, we implemented a stable URL to maintain public access to the most up-to-date data layer. Users are strongly encouraged to transition to the new service as soon as possible to ensure uninterrupted workflows. This URL will remain persistent, providing long-term stability for your applications and integrations. Once you’ve transitioned to the new service, no further URL changes will be necessary. CAMA Notes: The CAMA underwent several steps to standardize and consolidate the information. Python scripts were used to concatenate fields and create a unique identifier for each entry. The resulting dataset contains 1,354,720 entries and information on property assessments and other relevant attributes. CAMA was provided by the towns. Spatial Data Notes: Data processing involved merging the parcels from different municipalities using ArcGIS Pro and Python. The resulting dataset contains 1,282,833 parcels. No alteration has been made to the spatial geometry of the data. Fields that are associated with CAMA data were provided by towns. The data fields that have information from the CAMA were sourced from the towns’ CAMA data. If no field for the parcels was provided for linking back to the CAMA by the town a new field within the original data was selected if it had a match rate above 50%, that joined back to the CAMA. Linking fields were renamed to "Link". All linking fields had a census town code added to the beginning of the value to create a unique identifier per town. Any field that was not town name, Location, Editor, Edit Date, or a field associated back to the CAMA, was not used in the creation of this Dataset. Only the fields related to town name, location, editor, edit date, and link fields associated with the towns’ CAMA were included in the creation of this dataset. Any other field provided in the original data was deleted or not used. Field names for town (Muni, Municipality) were renamed to "Town Name". Attributes included in the data: Town Name Owner Co-Owner Link Editor Edit Date Collection year – year the parcels were submitted Location Property Zip Mailing Address Mailing City Mailing State Mailing Zip Assessed Total Assessed Land Assessed Building Pre-Year Assessed Total Appraised Land Appraised Building Appraised Outbuilding Condition Model Valuation Zone State Use State Use Description Land Acre Living Area Effective Area Total rooms Number of bedrooms Number of Baths Number of Half-Baths Sale Price Sale Date Qualified Occupancy Prior Sale Price Prior Sale Date Prior Book and Page Planning Region FIPS Code *Please note that not all parcels have a link to a CAMA entry. *If any discrepancies are discovered within the data, whether pertaining to geographical inaccuracies or attribute inaccuracy, please directly contact the respective municipalities to request any necessary amendments Additional information about the specifics of data availability and compliance will be coming soon. 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