This EnviroAtlas data set depicts estimates for mean cash rent paid for land by farmers, sorted by county for irrigated cropland, non-irrigated cropland, and pasture by for most of the conterminous US. This data comes from national surveys which includes approximately 240,000 farms and applies to all crops. According to the USDA (U.S. Department of Agriculture) National Agricultural Statistics Service (NASS), these surveys do not include land rented for a share of the crop, on a fee per head, per pound of gain, by animal unit month (AUM), rented free of charge, or land that includes buildings such as barns. For each land use category with positive acres, respondents are given the option of reporting rent per acre or total dollars paid. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Value of farmland and buildings per acre, for Canada and the provinces at July 1 (in dollars).

New Zealand's average farm sale prices showed significant regional variations in the three months to November 2024. The price of farm property in the country was the highest in the Nelson/Marlborough/Tasman region as of November 2024, with an average sale price of around ******* New Zealand dollars per hectare. In comparison, in the Auckland region, the average farm sales price came to just over ****** dollars per hectare. A farming nation The agriculture industry is a major economic pillar of the country. The contribution to the nation’s GDP is valued in the billions of New Zealand dollars. Horticulture, livestock, and dairying are all important segments, and the commodities produced within them are exported across the globe. While sheep livestock numbers have declined, they still make up a large share of the country’s livestock population. Horticultural farming While New Zealand exports various horticultural products, including wine grapes, potatoes, and apples, it is perhaps best known for its kiwi fruit. Accordingly, the land area dedicated to kiwi fruit farming has continued to increase over the years. New Zealand’s leading horticultural product export destinations include Asia, Europe, and Australia.

These maps were compiled by the University of Sydney from Cumberland County Council maps, and were printed at the Lands Department (62.431).

They are annotated with the price per acre for industrial land and what services are available.

The scale is 1" = 3 miles.



(SR Map Nos.52686-87). 2 maps.

Note:
This description is extracted from Concise Guide to the State Archives of New South Wales, 3rd Edition 2000.

The Subdivision Map Act requires that agencies imposing fees have a general drainage plan for the fee area, a special fund for the fees and an equitable distribution of the fees prior to implementation. Since the District does not have land use authority, it cannot implement drainage fees directly. The District must therefore request that the County and/or local cities adopt drainage fees within their jurisdictions for the District. The District generally agrees to create the special funds for the fees and to prepare an ADP. The ADP is a document specifically prepared for the County and cities to adopt. The Area Drainage Plan is essentially the Master Drainage Plan with additional language supporting the costs and distribution of the fee within the plan area. To ensure the equitable distribution of fees, the ADP/MDP boundaries are generally based on watersheds. The total costs of facilities within the watershed are first calculated. The watershed area is then adjusted to discount publicly owned lands and areas on steep slopes not likely to develop. Finally, the total facility cost is divided by the revised watershed area to determine a per acre fee for the plan area. Due to State Law, the collection of drainage fees varies depending on the type of development. Developments falling under the Subdivision Map Act (those requiring a division of lands) pay fees on a per acre basis. Developments falling outside of the Subdivision Map Act (known as discretionary developments) can only be assessed fees based on their impacts to the watershed. The ADP Rules and Regulations state that these impacts can be related to the amount of impervious surface area that the development creates. Therefore, discretionary developments are charged not on a gross acreage basis, but on the total impervious acreage created by their development.

FIA Modeled Abundance:�This dataset portrays the live tree mean basal area (square feet per acre) of the species across the contiguous United States. The underlying data publication contains raster maps of live tree basal area for each tree species along with corresponding assessment data. An efficient approach for mapping multiple individual tree species over large spatial domains was used to develop these raster datasets. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-meter (m) pixel size for the contiguous United States. The approach uses the modeling techniques of k-nearest neighbors and canonical correspondence analysis, where model predictions are calculated using a weighting of nearest neighbors based on proximity in a feature space derived from the model. The approach also utilizes a stratification derived from the 2001 National Land-Cover Database tree canopy cover layer.�This data depicts current species abundance and distribution across the contiguous United States, modeled by using FIA field plot data. Although the absolute values associated with the maps differ from species to species, the highest values within each map are always associated with darker colors. The Little's Range Boundaries show the historical tree species ranges across North America. This is a digital representation of maps by Elbert L. Little, Jr., published between 1971 and 1977. These maps were based on botanical lists, forest surveys, field notes and herbarium specimens.Forest-type Groups:This dataset portrays the forest type group. Each group is a subset of the National Forest Type dataset which portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data.Harvest Growth:This data shows the percentage of timber that is harvested when compared to the total live volume, at a county-by-county level. Timber volume in forests is constantly in flux, and harvest plays an important role in shaping forests. While most counties have some timber harvest, harvest volumes represent low percentages of standing timber volume.Carbon Harvest:The Carbon Harvest raster dataset represents Mg of annual pulpwood harvested (carbon) by county, derived from the Forest Inventory Analysis in 2016.

Parcels and property data maintained and provided by Lee County Property Appraiser. This dataset includes condominium units. Property attribute data joined to parcel GIS layer by Lee County Government GIS.Projected coordinate system name: NAD_1983_StatePlane_Florida_West_FIPS_0902_FeetGeographic coordinate system name: GCS_North_American_1983

 Name
 Type
 Length
 Description


 STRAP
 String
 25
 17-digit Property ID (Section, Township, Range, Area, Block, Lot)


 BLOCK
 String
 10
 5-digit portion of STRAP (positions 9-13)


 LOT
 String
 8
 Last 4-digits of STRAP


 FOLIOID
 Double
 8
 Unique Property ID


 MAINTDATE
 Date
 8
 Date LeePA staff updated record


 MAINTWHO
 String
 20
 LeePA staff who updated record


 UPDATED
 Date
 8
 Data compilation date


 HIDE_STRAP
 String
 1
 Confidential parcel ownership


 TRSPARCEL
 String
 17
 Parcel ID sorted by Township, Range & Section


 DORCODE
 String
 2
 Department of Revenue property classification code


 CONDOTYPE
 String
 1
 Type of condominium: C (commercial) or R (residential)


 UNITOFMEAS
 String
 2
 Type of Unit of Measure (ex: AC=acre, LT=lot, FF=frontage in feet)


 NUMUNITS
 Double
 8
 Number of Land Units (units defined in UNITOFMEAS)


 FRONTAGE
 Integer
 4
 Road Frontage in Feet


 DEPTH
 Integer
 4
 Property Depth in Feet


 GISACRES
 Double
 8
 Total Computed Acres from GIS


 TAXINGDIST
 String
 3
 Taxing District of Property


 TAXDISTDES
 String
 60
 Taxing District Description


 FIREDIST
 String
 3
 Fire District of Property


 FIREDISTDE
 String
 60
 Fire District Description


 ZONING
 String
 10
 Zoning of Property


 ZONINGAREA
 String
 3
 Governing Area for Zoning


 LANDUSECOD
 SmallInteger
 2
 Land Use Code


 LANDUSEDES
 String
 60
 Land Use Description


 LANDISON
 String
 5
 BAY,CANAL,CREEK,GULF,LAKE,RIVER & GOLF


 SITEADDR
 String
 55
 Lee County Addressing/E911


 SITENUMBER
 String
 10
 Property Location - Street Number


 SITESTREET
 String
 40
 Street Name


 SITEUNIT
 String
 5
 Unit Number


 SITECITY
 String
 20
 City


 SITEZIP
 String
 5
 Zip Code


 JUST
 Double
 8
 Market Value


 ASSESSED
 Double
 8
 Building Value + Land Value


 TAXABLE
 Double
 8
 Taxable Value


 LAND
 Double
 8
 Land Value


 BUILDING
 Double
 8
 Building Value


 LXFV
 Double
 8
 Land Extra Feature Value


 BXFV
 Double
 8
 Building Extra Feature value


 NEWBUILT
 Double
 8
 New Construction Value


 AGAMOUNT
 Double
 8
 Agriculture Exemption Value


 DISAMOUNT
 Double
 8
 Disability Exemption Value


 HISTAMOUNT
 Double
 8
 Historical Exemption Value


 HSTDAMOUNT
 Double
 8
 Homestead Exemption Value


 SNRAMOUNT
 Double
 8
 Senior Exemption Value


 WHLYAMOUNT
 Double
 8
 Wholly Exemption Value


 WIDAMOUNT
 Double
 8
 Widow Exemption Value


 WIDRAMOUNT
 Double
 8
 Widower Exemption Value


 BLDGCOUNT
 SmallInteger
 2
 Total Number of Buildings on Parcel


 MINBUILTY
 SmallInteger
 2
 Oldest Building Built


 MAXBUILTY
 SmallInteger
 2
 Newest Building Built


 TOTALAREA
 Double
 8
 Total Building Area


 HEATEDAREA
 Double
 8
 Total Heated Area


 MAXSTORIES
 Double
 8
 Tallest Building on Parcel


 BEDROOMS
 Integer
 4
 Total Number of Bedrooms


 BATHROOMS
 Double
 8
 Total Number of Bathrooms / Not For Comm


 GARAGE
 String
 1
 Garage on Property 'Y'


 CARPORT
 String
 1
 Carport on Property 'Y'


 POOL
 String
 1
 Pool on Property 'Y'


 BOATDOCK
 String
 1
 Boat Dock on Property 'Y'


 SEAWALL
 String
 1
 Sea Wall on Property 'Y'


 NBLDGCOUNT
 SmallInteger
 2
 Total Number of New Buildings on ParcelTotal Number of New Buildings on Parcel


 NMINBUILTY
 SmallInteger
 2
 Oldest New Building Built


 NMAXBUILTY
 SmallInteger
 2
 Newest New Building Built


 NTOTALAREA
 Double
 8
 Total New Building Area


 NHEATEDARE
 Double
 8
 Total New Heated Area


 NMAXSTORIE
 Double
 8
 Tallest New Building on Parcel


 NBEDROOMS
 Integer
 4
 Total Number of New Bedrooms


 NBATHROOMS
 Double
 8
 Total Number of New Bathrooms/Not For Comm


 NGARAGE
 String
 1
 New Garage on Property 'Y'


 NCARPORT
 String
 1
 New Carport on Property 'Y'


 NPOOL
 String
 1
 New Pool on Property 'Y'


 NBOATDOCK
 String
 1
 New Boat Dock on Property 'Y'


 NSEAWALL
 String
 1
 New Sea Wall on Property 'Y'


 O_NAME
 String
 30
 Owner Name


 O_OTHERS
 String
 120
 Other Owners


 O_CAREOF
 String
 30
 In Care Of Line


 O_ADDR1
 String
 30
 Owner Mailing Address Line 1


 O_ADDR2
 String
 30
 Owner Mailing Address Line 2


 O_CITY
 String
 30
 Owner Mailing City


 O_STATE
 String
 2
 Owner Mailing State


 O_ZIP
 String
 9
 Owner Mailing Zip


 O_COUNTRY
 String
 30
 Owner Mailing Country


 S_1DATE
 Date
 8
 Most Current Sale Date > $100.00


 S_1AMOUNT
 Double
 8
 Sale Amount


 S_1VI
 String
 1
 Sale Vacant or Improved


 S_1TC
 String
 2
 Sale Transaction Code


 S_1TOC
 String
 2
 Sale Transaction Override Code


 S_1OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_2DATE
 Date
 8
 Previous Sale Date > $100.00


 S_2AMOUNT
 Double
 8
 Sale Amount


 S_2VI
 String
 1
 Sale Vacant or Improved


 S_2TC
 String
 2
 Sale Transaction Code


 S_2TOC
 String
 2
 Sale Transaction Override Code


 S_2OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_3DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_3AMOUNT
 Double
 8
 Sale Amount


 S_3VI
 String
 1
 Sale Vacant or Improved


 S_3TC
 String
 2
 Sale Transaction Code


 S_3TOC
 String
 2
 Sale Transaction Override Code


 S_3OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_4DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_4AMOUNT
 Double
 8
 Sale Amount


 S_4VI
 String
 1
 Sale Vacant or Improved


 S_4TC
 String
 2
 Sale Transaction Code


 S_4TOC
 String
 2
 Sale Transaction Override Code


 S_4OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 LEGAL
 String
 255
 Full Legal Description (On Deed)


 GARBDIST
 String
 3
 County Garbage Hauling Area


 GARBTYPE
 String
 1
 County Garbage Pick-up Type


 GARBCOMCAT
 String
 1
 County Garbage Commercial Category


 GARBHEADER
 String
 1
 Garbage Header Code


 GARBUNITS
 Double
 8
 Number of Garbage Units


 CREATEYEAR

Established in 1982, Government Code Section 65570 mandates FMMP to biennially report on the conversion of farmland and grazing land, and to provide maps and data to local government and the public. Other sections: Spatial Data Organization: Direct_Spatial_Reference_Method: Vector Point_and_Vector_Object_Information: SDTS_Terms_Description: SDTS_Point_and_Vector_Object_Type: G-polygon Point_and_Vector_Object_Count: Varies by Year Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Planar: Map_Projection: Map_Projection_Name:Albers Conical Equal Area Albers_Conical_Equal_Area: Albers Conical Equal Area Standard_Parallel: 34.000000 Standard_Parallel: 40.500000 Longitude_of_Central_Meridian: -120.000000 Latitude_of_Projection_Origin: 0.000000 False_Easting: 0.000000 False_Northing: -4000000.000000 Planar_Coordinate_Information: Planar_Coordinate_Encoding_Method: coordinate pair Coordinate_Representation: Abscissa_Resolution: 0.000256Ordinate_Resolution: 0.000256 Planar_Distance_Units: meters Geodetic_Model: Horizontal_Datum_Name: North American Datum of 1927 Ellipsoid_Name: Clarke 1866 Semi-major_Axis: 6378206.400000 Denominator_of_Flattening_Ratio: 294.978698 Vertical_Coordinate_System_Definition: Altitude_System_Definition: Altitude_Resolution: 0.000010 Altitude_Encoding_Method: Explicit elevation coordinate included with horizontal coordinates Entity_and_Attribute_Information: Detailed_Description: Entity_Type: Entity_Label: Important Farmland Categories Entity_Definition: Technical ratings of the soils and current land use information are combined to determine the appropriate map category. Definition_Source: Farmland Mapping and Monitoring Program Attribute: Attribute_Label: OBJECTID Attribute_Definition: Internal feature number. Attribute_Definition_Source: ESRI Attribute_Domain_Values: Unrepresentable_Domain: Sequential unique whole numbers that are automatically generated. Attribute: Attribute_Label: Shape Attribute_Definition: Feature geometry. Attribute_Definition_Source: ESRI Attribute_Domain_Values: Unrepresentable_Domain: Coordinates defining the features. Attribute: Attribute_Label: POLYGON_TY Attribute_Definition: Identifies the mapping categories used by the Farmland Mapping and Monitoring Program. Attribute_Definition_Source: Definitions were developed by the USDA-NRCS as part of their nationwide Land Inventory and Monitoring (LIM) system. Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: Prime Farmland (P) Enumerated_Domain_Value_Definition: Irrigated land with the best combination of physical and chemical features able to sustain long term production of agricultural crops. This land has the soil quality, growing season, and moisture supply needed to produce sustained high yields. Land must have been used for production of irrigated crops at some time during the four years prior to the mapping date. Domain Value Attribute: Enumerated_Domain: Enumerated_Domain_Value: Farmland of Statewide Importance (S) Enumerated_Domain_Value_Definition: Irrigated land similar to Prime Farmland that has a good combination of physical and chemical characteristics for the production of agricultural crops. This land has minor shortcomings, such as greater slopes or less ability to store soil moisture than Prime Farmland. Land must have been used for production of irrigated crops at some time during the four years prior to the mapping date. Domain Value Attribute: Enumerated_Domain: Enumerated_Domain_Value: Unique Farmland (U) Enumerated_Domain_Value_Definition: Lesser quality soils used for the production of the state's leading agricultural crops. This land is usually irrigated, but may include non-irrigated orchards or vineyards as found in some climatic zones in California. Land must have been cropped at some time during the four years prior to the mapping date. Domain Value Attribute: Enumerated_Domain: Enumerated_Domain_Value: Farmland of Local Importance (L) Enumerated_Domain_Value_Definition: Lands that do not qualify for the Prime, Statewide, or Unique designation but are considered Existing Agricultural Lands, or Potential Agricultural Lands, in the Agricultural Land Element of the County General Plan. Timberlands are excluded. Domain Value Attribute: Enumerated_Domain: Enumerated_Domain_Value: Grazing Land (G) Enumerated_Domain_Value_Definition: Land on which the existing vegetation is suited to the grazing of livestock. This category is used only in California and was developed in cooperation with the California Cattlemen's Association, University of California Cooperative Extension, and other groups interested in the extent of grazing activities. Domain Value Attribute: Enumerated_Domain: Enumerated_Domain_Value: Urban and Built-Up Land (D) Enumerated_Domain_Value_Definition: Urban and Built-Up land is occupied by structures with a building density of at least 1 unit to 1.5 acres, or approximately 6 structures to a 10-acre parcel. Common examples include residential, industrial, commercial, institutional facilities, cemeteries, airports, golf courses, sanitary landfills, sewage treatment, and water control structures. Domain Value Attribute: Enumerated_Domain: Enumerated_Domain_Value: Other Land (X) Enumerated_Domain_Value_Definition: Land which does not meet the criteria of any other category. Typical uses include low density rural development, heavily forested land, mined land, or government land with restrictions on use. Domain Value Attribute: Enumerated_Domain: Enumerated_Domain_Value: Water (W) Enumerated_Domain_Value_Definition: Water areas with an extent of at least 40 acres. Domain Value Attribute: Enumerated_Domain: Enumerated_Domain_Value: Area not mapped (Z) Enumerated_Domain_Value_Definition: Area which falls outside of the NRCS soil survey. Not mapped by the FMMP. Domain Value Attribute: Attribute: Attribute_Label: POLYGON_AC Attribute_Definition: The acreage of the polygon feature. Attribute_Definition_Source: Computer calculated. Attribute: Attribute_Label: COUNTY_NAM Attribute_Definition: County name identified by a three letter abbreviation. Attribute_Definition_Source: County abbreviations are in the text file located at the following url: ftp://consrv.ca.gov/pub/dlrp/FMMP/county_index.txt Attribute_Domain_Values: Unrepresentable_Domain: Coordinates defining the features. Attribute: Attribute_Label: UPD_YEAR Attribute_Definition: The year the data was captured. Attribute_Definition_Source: FMMP updates their data biennially. Attribute: Attribute_Label: SHAPE_LENG Attribute_Definition: Perimeter of the polygon feature in meters. Attribute_Definition_Source: Computer calculated. Attribute_Domain_Values: Unrepresentable_Domain: Positive real numbers that are automatically generated. Attribute: Attribute_Label: SHAPE_AREA Attribute_Definition: Area of feature in meters squared. Attribute_Definition_Source: Computer calculated. Attribute_Domain_Values: Unrepresentable_Domain: Positive real numbers that are automatically generated.

Parcels and property data maintained and provided by Lee County Property Appraiser are converted to points. Property attribute data joined to parcel GIS layer by Lee County Government GIS. This dataset is generally used in spatial analysis.Process description: Parcel polygons, condominium points and property data provided by the Lee County Property Appraiser are processed by Lee County's GIS Department using the following steps:Join property data to parcel polygons Join property data to condo pointsConvert parcel polygons to points using ESRI's ArcGIS tool "Feature to Point" and designate the "Source" field "P".Load Condominium points into this layer and designate the "Source" field "C". Add X/Y coordinates in Florida State Plane West, NAD 83, feet using the "Add X/Y" tool.Projected coordinate system name: NAD_1983_StatePlane_Florida_West_FIPS_0902_FeetGeographic coordinate system name: GCS_North_American_1983

 Name
 Type
 Length
 Description


 STRAP
 String
 25
 17-digit Property ID (Section, Township, Range, Area, Block, Lot)


 BLOCK
 String
 10
 5-digit portion of STRAP (positions 9-13)


 LOT
 String
 8
 Last 4-digits of STRAP


 FOLIOID
 Double
 8
 Unique Property ID


 MAINTDATE
 Date
 8
 Date LeePA staff updated record


 MAINTWHO
 String
 20
 LeePA staff who updated record


 UPDATED
 Date
 8
 Data compilation date


 HIDE_STRAP
 String
 1
 Confidential parcel ownership


 TRSPARCEL
 String
 17
 Parcel ID sorted by Township, Range & Section


 DORCODE
 String
 2
 Department of Revenue. See https://leepa.org/Docs/Codes/DOR_Code_List.pdf


 CONDOTYPE
 String
 1
 Type of condominium: C (commercial) or R (residential)


 UNITOFMEAS
 String
 2
 Type of Unit of Measure (ex: AC=acre, LT=lot, FF=frontage in feet)


 NUMUNITS
 Double
 8
 Number of Land Units (units defined in UNITOFMEAS)


 FRONTAGE
 Integer
 4
 Road Frontage in Feet


 DEPTH
 Integer
 4
 Property Depth in Feet


 GISACRES
 Double
 8
 Total Computed Acres from GIS


 TAXINGDIST
 String
 3
 Taxing District of Property


 TAXDISTDES
 String
 60
 Taxing District Description


 FIREDIST
 String
 3
 Fire District of Property


 FIREDISTDE
 String
 60
 Fire District Description


 ZONING
 String
 10
 Zoning of Property


 ZONINGAREA
 String
 3
 Governing Area for Zoning


 LANDUSECOD
 SmallInteger
 2
 Land Use Code


 LANDUSEDES
 String
 60
 Land Use Description


 LANDISON
 String
 5
 BAY,CANAL,CREEK,GULF,LAKE,RIVER & GOLF


 SITEADDR
 String
 55
 Lee County Addressing/E911


 SITENUMBER
 String
 10
 Property Location - Street Number


 SITESTREET
 String
 40
 Street Name


 SITEUNIT
 String
 5
 Unit Number


 SITECITY
 String
 20
 City


 SITEZIP
 String
 5
 Zip Code


 JUST
 Double
 8
 Market Value


 ASSESSED
 Double
 8
 Building Value + Land Value


 TAXABLE
 Double
 8
 Taxable Value


 LAND
 Double
 8
 Land Value


 BUILDING
 Double
 8
 Building Value


 LXFV
 Double
 8
 Land Extra Feature Value


 BXFV
 Double
 8
 Building Extra Feature value


 NEWBUILT
 Double
 8
 New Construction Value


 AGAMOUNT
 Double
 8
 Agriculture Exemption Value


 DISAMOUNT
 Double
 8
 Disability Exemption Value


 HISTAMOUNT
 Double
 8
 Historical Exemption Value


 HSTDAMOUNT
 Double
 8
 Homestead Exemption Value


 SNRAMOUNT
 Double
 8
 Senior Exemption Value


 WHLYAMOUNT
 Double
 8
 Wholly Exemption Value


 WIDAMOUNT
 Double
 8
 Widow Exemption Value


 WIDRAMOUNT
 Double
 8
 Widower Exemption Value


 BLDGCOUNT
 SmallInteger
 2
 Total Number of Buildings on Parcel


 MINBUILTY
 SmallInteger
 2
 Oldest Building Built


 MAXBUILTY
 SmallInteger
 2
 Newest Building Built


 TOTALAREA
 Double
 8
 Total Building Area


 HEATEDAREA
 Double
 8
 Total Heated Area


 MAXSTORIES
 Double
 8
 Tallest Building on Parcel


 BEDROOMS
 Integer
 4
 Total Number of Bedrooms


 BATHROOMS
 Double
 8
 Total Number of Bathrooms / Not For Comm


 GARAGE
 String
 1
 Garage on Property 'Y'


 CARPORT
 String
 1
 Carport on Property 'Y'


 POOL
 String
 1
 Pool on Property 'Y'


 BOATDOCK
 String
 1
 Boat Dock on Property 'Y'


 SEAWALL
 String
 1
 Sea Wall on Property 'Y'


 NBLDGCOUNT
 SmallInteger
 2
 Total Number of New Buildings on ParcelTotal Number of New Buildings on Parcel


 NMINBUILTY
 SmallInteger
 2
 Oldest New Building Built


 NMAXBUILTY
 SmallInteger
 2
 Newest New Building Built


 NTOTALAREA
 Double
 8
 Total New Building Area


 NHEATEDARE
 Double
 8
 Total New Heated Area


 NMAXSTORIE
 Double
 8
 Tallest New Building on Parcel


 NBEDROOMS
 Integer
 4
 Total Number of New Bedrooms


 NBATHROOMS
 Double
 8
 Total Number of New Bathrooms/Not For Comm


 NGARAGE
 String
 1
 New Garage on Property 'Y'


 NCARPORT
 String
 1
 New Carport on Property 'Y'


 NPOOL
 String
 1
 New Pool on Property 'Y'


 NBOATDOCK
 String
 1
 New Boat Dock on Property 'Y'


 NSEAWALL
 String
 1
 New Sea Wall on Property 'Y'


 O_NAME
 String
 30
 Owner Name


 O_OTHERS
 String
 120
 Other Owners


 O_CAREOF
 String
 30
 In Care Of Line


 O_ADDR1
 String
 30
 Owner Mailing Address Line 1


 O_ADDR2
 String
 30
 Owner Mailing Address Line 2


 O_CITY
 String
 30
 Owner Mailing City


 O_STATE
 String
 2
 Owner Mailing State


 O_ZIP
 String
 9
 Owner Mailing Zip


 O_COUNTRY
 String
 30
 Owner Mailing Country


 S_1DATE
 Date
 8
 Most Current Sale Date > $100.00


 S_1AMOUNT
 Double
 8
 Sale Amount


 S_1VI
 String
 1
 Sale Vacant or Improved


 S_1TC
 String
 2
 Sale Transaction Code


 S_1TOC
 String
 2
 Sale Transaction Override Code


 S_1OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_2DATE
 Date
 8
 Previous Sale Date > $100.00


 S_2AMOUNT
 Double
 8
 Sale Amount


 S_2VI
 String
 1
 Sale Vacant or Improved


 S_2TC
 String
 2
 Sale Transaction Code


 S_2TOC
 String
 2
 Sale Transaction Override Code


 S_2OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_3DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_3AMOUNT
 Double
 8
 Sale Amount


 S_3VI
 String
 1
 Sale Vacant or Improved


 S_3TC
 String
 2
 Sale Transaction Code


 S_3TOC
 String
 2
 Sale Transaction Override Code


 S_3OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_4DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_4AMOUNT
 Double
 8
 Sale Amount


 S_4VI
 String
 1
 Sale Vacant or Improved


 S_4TC
 String
 2
 Sale Transaction Code


 S_4TOC
 String
 2
 Sale Transaction Override Code


 S_4OR_NUM
 String
 13

The Visual Resource Inventory Classes Polygon is a component of the Visual Resources Inventory (VRI) and includes information needed for inventorying for visual values on BLM-managed public lands according to policy direction found in Manual 8400 and related Handbook 8410-1. Current policy requires that every acre of BLM land be inventoried for visual values and be assigned one of four VRI classes (Class I, II, III, or IV). Class I is reserved for those areas where a management decision has been made previously to maintain a natural landscape. This includes areas such as national wilderness areas, the wild section of national wild and scenic rivers, and other congressionally and administratively designated areas where decisions have been made to preserve a natural landscape. The inventory classes provide the basis for considering visual values in the resource management planning (RMP) process and constitute the current state of visual resource values as part of the affected environment sections of environmental analyses. Particularly, this data pertains Visual Resource National, State, District and Field Office leads and any group, program, or organization that is involved with surface disturbance activities or visually altering activities, including: Land Use Planners, Realty Specialists, Recreation Planners, Natural Resource Specialists, Landscape Architects, Cultural Resource Specialists, Fluid Minerals and Renewable Energy. This dataset is a subset of the official national dataset, containing features and attributes intended for public release and has been optimized for online map service performance. The Schema Workbook represents the official national dataset from which this dataset was derived.

County-Level Pesticide Use Estimates - 1993

The NAWQA Pesticide National Synthesis Project, which began in 1992, is a national-scale assessment of the occurrence and behavior of pesticides in streams and ground water of the United States and the potential for pesticides to adversely affect drinking-water supplies or aquatic ecosystems.

The tables, maps, and graphs provided by Pesticide National Synthesis Project provide estimates of agricultural pesticide use in the conterminous United States for numerous pesticides. The tables report agricultural pesticide use at the county level and are based on farm surveys of pesticide use and estimates of harvested crop acres. The maps show agricultural pesticide use on a finer scale and are created by allocating the county-level estimates to agricultural land within each county. A graph accompanies each map and shows annual national use by major crop for the mapped pesticide for each year.

These pesticide-use estimates are suitable for evaluating national and regional patterns and trends of annual pesticide use. The reliability of estimates, however, generally decreases with scale and these estimates and maps are not intended for detailed evaluations, such as comparing within or between specific individual counties.

About The Pesticide National Synthesis Project

Estimated Annual Agricultural Pesticide Use

How the estimates and maps are made

For all States except California, proprietary farm survey pesticide-use data are aggregated and reported at the multi-county Crop Reporting District (CRD) level. Harvested-crop acreage data by county from the U.S. Department of Agriculture Census of Agriculture are used to calculate the median pesticide-by- crop use rates for each crop in each CRD. These rates are applied to the harvested acreage of each crop in a county to obtain pesticide-use estimates at a county level. Estimates for California are obtained from annual Department of Pesticide Regulation Pesticide Use Reports (California Department of Pesticide Regulation). Methods for generating county-level pesticide-use estimates are described in Estimation of Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 1992–2009 (Thelin and Stone, 2013) and Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2008-12 (Baker and Stone, 2015).

Maps are created by allocating county-level use estimates to agricultural land within each county based on land classifications defined in the National Land Cover Database 2011 (NLCD11) (Jin and others, 2013; NLCD 2011 Data Download). The NLCD11 is used for the entire period of record because at a national level agricultural land use has not changed much during that time frame, and by using a single snapshot in time, changes in pesticide use are not obscured by changes in land use. NLCD11 Planted/Cultivated categories 81 (Pasture/Hay) and 82 (Cultivated Crops) were combined to differentiate agricultural land from non-agricultural land. The NLCD11 was then generalized to 1 square kilometer cell size and the percentage of agricultural land for each cell was calculated. The proportion of county agricultural land included in each 1 square kilometer cell was multiplied by the total county use for each pesticide to calculate the proportional amount of use allocated to each cell. To display pesticide use on the annual maps for each compound, the range of all of the cell values nationwide for the entire period are divided into quartiles and a color-coded map is generated for each year based on these quartiles. The quartile classes are converted to pounds per square mile.

Estimates of Pesticide Use – EPest-low and EPest-high methods

For all States except California, two different methods, EPest-low and EPest- high, are used to estimate a range of pesticide use. Both EPest-low and EPest-high methods incorporate proprietary surveyed rates for Crop Reporting Districts (CRDs), but EPest-low and EPest-high estimates differ in how they treat situations when a CRD was surveyed and pesticide use was not reported for a particular crop present in the CRD. In these situations, EPest-low assumes zero use in the CRD for that pesticide-by- crop combination. EPest-high, however, treats the unreported use for that pesticide-by- crop combination in the CRD as missing data. In this case, pesticide-by- crop use rates from neighboring CRDs or CRDs within the same region are used to estimate the pesticide-by- crop EPest-high rate for the CRD.

State-based restrictions on pesticide use were not incorporated into EPest- high or EPest-low estimates. However, EPest-low estimates are more likely to reflect these restrictions than EPest-high estimates. Users of the maps and data should consult the methods presented in Thelin and Stone (2013) and Baker and Stone (2015) to understand the details of how both estimates were determined. Maps are provided for both EPest-low and EPest-high estimates.

Use estimates for California are obtained from annual California Department of Pesticide Regulation pesticide use reports. Because these reports provide county-level use estimates, they are incorporated into the data without further processing and low and high rates are the same for counties in California. California county data are appended after the estimation process is completed for the rest of the Nation.

Pesticide Use-Trend Graphs by Crop

Graphs showing annual use by crop for each pesticide are created by summing the national pesticide use for each compound, for each crop or combination of crops. Combined crops are Pasture and Hay (cropland for pasture, fallow and idle cropland, pastureland, and other hay); Alfalfa; Orchards and grapes (stone fruit trees, citrus, nut trees, apples, pears, and grapevines); Vegetables and fruit (all vegetables and non-orchard fruit, including beans, peas, greens, berries, and melons); and Other (sorghum, non-wheat grains, tobacco, peanuts, sugarcane, sugarbeets, and other miscellaneous crops). The relations of graphed crops and combinations of crops to individual Epest Crop Names are shown in the following table. State-by crop estimates are available in tabular format.

Applications and limitations

Pesticide-use estimates from this study are suitable for making national, regional, and watershed estimates of annual pesticide use; however, the reliability of these estimates generally decreases with scale. For example, detailed interpretation of where and how much use occurs within a county is not appropriate. Although county-level estimates were used to create the maps and are provided in the dataset, it is important to understand that surveyed pesticide-by- crop use was not available for all CRDs and, therefore, extrapolation methods were used to estimate pesticide use for some counties. Moreover, surveyed pesticide-by- crop use may not reflect all agricultural use on all crops grown. In addition, State-based restrictions on pesticide use were not incorporated into EPest-high or EPest-low estimates. EPest-low estimates are more likely to reflect these restrictions than EPest- high estimates. With these caveats in mind, including other details discussed in Thelin and Stone (2013) and Baker and Stone (2015), the maps, graphs, and associated county-level use data are critical information for water- quality models and provide a comprehensive graphical overview of the geographic distribution and trends in agricultural pesticide use in the conterminous United States.

References

• Baker, N.T., and Stone, W.W., 2015, Estimated annual agricultural pesticide use for counties of the conterminous United States, 2008-12: U.S. Geological Survey Data Series 907, 9 p., http://dx.doi.org/10.3133/ds907.
• California Department of Pesticide Regulation, Variously dated, Pesticide use reporting: California Department of Pesticide Regulation pesticide use reporting (PUR) database, at http://www.cdpr.ca.gov/docs/pur/purmain.htm.
• Jin, S., Yang, L., Danielson, P., Homer, C., Fry, J., and Xian, G. 2013. A comprehensive change detection method for updating the National Land Cover Database to circa 2011. Remote Sensing of Environment, 132: 159-175.
• Thelin, G.P., and Stone, W.W., 2013, Estimation of annual agricultural pesticide use for counties of the conterminous United States, 1992–2009: U.S. Geological Survey Scientific Investigations Report 2013-5009, 54 p.
• U.S. Department of Agriculture, 2014, State and county data, Geographic area series parts 1–50, AC–12–A–1—AC–12–A–50: U.S. Department of Agriculture 2012 Census of Agriculture, v. 1, at http://www.agcensus.usda.gov/Publications/2012

References and Resources:

• 1993 County-Level Pesticide Use Estimates
• Estimated Annual Agricultural Pesticide Use - County Level

The Nature Conservancy (TNC) and Stanford University contracted Aerial Information Systems, Inc. to develop a 2005 and 2012 Anderson Level II terrestrial Land Use/Land Cover map for a portion of the Salinas Valley in Monterey County and portions of several valleys in the greater Pajaro River and San Benito River watershed in San Benito, Santa Clara, and Santa Cruz Counties, to support research and future modeling efforts in the area.

We are also including a 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). This Excel file can be downloaded HERE, and does not contain the latitude and longitude information.Data Dictionary: Attribute Label Definition Source

TAX_ID Unique 26 character property tax identification number Onondaga County Planning

PRINTKEY Abbreviated tax identification number (section-block-lot) Onondaga County Planning

ADDRESSNUM Property’s physical street address Onondaga County Planning

ADDRESSNAM Property’s physical street name Onondaga County Planning

LAT Latitude Onondaga County Planning

LONG Longitude Onondaga County Planning

TAX_ID_1 City Tax ID number (26 digit number used for parcel mapping) City of Syracuse - Assessment

SBL Property Tax Map Number (Section, Block, Lot) City of Syracuse - Assessment

PNUMBR Property Number (10 digit number) City of Syracuse - Assessment

StNum Parcel street number City of Syracuse - Assessment

StName Parcel street name City of Syracuse - Assessment

FullAddress Street number and street name City of Syracuse - Assessment

Zip Parcel zip code City of Syracuse - Assessment

desc_1 Lot description including dimensions City of Syracuse - Assessment

desc_2 Lot description including dimensions City of Syracuse - Assessment

desc_3 Lot description including dimensions City of Syracuse - Assessment

SHAPE_IND

City of Syracuse - Assessment

LUC_parcel New 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.htm City of Syracuse - Assessment

LU_parcel New York State property type classification name City of Syracuse - Assessment

LUCat_Old Legacy land use category that corresponds to the overarching NYS category, i.e. all 400s = commercial, all 300s = vacant land, etc. NA

land_av Land assessed value City of Syracuse - Assessment

total_av Full assessed value City of Syracuse - Assessment

Owner Property owner name (First, Initial, Last, Suffix) City of Syracuse - Assessment

Add1_OwnPOBox Property owner mailing address (PO Box) City of Syracuse - Assessment

Add2_OwnStAdd Property owner mailing address (street number, street name, street direction) City of Syracuse - Assessment

Add3_OwnUnitInfo Property owner mailing address unit info (unit name, unit number) City of Syracuse - Assessment

Add4_OwnCityStateZip Property owner mailing address (city, state or country, zip code) City of Syracuse - Assessment

FRONT Front footage for square or rectangular shaped lots and the effective front feet on irregularly shaped lots in feet City of Syracuse - Assessment

DEPTH Actual depth of rectangular shaped lots in feet (irregular lots are usually measured in acres or square feet) City of Syracuse - Assessment

ACRES Number of acres (where values were 0, acreage calculated as FRONT*DEPTH)/43560) City of Syracuse - Assessment

yr_built Year 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 - Assessment

n_ResUnits Number of residential units NA - Calculated field

IPSVacant Is it a vacant structure? ("Commercial" or "Residential" = Yes; null = No) City of Syracuse - Division of Code Enforcement

IPS_Condition Property Condition Score assigned to vacant properties by housing inspectors during routine vacant inspections (1 = Worst; 5 = Best) City of Syracuse - Division of Code Enforcement

NREligible National Register of Historic Places Eligible ("NR Eligible (SHPO)," or "NR Listed") City of Syracuse - Neighborhood and Business Development

LPSS Locally Protected Site Status ("Eligible/Architecturally Significant" or "Local Protected Site or Local District") City of Syracuse - Neighborhood and Business Development

WTR_ACTIVE Water activity code ("I" = Inactive; "A" = Active) City of Syracuse - Water

RNI Is property located in Resurgent Neighborhood Initiative (RNI) Area? (1 = Yes; 0 = No) City of Syracuse - Neighborhood and Business Development

DPW_Quad Geographic 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 Works

TNT_NAME TNT Sector property is located in City of Syracuse - Neighborhood and Business Development

NHOOD City Neighborhood Syracuse-Onondaga County Planning Agency (SOCPA)

NRSA Is property located in Neighborhood Revitilization Strategy Area (NRSA)? (1 = Yes; 0 = No) City of Syracuse - Neighborhood and Business Development

DOCE_Area Geographic boundary use to assign Division of Code Enforcement cases City of Syracuse - Neighborhood and Business Development

ZONE_DIST_PREV Former zoning district code Syracuse-Onondaga County Planning Agency (SOCPA)

REZONE ReZone designation (adopted June 2023) City of Syracuse - Neighborhood and Business Development

New_CC_DIST Current Common Council District property is located in Onondaga County Board of Elections

CTID_2020 Census Tract ID (2020) U.S. Census Bureau

CTLAB_2020 Census Tract Label (2020) U.S. Census Bureau

CT_2020 Census Tract (2020) U.S. Census Bureau

SpecNhood Is property located in a special Neighborhood historic preservation district? (1 = Yes; 0 or null = No) Syracuse-Onondaga County Planning Agency (SOCPA)

InPD Is property located in preservation district? (1 = Yes; 0 or null = No) Syracuse-Onondaga County Planning Agency (SOCPA)

PDNAME Preservation District name Syracuse-Onondaga County Planning Agency (SOCPA)

ELECT_DIST Election district number Onondaga County Board of Elections

CITY_WARD City ward number Onondaga County Board of Elections

COUNTY_LEG Onondaga County Legislative District number (as of Dec 2022) Onondaga County Board of Elections

NYS_ASSEMB New York State Assembly District number (as of Dec 2022) Onondaga County Board of Elections

NYS_SENATE New York State Senate District number (as of Dec 2022) Onondaga County Board of Elections

US_CONGR United States Congressional District number Onondaga County Board of Elections

Dataset Contact InformationOrganization: Neighborhood & Business DevelopmentPosition:Data Program ManagerCity:Syracuse, NYE-Mail Address:opendata@syrgov.netPlease note there is a data quality issue in this iteration with the preservation district (“InPD,” “PDNAME”) and special neighborhood historic district (“SpecNhood”) fields erroneously showing null results for all parcels.

This polygon shapefile represents land use and land cover for the Pajaro River and San Benito River Watershed in San Benito, Santa Clara, and Santa Cruz counties of California for 2005. This shapefile was extracted from a generalized land use/land cover database of the Salinas-Pajaro region. Map unit categories were based on a modified Anderson Level II hierarchy. Mapping generally adhered to a 0.5 acre Minimum Mapping Unit (MMU) for riparian and agriculture types and 1 acre MMU for all upland, urban, or other land use types. Vegetation percent cover classes were assigned to the tree and shrub layers for each stand. Herbaceous vegetation was not assigned a cover class. All density values are measured in absolute cover, not relative cover. If tree cover is equal to or greater than 40% then the shrub cover is assigned a Not Assessed value of 9. The minimum mapping unit (MMU) resolution size of the land use/land cover polygons is twofold. In the intense agricultural region and for wetland and riparian areas the polygons have a 0.5 acre MMU. In the remainder of the study area, composed of non-agricultural areas, upland vegetation, and urban areas, the MMU is 1 acre. For thin linear-shaped polygons the MMU for width is one half the width of a full MMU square. Exceptions to the MMU guidance are noted in further criteria below. Because of the agricultural emphasis of the project, large urban developed areas, such as cities, towns, and villages, were not typically further subdivided other than for agricultural uses within their extents. The MMU size for these agricultural uses within urban areas is 0.5 acres. As noted above, the study area overlaps with the 2005 mapping of the Salinas River and San Benito river major riparian corridors that Aerial Information Systems, Inc. conducted for the Nature Conservancy. The MMU for the original projects was <0.5 acres. Where those units had not changed for 2005 and 2012 mapping, the map units were kept at the original polygon size. The 0.5 acre MMU is used for new mapping of riparian and wetland map units. Other Mapping Criteria includes photo interpretation of land cover is based on state-wide criteria for vegetation mapping.

This TNC Lands spatial dataset represents the lands and waters in which The Nature Conservancy (TNC) currently has, or historically had, an interest, legal or otherwise in Wyoming. The system of record for TNC Lands is the Legal Records Management (LRM) system, which is TNC’s database for all TNC land transactions.TNC properties should not be considered open to the public unless specifically designated as being so. TNC may change the access status at any time at its sole discretion. It's recommended to visit preserve-specific websites or contact the organization operating the preserve before any planned visit for the latest conditions, notices, and closures. TNC prohibits redistribution or display of the data in maps or online in any way that misleadingly implies such lands are universally open to the public.The types of current land interests represented in the TNC Lands data include: Fields and Attributes included in the public dataset:Field NameField DefinitionAttributesAttribute Definitions Public NameThe name of the tract that The Nature Conservancy (TNC) Business Unit (BU) uses for public audiences.Public name of tract if applicableN/A TNC Primary InterestThe primary interest held by The Nature Conservancy (TNC) on the tractFee OwnershipProperties where TNC currently holds fee-title or exclusive rights and control over real estate. Fee Ownership can include TNC Nature Preserves, managed areas, and properties that are held for future transfer. Conservation EasementProperties on which TNC holds a conservation easement, which is a legally binding agreement restricting the use of real property for conservation purposes (e.g., no development). The easement may additionally provide the holder (TNC) with affirmative rights, such as the rights to monitor species or to manage the land. It may run forever or for an expressed term of years. Deed RestrictionProperties where TNC holds a deed restriction, which is a provision placed in a deed restricting or limiting the use of the property in some manner (e.g., if a property goes up for sale, TNC gets the first option). TransferProperties where TNC historically had a legal interest (fee or easement), then subsequently transferred the interest to a conservation partner. AssistProperties where TNC assisted another agency/entity in protecting. Management Lease or AgreementAn agreement between two parties whereby one party allows the other to use their property for a certain period of time in exchange for a periodic fee. Grazing Lease or PermitA grazing lease or permit held by The Nature Conservancy Right of WayAn access easement or agreement held by The Nature Conservancy. OtherAnother real estate interest or legal agreement held by The Nature Conservancy Fee OwnerThe name of the organization serving as fee owner of the tract, or "Private Land Owner" if the owner is a private party. If The Nature Conservancy (TNC) primary interest is a "Transfer" or "Assist", then this is the fee owner at the time of the transaction.Fee Owner NameN/A Fee Org TypeThe type of organization(s) that hold(s) fee ownership. Chosen from a list of accepted values.Organization Types for Fee OwnershipFED:Federal, TRIB:American Indian Lands, STAT:State,DIST:Regional Agency Special District, LOC:Local Government, NGO:Non-Governmental Organization, PVT:Private, JNT:Joint, UNK:Unknown, TERR:Territorial, DESG:Designation Other Interest HolderThe name of the organization(s) that hold(s) a different interest in the tract, besides fee ownership or TNC Primary Interest. This may include TNC if the Other Interest is held or co-held by TNC. Multiple interest holders should be separated by a semicolon (;).Other Interest Holder NameN/A Other Interest Org TypeThe type of organization(s) that hold(s) a different interest in the tract, besides fee ownership. This may include TNC if the Other Interest is held or co-held by TNC. Chosen from a list of accepted values.Organization Types for interest holders:FED:Federal, TRIB:American Indian Lands, STAT:State,DIST:Regional Agency Special District, LOC:Local Government, NGO:Non-Governmental Organization, PVT:Private, JNT:Joint, UNK:Unknown, TERR:Territorial, DESG:Designation Other Interest TypeThe other interest type held on the tract. Chosen from a list of accepted values.​Access Right of Way; Conservation Easement; Co-held Conservation Easement; Deed Restriction; Co-held Deed Restriction; Fee Ownership; Co-held Fee Ownership; Grazing Lease or Permit; Life Estate; Management Lease or Agreement; Timber Lease or Agreement; OtherN/A Preserve NameThe name of The Nature Conservancy (TNC) preserve that the tract is a part of, this may be the same name as the as the "Public Name" for the tract.Preserve Name if applicableN/APublic AccessThe level of public access allowed on the tract.Open AccessAccess is encouraged on the tract, trails are maintained, signage is abundant, and parking is available. The tract may include regular hours of availability.Open with Limited AccessThere are no special requirements for public access to the tract, the tract may include regular hours of availability with limited amenities.Restricted AccessThe tract requires a special permit from the owner for access, a registration permit on public land, or has highly variable times or conditions to use.Closed AccessNo public access is allowed on the tract.UnknownAccess information for the tract is not currently available.Gap CategoryThe Gap Analysis Project (GAP) code for the tract. Gap Analysis is the science of determining how well we are protecting common plants and animals. Developing the data and tools to support that science is the mission of the Gap Analysis Project (GAP) at the US Geological Survey. See their website for more information, linked in the field name.1 - Permanent Protection for BiodiversityPermanent Protection for Biodiversity2 - Permanent Protection to Maintain a Primarily Natural StatePermanent Protection to Maintain a Primarily Natural State3 - Permanently Secured for Multiple Uses and in natural coverPermanently Secured for Multiple Uses and in natural cover39 - Permanently Secured and in agriculture or maintained grass coverPermanently Secured and in agriculture or maintained grass cover4 - UnsecuredUnsecured (temporary easements lands and/or municipal lands that are already developed (schools, golf course, soccer fields, ball fields)9 - UnknownUnknownProtected AcresThe planar area of the tract polygon in acres, calculated by the TNC Lands geographic information system (GIS).Total geodesic area of polygon in acresProjection: WGS 1984 Web Mercator Auxiliary SphereOriginal Protection DateThe original protection date for the tract, from the Land Resource Management (LRM) system record.Original protection dateN/AStateThe state within the United States of America or the Canadian province where the tract is located.Chosen from a list of state names.N/ACountryThe name of the country where the tract is located.Chosen from a list of countries.N/ADivisionThe name of the TNC North America Region Division where the tract is located. Chosen from a list of TNC North America DivisionsN/A

This polygon shapefile represents land use and land cover for additional sites within the Pajaro River and San Benito River Watershed in San Benito, Santa Clara, and Santa Cruz counties of California for 2005. This shapefile was extracted from a generalized land use/land cover database of the Salinas-Pajaro region. Map unit categories were based on a modified Anderson Level II hierarchy. Mapping generally adhered to a 0.5 acre Minimum Mapping Unit (MMU) for riparian and agriculture types and 1 acre MMU for all upland, urban, or other land use types. Vegetation percent cover classes were assigned to the tree and shrub layers for each stand. Herbaceous vegetation was not assigned a cover class. All density values are measured in absolute cover, not relative cover. If tree cover is equal to or greater than 40% then the shrub cover is assigned a Not Assessed value of 9. The minimum mapping unit resolution size of the land use/land cover polygons is twofold. In the intense agricultural region and for wetland and riparian areas the polygons have a 0.5 acre MMU. In the remainder of the study area, composed of non-agricultural areas, upland vegetation, and urban areas, the MMU is 1 acre. For thin linear-shaped polygons the MMU for width is one half the width of a full MMU square. Exceptions to the MMU guidance are noted in further criteria below. Because of the agricultural emphasis of the project, large urban developed areas, such as cities, towns, and villages, were not typically further subdivided other than for agricultural uses within their extents. The MMU size for these agricultural uses within urban areas is 0.5 acres. As noted above, the study area overlaps with the 2005 mapping of the Salinas River and San Benito river major riparian corridors that Aerial Information Systems, Inc. conducted for the Nature Conservancy. The MMU for the original projects was <0.5 acres. Where those units had not changed for 2005 and 2012 mapping, the map units were kept at the original polygon size. The 0.5 acre MMU is used for new mapping of riparian and wetland map units. Other Mapping Criteria includes photo interpretation of land cover is based on state-wide criteria for vegetation mapping.

Data Dictionary:We are also including a 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 2024). This Excel file can be downloaded [HERE], and does not contain latitude and longitude information. Attribute Label Definition Source

TAX_ID Unique 26 character property tax identification number Onondaga County Planning

SHAPE_Leng Shape length NA - Calculated field

SHAPE_Area Shape area NA - Calculated field

PRINTKEY Abbreviated tax identification number (section-block-lot) Onondaga County Planning

ADDRESSNUM Property’s physical street address Onondaga County Planning

ADDRESSNAM Property’s physical street name Onondaga County Planning

TAX_ID City Tax ID number (26 digit number used for parcel mapping) City of Syracuse - Assessment

SBL Property Tax Map Number (Section, Block, Lot) City of Syracuse - Assessment

PNUMBR Property Number (10 digit number) City of Syracuse - Assessment

StNum Parcel street number City of Syracuse - Assessment

StName Parcel street name City of Syracuse - Assessment

FullAddress Street number and street name City of Syracuse - Assessment

Zip Parcel zip code City of Syracuse - Assessment

desc_1 Lot description including dimensions City of Syracuse - Assessment

desc_2 Lot description including dimensions City of Syracuse - Assessment

desc_3 Lot description including dimensions City of Syracuse - Assessment

SHAPE_IND

City of Syracuse - Assessment

LUC_parcel New 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.htm City of Syracuse - Assessment

LU_parcel New York State property type classification name City of Syracuse - Assessment

LUCat_Old Legacy land use category that corresponds to the overarching NYS category, i.e. all 400s = commercial, all 300s = vacant land, etc. NA

land_av Land assessed value City of Syracuse - Assessment

total_av Full assessed value City of Syracuse - Assessment

Owner Property owner name (First, Initial, Last, Suffix) City of Syracuse - Assessment

Add1_OwnPOBox Property owner mailing address (PO Box) City of Syracuse - Assessment

Add2_OwnStAdd Property owner mailing address (street number, street name, street direction) City of Syracuse - Assessment

Add3_OwnUnitInfo Property owner mailing address unit info (unit name, unit number) City of Syracuse - Assessment

Add4_OwnCityStateZip Property owner mailing address (city, state or country, zip code) City of Syracuse - Assessment

FRONT Front footage for square or rectangular shaped lots and the effective front feet on irregularly shaped lots in feet City of Syracuse - Assessment

DEPTH Actual depth of rectangular shaped lots in feet (irregular lots are usually measured in acres or square feet) City of Syracuse - Assessment

ACRES Number of acres (where values were 0, acreage calculated as FRONT*DEPTH)/43560) City of Syracuse - Assessment

yr_built Year 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 - Assessment

n_ResUnits Number of residential units NA - Calculated field

IPSVacant Is it a vacant structure? ("Commercial" or "Residential" = Yes; null = No) City of Syracuse - Division of Code Enforcement

IPS_Condition Property Condition Score assigned to vacant properties by housing inspectors during routine vacant inspections (1 = Worst; 5 = Best) City of Syracuse - Division of Code Enforcement

NREligible National Register of Historic Places Eligible ("NR Eligible (SHPO)," or "NR Listed") City of Syracuse - Neighborhood and Business Development

LPSS Locally Protected Site Status ("Eligible/Architecturally Significant" or "Local Protected Site or Local District") City of Syracuse - Neighborhood and Business Development

WTR_ACTIVE Water activity code ("I" = Inactive; "A" = Active) City of Syracuse - Water

RNI Is property located in Resurgent Neighborhood Initiative (RNI) Area? (1 = Yes; 0 = No) City of Syracuse - Neighborhood and Business Development

DPW_Quad Geographic 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 Works

DPW_Sani DPW sanitation trash and recycling pick-up day (trash service weekly, recycling biweekly) City of Syracuse - Department of Public Works

DPW_Recycle DPW recycling biweekly pick-up group (either Week A or Week B), collection occurs every other week City of Syracuse - Department of Public Works

TNT_NAME TNT Sector property is located in City of Syracuse - Neighborhood and Business Development

NHOOD City Neighborhood Syracuse-Onondaga County Planning Agency (SOCPA)

NRSA Is property located in Neighborhood Revitilization Strategy Area (NRSA)? (1 = Yes; 0 = No) City of Syracuse - Neighborhood and Business Development

DOCE_Insp1 Geographic boundary use to assign Division of Code Enforcement cases for housing inspectors City of Syracuse - Division of Code Enforcement

DOCE_Insp2 Geographic boundary use to assign Division of Code Enforcement cases for building inspectors City of Syracuse - Division of Code Enforcement

DOCE_Permit Geographic boundary use to assign Division of Code Enforcement cases for permit inspectors City of Syracuse - Division of Code Enforcement

DOCE_Comm Geographic boundary use to assign Division of Code Enforcement cases for commercial and electrical inspectors City of Syracuse - Division of Code Enforcement

FIRE_DIST Fire engine districts City of Syracuse - Fire Department

ZONE_DIST_PREV Former zoning district code Syracuse-Onondaga County Planning Agency (SOCPA)

REZONE ReZone designation (adopted June 2023, last updated 2024-12-17) City of Syracuse - Neighborhood and Business Development

CC_DIST Current Common Council District property is located in Onondaga County Board of Elections

CTID_2020 Census Tract ID (2020) U.S. Census Bureau

CTLAB_2020 Census Tract Label (2020) U.S. Census Bureau

CT_2020 Census Tract (2020) U.S. Census Bureau

SpecNhood Is property located in a special Neighborhood historic preservation district? (1 = Yes; 0 or null = No) Syracuse-Onondaga County Planning Agency (SOCPA)

InPD Is property located in preservation district? (1 = Yes; 0 or null = No) Syracuse-Onondaga County Planning Agency (SOCPA)

PDNAME Preservation District name Syracuse-Onondaga County Planning Agency (SOCPA)

ELECT_DIST Election district number Onondaga County Board of Elections

CITY_WARD City ward number Onondaga County Board of Elections

COUNTY_LEG Onondaga County Legislative District number (as of Dec 2024) Onondaga County Board of Elections

NYS_ASSEMB New York State Assembly District number (as of Dec 2024) Onondaga County Board of Elections

NYS_SENATE New York State Senate District number (as of Dec 2024) Onondaga County Board of Elections

US_CONGR United States Congressional District number Onondaga County Board of Elections

LAT Parcel latitude (centroid y-coordinate) in decimal degrees NA - Calculated field

LONG Parcel longitude (centroid x-coordinate) in decimal degrees NA - Calculated field

This web mapping application shows the monitoring networks used to track drought conditions across Manitoba. Each tab displays a different source of data, including: streamflow and water level, groundwater, precipitation, reservoir supply status, and Canadian and United States Drought Monitor contours. Each of the data sources are explained in more detail below. Please note the following information when using the web mapping application: When you click on a data point on the River and Lake, Groundwater or Reservoir maps, a pop-up box will appear. This pop-up box contains information on the streamflow (in cubic feet per second; ft3/s), water level (in feet), groundwater level (in metres), storage volume (acre-feet), or supply status (in per cent of full supply level; %) for that location. Click on the Percentile Plot link at the bottom of the pop-up box to view a three-year time series of observed conditions (available for river and lake and groundwater conditions only). A toolbar is located in the top right corner of the web mapping application. The Query Tool can be used to search for a specific river, lake or reservoir monitoring station by name or aquifer type by location. The Layer List enables the user to toggle between precipitation conditions layers (1-month, 3-month, and 12-month) and increase or decrease the transparency of the layer. Data is current for the date indicated on the pop-up box, percentile plot, or map product. Near-real time data are preliminary and subject to change upon review. River and lake conditions are monitored to determine the severity of hydrological dryness in a watershed. River and lake measurements are converted to percentiles by comparing daily measurements from a specified day to historical measurements over the monitoring station’s period of record for that particular day. A percentile is a value on a scale of zero to 100 that indicates the percent of a distribution that is equal to or below it. In general: Streamflow (or lake level) which is greater than the 90th percentile is classified as “much above normal”. Streamflow (or lake level) which is between the 75th and 90th percentile is classified as “above normal”. Streamflow (or lake level) which is between the 25th and 75th percentiles is classified as “normal”. Streamflow (or lake level) which is between the 10th and 25th percentile is classified as “below normal”. Streamflow (or lake level) which is less than the 10th percentile is classified as “much below normal”. "Median" indicates the midpoint (or 50th percentile) of the distribution, whereby 50 per cent of the data falls below the given point, and 50 per cent falls above. Other flow categories include: "Lowest" indicates that the estimated streamflow (or lake level) is the lowest value ever measured for the day of the year. "Highest" indicates that the estimated streamflow (or lake level) is the highest value ever measured for the day of the year. Monitoring stations classified as “No Data” do not have current estimates of streamflow (or lake level) available. Click on the Percentile Plot link at the bottom of the pop-up box to view a graph (in PDF format) displaying a three-year time series of observed conditions relative to the historical percentiles described above. The period of record used to compute the percentiles is stated, alongside the station ID, and if the river or lake is regulated (i.e. controlled) or natural. Hydrometric data are obtained from Water Survey of Canada, Manitoba Infrastructure, and the United States Geological Survey. Near real-time data are preliminary as they can be impacted by ice, wind, or equipment malfunction. Preliminary data are subject to change upon review. Groundwater conditions are monitored to determine the severity of hydrological dryness in an aquifer. Water levels are converted to percentiles by comparing daily measurements from a specified day to historical measurements over the monitoring station’s period of record for that particular day. A percentile is a value on a scale of zero to 100 that indicates the percent of a distribution that is equal to or below it. In general: A groundwater level which is greater than the 90th percentile is classified as “much above normal”. A groundwater level which is between the 75th and 90th percentile is classified as “above normal”. A groundwater level which is between the 25th and 75th percentiles is classified as “normal”. A groundwater level which is between the 10th and 25th percentile is classified as “below normal”. A groundwater level which is less than the 10th percentile is classified as “much below normal”. Monitoring stations classified as “No Data” do not have current measurements of groundwater level available. "Median" indicates the midpoint (or 50th percentile) of the distribution, whereby 50 per cent of the data falls below the given point, and 50 per cent falls above. Click on the Percentile Plot link at the bottom of the pop-up box to view a graph (in PDF format) displaying a three-year time series of observed conditions relative to the historical percentiles described above. The period of record used to compute the percentiles is stated, alongside the station ID. Precipitation conditions maps are developed to determine the severity of meteorological dryness and are also an indirect measurement of agricultural dryness. Precipitation indicators are calculated at over 40 locations by comparing total precipitation over the time period to long-term (1971 – 2015) medians. Three different time periods are used to represent: (1) short-term conditions (the past month), (2) medium-term conditions (the past three months), and (3) long-term conditions (the past twelve months). These indicator values are then interpolated across the province to produce the maps provided here. Long-term and medium-term precipitation indicators provide the most appropriate assessment of dryness as the short term indicator is influenced by significant rainfall events and spatial variability in rainfall, particularly during summer storms. Due to large distances between meteorological stations in northern Manitoba, the interpolated contours in this region are based on limited observations and should be interpreted with caution. Precipitation conditions are classified as follows: Per cent of median greater than 115 per cent is classified as “above normal”. Per cent of median between 85 per cent and 115 per cent is classified as “normal”. Per cent of median between 60 per cent and 85 per cent is classified as “moderately dry”. Per cent of median between 40 per cent and 60 per cent is classified as a “severely dry”. Per cent of median less than 40 per cent is classified as an “extremely dry”. Precipitation data is obtained from Environment and Climate Change Canada, Manitoba Agriculture, and Manitoba Sustainable Development’s Fire Program. Reservoir conditions are monitored at 15 locations across southern Manitoba to track water availability, including possible water shortages. Conditions are reported both as a water level and as a “supply status”. The supply status is the current amount of water stored in the reservoir compared to the target storage volume of the reservoir (termed “full supply level”). A supply status greater than 100 per cent represents a reservoir that is exceeding full supply level. Canadian and U.S Drought Monitors: Several governments, agencies, and universities monitor the spatial extent and intensity of drought conditions across Canada and the United States, producing maps and data products available through the Canadian Drought Monitor and United States Drought Monitor websites. The Canadian Drought Monitor is managed through Agriculture and Agri-Food Canada, while the United States Drought Monitor is a joint effort between The National Drought Mitigation Centre (at the University of Nebraska-Lincoln), the United States Department of Agriculture, and the National Oceanic and Atmospheric Administration. The drought monitor assessments are based on a suite of drought indicators, impacts data and local reports as interpreted by federal, provincial/state and academic scientists. Both the Canadian and United States drought assessments have been amalgamated to form this map, and use the following drought classification system: D0 (Abnormally Dry) – represents an event that occurs every 3 - 5 years; D1 (Moderate Drought) – 5 to 10 year event; D2 (Severe Drought) – 10 to 20 year event; D3 (Extreme Drought) – 20 to 50 year event; and D4 (Exceptional Drought) – 50+ year event. Additionally, the map indicates whether drought impacts are: (1) short-term (S); typically less than six months, such as impacts to agriculture and grasslands, (2) long-term (L); typically more than six months, such as impacts to hydrology and ecology, or (3) a combination of both short-term and long-term impacts (SL). The Canadian Drought Monitor publishes its assessments monthly, and United States Drought Monitor maps are released weekly on Thursday mornings. The amalgamated map provided here will be updated on a monthly basis corresponding to the release of the Canadian Drought Monitor map. Care will be taken to ensure both maps highlight drought conditions for the same point in time; however the assessment dates may differ between Canada and the United States due to when the maps are published. Please click on an area of drought on the map to confirm the assessment date. Canadian Drought Monitor data are subject to the Government of Canada Open Data Licence Agreement: https://open.canada.ca/en/open-government-licence-canada. United States Drought Monitor data are available on the United States Drought Monitor website: https://droughtmonitor.unl.edu. For more information, please visit the Manitoba Drought Monitor website.

Data Dictionary: Attribute Label Definition Source

TAX_ID Unique 26 character property tax identification number Onondaga County Planning

SHAPE_Leng Shape length NA - Calculated field

SHAPE_Area Shape area NA - Calculated field

PRINTKEY Abbreviated tax identification number (section-block-lot) Onondaga County Planning

ADDRESSNUM Property’s physical street address Onondaga County Planning

ADDRESSNAM Property’s physical street name Onondaga County Planning

SBL Property Tax Map Number (Section, Block, Lot) City of Syracuse - Assessment

PNUMBR Property Number (10 digit number) City of Syracuse - Assessment

StNum Parcel street number City of Syracuse - Assessment

StName Parcel street name City of Syracuse - Assessment

FullAddress Street number and street name City of Syracuse - Assessment

Zip Parcel zip code City of Syracuse - Assessment

desc_1 Lot description including dimensions City of Syracuse - Assessment

desc_2 Lot description including dimensions City of Syracuse - Assessment

desc_3 Lot description including dimensions City of Syracuse - Assessment

SHAPE_IND

City of Syracuse - Assessment

LUC_parcel New 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.htm City of Syracuse - Assessment

LU_parcel New York State property type classification name City of Syracuse - Assessment

LUCat_Old Legacy land use category that corresponds to the overarching NYS category, i.e. all 400s = commercial, all 300s = vacant land, etc. NA

land_av Land assessed value City of Syracuse - Assessment

total_av Full assessed value City of Syracuse - Assessment

Owner Property owner name (First, Initial, Last, Suffix) City of Syracuse - Assessment

OwnerFullAddress Property owner assessed address (street number, street name, street direction [or PO Box], unit name, unit number, city, state or country, zip code) City of Syracuse - Assessment

Add1_OwnPOBox Property owner mailing address (PO Box) City of Syracuse - Assessment

Add2_OwnStAdd Property owner mailing address (street number, street name, street direction) City of Syracuse - Assessment

Add3_OwnUnitInfo Property owner mailing address unit info (unit name, unit number) City of Syracuse - Assessment

Add4_OwnCityStateZip Property owner mailing address (city, state or country, zip code) City of Syracuse - Assessment

FRONT Front footage for square or rectangular shaped lots and the effective front feet on irregularly shaped lots in feet City of Syracuse - Assessment

DEPTH Actual depth of rectangular shaped lots in feet (irregular lots are usually measured in acres or square feet) City of Syracuse - Assessment

ACRES Number of acres (where values were 0, acreage calculated as FRONT*DEPTH)/43560) City of Syracuse - Assessment

yr_built Year 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 - Assessment

n_ResUnits Number of residential units NA - Calculated field

IPSVacant Is it a vacant structure? ("Commercial" or "Residential" = Yes; null = No) City of Syracuse - Division of Code Enforcement

IPS_Condition Property Condition Score assigned to vacant properties by housing inspectors during routine vacant inspections (1 = Worst; 5 = Best) City of Syracuse - Division of Code Enforcement

NREligible National Register of Historic Places Eligible ("NR Eligible (SHPO)," or "NR Listed") City of Syracuse - Neighborhood and Business Development

LPSS Locally Protected Site Status ("Eligible/Architecturally Significant" or "Local Protected Site or Local District") City of Syracuse - Neighborhood and Business Development

WTR_ACTIVE Water activity code ("I" = Inactive; "A" = Active) City of Syracuse - Water

RNI Is property located in Resurgent Neighborhood Initiative (RNI) Area? (1 = Yes; 0 = No) City of Syracuse - Neighborhood and Business Development

DPW_Quad Geographic 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 Works

DPW_Sani DPW sanitation trash and recycling pick-up day (trash service weekly, recycling biweekly) City of Syracuse - Department of Public Works

DPW_Recycle DPW recycling biweekly pick-up group (either Week A or Week B), collection occurs every other week City of Syracuse - Department of Public Works

TNT_NAME TNT Sector property is located in City of Syracuse - Neighborhood and Business Development

NHOOD City Neighborhood Syracuse-Onondaga County Planning Agency (SOCPA)

NRSA Is property located in Neighborhood Revitilization Strategy Area (NRSA)? (1 = Yes; 0 = No) City of Syracuse - Neighborhood and Business Development

DOCE_Insp1 Geographic boundary use to assign Division of Code Enforcement cases for housing inspectors City of Syracuse - Division of Code Enforcement

DOCE_Insp2 Geographic boundary use to assign Division of Code Enforcement cases for building inspectors City of Syracuse - Division of Code Enforcement

DOCE_Permit Geographic boundary use to assign Division of Code Enforcement cases for permit inspectors City of Syracuse - Division of Code Enforcement

DOCE_Comm Geographic boundary use to assign Division of Code Enforcement cases for commercial and electrical inspectors City of Syracuse - Division of Code Enforcement

FIRE_DIST Fire engine districts City of Syracuse - Fire Department

ZONE_DIST_PREV Former zoning district code Syracuse-Onondaga County Planning Agency (SOCPA)

REZONE ReZone designation (adopted June 2023, last updated 2024-12-17) City of Syracuse - Neighborhood and Business Development

CC_DIST Current Common Council District property is located in Onondaga County Board of Elections

CTID_2020 Census Tract ID (2020) U.S. Census Bureau

CTLAB_2020 Census Tract Label (2020) U.S. Census Bureau

CT_2020 Census Tract (2020) U.S. Census Bureau

SpecNhood Is property located in a special Neighborhood historic preservation district? (1 = Yes; 0 or null = No) Syracuse-Onondaga County Planning Agency (SOCPA)

InPD Is property located in preservation district? (1 = Yes; 0 or null = No) Syracuse-Onondaga County Planning Agency (SOCPA)

PDNAME Preservation District name Syracuse-Onondaga County Planning Agency (SOCPA)

ELECT_DIST Election district number Onondaga County Board of Elections

CITY_WARD City ward number Onondaga County Board of Elections

COUNTY_LEG Onondaga County Legislative District number (as of Dec 2024) Onondaga County Board of Elections

NYS_ASSEMB New York State Assembly District number (as of Dec 2024) Onondaga County Board of Elections

NYS_SENATE New York State Senate District number (as of Dec 2024) Onondaga County Board of Elections

US_CONGR United States Congressional District number Onondaga County Board of Elections

Section 2a2 of the June 2022 Secretary’s Memorandum 1077-004 on Climate Resilience and Carbon Stewardship of America’s National Forests and Grasslands (https://www.usda.gov/directives/sm-1077-004) directed the Forest Service to spatially identify risks to ecosystem values to inform decision-making. This app includes datasets related to old-growth and mature forests.U.S. Department of Agriculture Forest Service and U.S. Department of the Interior Bureau of Land Management (BLM) lands contain more than 178 million acres of forest, which provide a variety of ecological, social, Tribal, and economic values. Among these values are those provided by older forests, sometimes referred to as ‘old-growth’ and ‘mature’ forests. However, neither of these terms has been consistently defined, nor has their national extent been inventoried on Forest Service or Bureau of Land Management lands by these agencies previously. These data are national in scale and present area (acres) estimates of old-growth and mature forests across all Forest Service and BLM lands. This report contains the first national inventory of old-growth and mature forests focused specifically on Forest Service and BLM lands and demonstrates that old-growth and mature forest is common (majority of Forest Service and BLM forest land) and generally widely distributed. These forests are well distributed across land use allocations. The definitions of old-growth and mature forests are presented in two forms (Tech Report Reference). Narrative frameworks are descriptive, general definitions of old-growth and mature forests that can be used consistently across geographic scales and forest types. Working definitions provide detailed quantitative criteria, using measurable structural characteristics, that were applied to specific regions and forest-types in this national-scale inventory. Forest Service and BLM lands combined contain 32.7 +/- 0.4 million acres of old-growth and 80.1 +/- 0.5 million acres of mature forest, which collectively represents 63 percent of all Forest Service and BLM forested lands and 26 percent of total surface ownership managed by the two agencies. This national-scale inventory was conducted by applying old-growth and mature working definitions to Forest Inventory and Analysis field plot data. Like all the nation’s forests, old-growth and mature forests are threatened by climate change and associated stressors. The inventory and definitions for old-growth and mature forests are part of an overarching climate-informed strategy to address climate-related impacts, including insects and disease, reduce wildfire risk, and help retain carbon. Inventory results will be used to assess threats to these forests, which will allow consideration of appropriate climate informed forest management, as required by subsequent sections of EO 14072.Old-Growth and Mature forest area (acres) estimates are reported using the Fireshed Registry (https://www.fs.usda.gov/research/rmrs/projects/firesheds)