Extensive land use and geographic data at the tax lot level in GIS format (ESRI Shapefile). Contains more than seventy fields derived from data maintained by city agencies, merged with tax lot features from the Department of Finance’s Digital Tax Map, clipped to the shoreline. All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

To access the tax lot layer you will need to contact the county Assessor's office. ORMAP is a statewide digital cadastral base map that is publicly accessible, continually maintained, supports the Oregon property tax system, supports a multi-purpose land information system, strives to comply with appropriate state and national standards, and will continue to be improved over time.

Historic land uses on lots that were vacant, privately owned, and zoned for manufacturing in 2009. Information came from a review of several years of historical Sanborn maps over the past 100 years. When the SPEED 1.0 mapping application was created in 2009, OER had its vendor examine historic land use maps on vacant, privately-owned, industrially-zoned tax lots. Up to seven years of maps for each lot were examined, and information was recorded that indicated industrial uses or potential environmental contamination such as historic fill. Data for an additional 139 lots requested by community-based organizations was added in 2014. Each record represents the information from a map from a particular year on a particular tax lot at that time. Limitations of funding determined the number of lots included and entailed that not all years were examined for each lot.

This dataset represents a compilation of data from various government agencies throughout the City of New York. The underlying geography is derived from the Tax Lot Polygon feature class that is part of the Department of Finance's Digital Tax Map (DTM). The tax lots have been clipped to the shoreline, as defined by NYCMap planimetric features. The attribute information is from the Department of City Planning's PLUTO data. The attribute data pertains to tax lot and building characteristics and geographic, political and administrative information for each tax lot in New York City.The Tax Lot Polygon feature class and PLUTO are derived from different sources. As a result, some PLUTO records do not have a corresponding tax lot in the Tax Lot polygon feature class at the time of release. These records are included in a separate non-geographic PLUTO Only table. There are a number of reasons why there can be a tax lot in PLUTO that does not match the DTM; the most common reason is that the various source files are maintained by different departments and divisions with varying update cycles and criteria for adding and removing records. The attribute definitions for the PLUTO Only table are the same as those for MapPLUTO. DCP Mapping Lots includes some features that are not on the tax maps. They have been added by DCP for cartographic purposes. They include street center 'malls', traffic islands and some built streets through parks. These features have very few associated attributes.To report problems, please open a GitHub issue or email DCPOpendata@planning.nyc.gov.DATES OF INPUT DATASETS:Department of City Planning - E-Designations: 2/5/2021Department of City Planning - Zoning Map Index: 7/31/2019Department of City Planning - NYC City Owned and Leased Properties: 11/15/2020Department of City Planning - NYC GIS Zoning Features: 2/5/2021Department of City Planning - Polictical and Administrative Districts: 11/17/2020Department of City Planning - Geosupport version 20D: 11/17/2020Department of Finance - Digital Tax Map: 1/30/2021Department of Finance - Mass Appraisal System (CAMA): 2/10/2021Department of Finance - Property Tax System (PTS): 2/6/2021Landmarks Preservation Commission - Historic Districts: 2/4/2021Landmarks Preservation Commission - Individual Landmarks: 2/4/2021Department of Information Telecommunications & Technology - Building Footprints: 2/10/2021Department of Parks and Recreation - GreenThumb Garden Info: 1/4/2021

Map showing land uses in the City of Austin jurisdictions. Upated during October of even years.

To access parcel information:Enter an address or zoom in by using the +/- tools or your mouse scroll wheel. Parcels will draw when zoomed in.Click on a parcel to display a popup with information about that parcel.Click the "Basemap" button to display background aerial imagery.From the "Layers" button you can turn map features on and off.Complete Help (PDF)Parcel Legend:Full Map LegendAbout this ViewerThis viewer displays land property boundaries from assessor parcel maps across Massachusetts. Each parcel is linked to selected descriptive information from assessor databases. Data for all 351 cities and towns are the standardized "Level 3" tax parcels served by MassGIS. More details ...Read about and download parcel dataUpdatesV 1.1: Added 'Layers' tab. (2018)V 1.2: Reformatted popup to use HTML table for columns and made address larger. (Jan 2019)V 1.3: Added 'Download Parcel Data by City/Town' option to list of layers. This box is checked off by default but when activated a user can identify anywhere and download data for that entire city/town, except Boston. (March 14, 2019)V 1.4: Data for Boston is included in the "Level 3" standardized parcels layer. (August 10, 2020)V 1.4 MassGIS, EOTSS 2021

Map showing the General Plan Land Use for the City of San Marcos. For additional information, please visit the City's website.

The CNES Land Cover Map (Occupation des Sols, OSO) produces land classification for Metropolitan France at 10 m spatial resolution based on Sentinel-2 L2A data within the Theia Land Cover CES framework. Maps for 2021, 2020, 2019, and 2018 use a 23-categories nomenclature. For earlier maps in 2017 and 2016, a fully compatible 17-classes nomenclature is employed.

Minnesota's original public land survey plat maps were created between 1848 and 1907 during the first government land survey of the state by the U.S. Surveyor General's Office. This collection of more than 3,600 maps includes later General Land Office (GLO) and Bureau of Land Management maps up through 2001. Scanned images of the maps are available in several digital formats and most have been georeferenced.

The survey plat maps, and the accompanying survey field notes, serve as the fundamental legal records for real estate in Minnesota; all property titles and descriptions stem from them. They also are an essential resource for surveyors and provide a record of the state's physical geography prior to European settlement. Finally, they testify to many years of hard work by the surveying community, often under very challenging conditions.

The deteriorating physical condition of the older maps (drawn on paper, linen, and other similar materials) and the need to provide wider public access to the maps, made handling the original records increasingly impractical. To meet this challenge, the Office of the Secretary of State (SOS), the State Archives of the Minnesota Historical Society (MHS), the Minnesota Department of Transportation (MnDOT), MnGeo and the Minnesota Association of County Surveyors collaborated in a digitization project which produced high quality (800 dpi), 24-bit color images of the maps in standard TIFF, JPEG and PDF formats - nearly 1.5 terabytes of data. Funding was provided by MnDOT.

In 2010-11, most of the JPEG plat map images were georeferenced. The intent was to locate the plat images to coincide with statewide geographic data without appreciably altering (warping) the image. This increases the value of the images in mapping software where they can be used as a background layer.

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2018(LCM2018) representing Great Britain. It describes Great Britain's land cover in 2018 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2018 20m classified pixels dataset. All further LCM2018 datasets for Great Britain are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value, and a range of per-parcel pixel statistics to help to assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2018 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2018. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2018. LCM2018 was simultaneously released with LCM2017 and LCM2019. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/9f7f7f70-5137-4bfc-a6a3-f91783d5a6a6

We are also including tabular version that’s slightly more comprehensive (would include anything that didn’t join to the parcel basefile due to lot alterations or resubdivisions since 2023 and/or due to parcels comprised of condos). There are approximately 200 records that don't join to the spatial parcel file and some additional that are null in the spatial parcel file, altogether around 560 total. This Excel file can be downloaded HERE, and does not contain the latitude and longitude information.Data Dictionary:Attribute LabelDefinitionSourceTAX_IDUnique 26 character property tax identification numberOnondaga County PlanningPRINTKEYAbbreviated tax identification number (section-block-lot)Onondaga County PlanningADDRESSNUMProperty’s physical street addressOnondaga County PlanningADDRESSNAMProperty’s physical street nameOnondaga County PlanningTAX_ID_1City Tax ID number (26 digit number used for parcel mapping)City of Syracuse - AssessmentSBLProperty Tax Map Number (Section, Block, Lot)City of Syracuse - AssessmentPNUMBRProperty Number (10 digit number)City of Syracuse - AssessmentStNumParcel street numberCity of Syracuse - AssessmentStNameParcel street nameCity of Syracuse - AssessmentFullAddressStreet number and street nameCity of Syracuse - AssessmentZipParcel zip codeCity of Syracuse - Assessmentdesc_1Lot description including dimensionsCity of Syracuse - Assessmentdesc_2Lot description including dimensionsCity of Syracuse - Assessmentdesc_3Lot description including dimensionsCity of Syracuse - AssessmentSHAPE_IND City of Syracuse - AssessmentLUC_parcelNew York State property type classification code assigned by assessor during each roll categorizing the property by use. For more details: https://www.tax.ny.gov/research/property/assess/manuals/prclas.htmCity of Syracuse - AssessmentLU_parcelNew York State property type classification nameCity of Syracuse - AssessmentLUCat_OldLegacy land use category that corresponds to the overarching NYS category, i.e. all 400s = commercial, all 300s = vacant land, etc.NAland_avLand assessed valueCity of Syracuse - Assessmenttotal_avFull assessed valueCity of Syracuse - AssessmentOwnerProperty owner name (First, Initial, Last, Suffix)City of Syracuse - AssessmentAdd1_OwnPOBoxProperty owner mailing address (PO Box)City of Syracuse - AssessmentAdd2_OwnStAddProperty owner mailing address (street number, street name, street direction)City of Syracuse - AssessmentAdd3_OwnUnitInfoProperty owner mailing address unit info (unit name, unit number)City of Syracuse - AssessmentAdd4_OwnCityStateZipProperty owner mailing address (city, state or country, zip code)City of Syracuse - AssessmentFRONTFront footage for square or rectangular shaped lots and the effective front feet on irregularly shaped lots in feetCity of Syracuse - AssessmentDEPTHActual depth of rectangular shaped lots in feet (irregular lots are usually measured in acres or square feet)City of Syracuse - AssessmentACRESNumber of acres (where values were 0, acreage calculated as FRONT*DEPTH)/43560)City of Syracuse - Assessmentyr_builtYear built. Where year built was "0" or null, effective year built is given. (Effective age is determined by comparing the physical condition of one building with that of other like-use, newer buildings. Effective age may or may not represent the actual year built; if there have been constant upgrades or excellent maintenance this may be more recent than the original year built.)City of Syracuse - Assessmentn_ResUnitsNumber of residential unitsNA - Calculated fieldIPSVacantIs it a vacant structure? ("Commercial" or "Residential" = Yes; null = No)City of Syracuse - Division of Code EnforcementIPS_ConditionProperty Condition Score assigned to vacant properties by housing inspectors during routine vacant inspections (1 = Worst; 5 = Best)City of Syracuse - Division of Code EnforcementNREligibleNational Register of Historic Places Eligible ("NR Eligible (SHPO)," or "NR Listed")City of Syracuse - Neighborhood and Business DevelopmentLPSSLocally Protected Site Status ("Eligible/Architecturally Significant" or "Local Protected Site or Local District")City of Syracuse - Neighborhood and Business DevelopmentWTR_ACTIVEWater activity code ("I" = Inactive; "A" = Active)City of Syracuse - WaterRNIIs property located in Resurgent Neighborhood Initiative (RNI) Area? (1 = Yes; 0 = No)City of Syracuse - Neighborhood and Business DevelopmentDPW_QuadGeographic quadrant property is located in. Quadrants are divided Northwest, Northeast, Southwest, and Southeast based on property location in relation to I-81 and I-690. DPW uses the quad designation for some types of staff assignments.City of Syracuse - Department of Public WorksTNT_NAMETNT Sector property is located inCity of Syracuse - Neighborhood and Business DevelopmentNHOODCity NeighborhoodSyracuse-Onondaga County Planning Agency (SOCPA)NRSAIs property located in Neighborhood Revitalization Strategy Area (NRSA)? (1 = Yes; 0 = No)City of Syracuse - Neighborhood and Business DevelopmentDOCE_AreaGeographic boundary use to assign Division of Code Enforcement casesCity of Syracuse - Neighborhood and Business DevelopmentZONE_DIST_PREVFormer zoning district codeSyracuse-Onondaga County Planning Agency (SOCPA)REZONEReZone designation (adopted June 2023)City of Syracuse - Neighborhood and Business DevelopmentNew_CC_DISTCurrent Common Council District property is located inOnondaga County Board of ElectionsCTID_2020Census Tract ID (2020)U.S. Census BureauCTLAB_2020Census Tract Label (2020)U.S. Census BureauCT_2020Census Tract (2020)U.S. Census BureauSpecNhoodIs property located in a special Neighborhood historic preservation district? (1 = Yes; 0 or null = No)Syracuse-Onondaga County Planning Agency (SOCPA)InPDIs property located in preservation district? (1 = Yes; 0 or null = No)Syracuse-Onondaga County Planning Agency (SOCPA)PDNAMEPreservation District nameSyracuse-Onondaga County Planning Agency (SOCPA)ELECT_DISTElection district numberOnondaga County Board of ElectionsCITY_WARDCity ward numberOnondaga County Board of ElectionsCOUNTY_LEGOnondaga County Legislative District number (as of Dec 2022)Onondaga County Board of ElectionsNYS_ASSEMBNew York State Assembly District number (as of Dec 2022)Onondaga County Board of ElectionsNYS_SENATENew York State Senate District number (as of Dec 2022)Onondaga County Board of ElectionsUS_CONGRUnited States Congressional District numberOnondaga County Board of Elections

Composite map of Future Land Use. This is a pdf document.

Land Cover Map 2021 (LCM2021) is a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2021. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2021. Land cover maps describe the physical material on the surface of the country. For example grassland, woodland, rivers & lakes or man-made structures such as roads and buildingsThis is a 10 m Classified Pixel dataset, classified to create a single mosaic of national cover. Provenance and quality:UKCEH’s automated land cover classification algorithms generated the 10m classified pixels. Training data were automatically selected from stable land covers over the interval of 2017 to 2019. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.Land cover was validated by organising the pixel classification into a land parcel framework (the LCM2021 Classified Land Parcels product). The classified land parcels were compared to known land cover producing confusion matrix to determine overall and per class accuracy.View full metadata information and download the data at catalogue.ceh.ac.uk

Government Land Office maps (GLOs) are a result of the effort to survey all United States public lands before settlement. Starting in 1812 land was divided into square six mile blocks called townships, then subdivided into sections and ranges. Each subdivided area was surveyed and given its own map or GLO. During this process surveyors were required to indicate cultural resources such as roads and Indian trails and standardized symbols were used to represent geographic features. These GLOs are now maintained by the Bureau of Land Management as part of the official Land Status and Cadastral Survey records. As land was divided into parcels of individual ownership additional cadastral survey maps were created over time. For this reason there are often multiple GLOs or "cadastral survey maps" for one township / range, generally numbered one through four. For this seamless GLO layer, DAHP focused solely on the more historical GLOs which were usually listed as image number one or two for that specific township / range in the BLM Cadastral Survey records. In some cases no GLOs were available for review. Such areas included National Forest Lands, National Parks, Indian Reservations, and remote wilderness areas.

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq Map showing lot sizes broken down by typical sizes to qualify for certain developments

description: Parcels and Land Ownership dataset current as of unknown. This data set consists of digital map files containing parcel-level cadastral information obtained from property descriptions. Cadastral features contained in the data set include real property boundary lines, rights-of-way boundaries, property dimensions.; abstract: Parcels and Land Ownership dataset current as of unknown. This data set consists of digital map files containing parcel-level cadastral information obtained from property descriptions. Cadastral features contained in the data set include real property boundary lines, rights-of-way boundaries, property dimensions.

This is a web map service (WMS) for the 10-metre Land Cover Map 2023. The map presents the and surface classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats.UKCEH’s automated land cover algorithms classify 10 m pixels across the whole of UK. Training data were automatically selected from stable land covers over the interval of 2020 to 2022. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.Land cover was validated by organising the 10 m pixel classification into a land parcel framework (the LCM2023 classified land parcels product). The classified land parcels were compared to known land cover producing a confusion matrix to determine overall and per class accuracy.

This tile package shows land use by parcel according to state assessing codes

This dataset consists of the 1km raster, percentage target class version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 1km percentage product provides the percentage cover for each of 21 land cover classes for 1km x 1km pixels. This product contains one band per target habitat class (producing a 21 band image). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019.

[Metadata] Description: Agricultural Land Use Maps (ALUM) for islands of Kauai, Oahu, Maui, Molokai, Lanai and Hawaii as of 1978-1980. Sources: State Department of Agriculture; Hawaii Statewide GIS Program, Office of Planning. Note: August, 2018 - Corrected one incorrect record, removed coded value attribute domain.For more information on data sources and methodologies used, please refer to complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/alum.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, HI 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.