This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.
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
Attribute field definitions for data created by Forest Practice GIS on plans and notices for timber harvesting either submitted to, approved, or accepted by, the California Department of Forestry and Fire Protection. Includes roads and hydrology within and adjacent to harvest areas.
Use the Attachment Viewer template to provide an app for users to explore a layer's features and review attachments with the option to update attribute data. Present your images, videos, and PDF files collected using ArcGIS Field Maps or ArcGIS Survey123 workflows. Choose an attachment-focused layout to display individual images beside your map or a map-focused layout to highlight your map next to a gallery of images. Examples: Review photos collected during emergency response damage inspections. Display the results of field data collection and support downloading images for inclusion in a report. Present a map of land parcel along with associated documents stored as attachments. Data requirements The Attachment Viewer template requires a feature layer with attachments. It includes the capability to view attachments of a hosted feature service or an ArcGIS Server feature service (10.8 or later). Currently, the app can display JPEG, JPG, PNG, GIF, MP4, QuickTime (.mov), and PDF files in the viewer window. All other attachment types are displayed as a link. Key app capabilities App layout - Choose between an attachment-focused layout, which displays one attachment at a time in the main panel of the app with the map on the side, or a map-focused layout, which displays the map in the main panel of the app with a gallery of attachments. Feature selection - Allows users to select features in the map and view associated attachments. Review data - Enable tools to review and update existing records. Zoom, pan, download images - Allow users to interact with and download attachments. Language switcher - Provide translations for custom text and create a multilingual app. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.
The site suitability criteria included in the techno-economic land use screens are listed below. As this list is an update to previous cycles, tribal lands, prime farmland, and flood zones are not included as they are not technically infeasible for development. The techno-economic site suitability exclusion thresholds are presented in table 1. Distances indicate the minimum distance from each feature for commercial scale wind developmentAttributes: Steeply sloped areas: change in vertical elevation compared to horizontal distancePopulation density: the number of people living in a 1 km2 area Urban areas: defined by the U.S. Census. Water bodies: defined by the U.S. National Atlas Water Feature Areas, available from Argonne National Lab Energy Zone Mapping Tool Railways: a comprehensive database of North America's railway system from the Federal Railroad Administration (FRA), available from Argonne National Lab Energy Zone Mapping Tool Major highways: available from ESRI Living Atlas Airports: The Airports dataset including other aviation facilities as of July 13, 2018 is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics's (BTS's) National Transportation Atlas Database (NTAD). The Airports database is a geographic point database of aircraft landing facilities in the United States and U.S. Territories. Attribute data is provided on the physical and operational characteristics of the landing facility, current usage including enplanements and aircraft operations, congestion levels and usage categories. This geospatial data is derived from the FAA's National Airspace System Resource Aeronautical Data Product. Available from Argonne National Lab Energy Zone Mapping Tool Active mines: Active Mines and Mineral Processing Plants in the United States in 2003Military Lands: Land owned by the federal government that is part of a US military base, camp, post, station, yard, center, or installation. Table 1 Wind Steeply sloped areas >10o Population density >100/km2 Capacity factor <20% Urban areas <1000 m Water bodies <250 m Railways <250 m Major highways <125 m Airports <5000 m Active mines <1000 m Military Lands <3000m For more information about the processes and sources used to develop the screening criteria see sources 1-7 in the footnotes. Data updates occur as needed, corresponding to typical 3-year CPUC IRP planning cyclesFootnotes:[1] Lopez, A. et. al. “U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis,” 2012. https://www.nrel.gov/docs/fy12osti/51946.pdf[2] https://greeningthegrid.org/Renewable-Energy-Zones-Toolkit/topics/social-environmental-and-other-impacts#ReadingListAndCaseStudies[3] Multi-Criteria Analysis for Renewable Energy (MapRE), University of California Santa Barbara. https://mapre.es.ucsb.edu/[4] Larson, E. et. al. “Net-Zero America: Potential Pathways, Infrastructure, and Impacts, Interim Report.” Princeton University, 2020. https://environmenthalfcentury.princeton.edu/sites/g/files/toruqf331/files/2020-12/Princeton_NZA_Interim_Report_15_Dec_2020_FINAL.pdf.[5] Wu, G. et. al. “Low-Impact Land Use Pathways to Deep Decarbonization of Electricity.” Environmental Research Letters 15, no. 7 (July 10, 2020). https://doi.org/10.1088/1748-9326/ab87d1.[6] RETI Coordinating Committee, RETI Stakeholder Steering Committee. “Renewable Energy Transmission Initiative Phase 1B Final Report.” California Energy Commission, January 2009.[7] Pletka, Ryan, and Joshua Finn. “Western Renewable Energy Zones, Phase 1: QRA Identification Technical Report.” Black & Veatch and National Renewable Energy Laboratory, 2009. https://www.nrel.gov/docs/fy10osti/46877.pdf.[8]https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2019&layergroup=Urban+Areas[9]https://ezmt.anl.gov/[10]https://www.arcgis.com/home/item.html?id=fc870766a3994111bce4a083413988e4[11]https://mrdata.usgs.gov/mineplant/Credits Title: Techno-economic screening criteria for utility-scale wind energy installations for Integrated Resource Planning Purpose for creation: These site suitability criteria are for use in electric system planning, capacity expansion modeling, and integrated resource planning. Keywords: wind energy, resource potential, techno-economic, IRP Extent: western states of the contiguous U.S. Use Limitations The geospatial data created by the use of these techno-economic screens inform high-level estimates of technical renewable resource potential for electric system planning and should not be used, on their own, to guide siting of generation projects nor assess project-level impacts.Confidentiality: Public ContactEmily Leslie Emily@MontaraMtEnergy.comSam Schreiber sam.schreiber@ethree.com Jared Ferguson Jared.Ferguson@cpuc.ca.govOluwafemi Sawyerr femi@ethree.com
[Metadata] Hawaii Digital Soil Survey polygons for the State of Hawaii. Downloaded statewide dataset from USDA/NRCS (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database) 11/28/23. This dataset is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information.This dataset consists of georeferenced digital map data and computerized attribute data. The map data are in a state-wide extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.
For more information, see metadata at https://files.hawaii.gov/dbedt/op/gis/data/soils.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.
This dataset includes all 7 metro counties that have made their parcel data freely available without a license or fees.
This dataset is a compilation of tax parcel polygon and point layers assembled into a common coordinate system from Twin Cities, Minnesota metropolitan area counties. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.
NOTICE: The standard set of attributes changed to the MN Parcel Data Transfer Standard on 1/1/2019.
https://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html
See section 5 of the metadata for an attribute summary.
Detailed information about the attributes can be found in the Metro Regional Parcel Attributes document.
The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties have polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. One primary example of this is the condominium, though some counties stacked polygons for condos. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated.
The polygon layer is broken into individual county shape files. The points layer is provided as both individual county files and as one file for the entire metro area.
In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties.
This is a MetroGIS Regionally Endorsed dataset.
Additional information may be available from each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person at each individual county.
Anoka = http://www.anokacounty.us/315/GIS
Caver = http://www.co.carver.mn.us/GIS
Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx
Hennepin = https://gis-hennepin.hub.arcgis.com/pages/open-data
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://opendata.gis.co.scott.mn.us/
Washington: http://www.co.washington.mn.us/index.aspx?NID=1606
Existing land use categories for current land uses in Fairfax County as of the VALID_TO date in the attribute table.
For methodology and a data dictionary please visit: https://www.fairfaxcounty.gov/demographics/sites/demographics/files/assets/datadictionary/ipls-data-dictionary-gis.pdf
This dataset is a compilation of tax parcel polygon and point layers from the seven Twin Cities, Minnesota metropolitan area counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington. The seven counties were assembled into a common coordinate system. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. (See section 5 of the metadata). The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.
This is an annual version of the MetroGIS Regional Parcel Dataset that can be used with other annual versions to do change analysis and time series investigations. This dataset is intended to contain all updates to each county's parcel data through the end of 2004. It was originally published as the 'January 1, 2005' version of the dataset. See the Currentness Reference below and the Entity and Attribute information in Section 5 for more information about the dates for specific aspects of the dataset.
The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties will polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. The primary example of this is the condominium. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated.
The polygon layer is broken into individual county shape files. The points layer is one file for the entire metro area.
In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties.
Polygon and point counts for each county are as follows (based on the January, 2005 dataset):
Anoka = 124,042 polygons, 124,042 points
Carver = 32,910 polygons, 32,910 points
Dakota = 130,989 polygons, 141,444 points
Hennepin = 353,759 polygons, 399,184 points
Ramsey = 148,266 polygons, 163,376 points
Scott = 49,958 polygons, 49,958 points
Washington = 93,794 polygons, 96,570 points
This is a MetroGIS Regionally Endorsed dataset.
Each of the seven Metro Area counties has entered into a multiparty agreement with the Metropolitan Council to assemble and distribute the parcel data for each county as a regional (seven county) parcel dataset.
A standard set of attribute fields is included for each county. The attributes are identical for the point and polygon datasets. Not all attributes fields are populated by each county. Detailed information about the attributes can be found in the MetroGIS Regional Parcels Attributes 2004 document.
Additional information may be available in the individual metadata for each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person listed in the individual county metadata.
Anoka = http://www.anokacounty.us/315/GIS
Caver = http://www.co.carver.mn.us/GIS
Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx
Hennepin: http://www.hennepin.us/gisopendata
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://www.scottcountymn.gov/1183/GIS-Data-and-Maps
Washington = http://www.co.washington.mn.us/index.aspx?NID=1606
[Metadata] Wave energy transect lines georeferenced and digitized from: Hagerman, G. 1992. Wave Energy Resources and Economic Assessment for the State of Hawaii. Prepared for DBEDT. June 1992. Adapted from Figure 2-16 to 2-21. Attribute data is from these figures as well. Attributes include name of transect and kW/m estimate at 80m depth, per the source figures.
For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/wave_energy_transects.pdf or contact Hawaii Statewide GIS Program, Office of Planning, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.
This dataset is a compilation of tax parcel polygon and point layers from the seven Twin Cities, Minnesota metropolitan area counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington. The seven counties were assembled into a common coordinate system. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. (See section 5 of the metadata). The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.
The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties will polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. The primary example of this is the condominium. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated.
The polygon layer is broken into individual county shape files. The points layer is one file for the entire metro area.
In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties.
Polygon and point counts for each county are as follows (based on the January, 2007 dataset):
Anoka = 129,392 polygons, 129,392 points
Carver = 37,021 polygons, 37,021 points
Dakota = 135,586 polygons, 148,952 points
Hennepin = 358,064 polygons, 419,736 points
Ramsey = 148,967 polygons, 166,280 points
Scott = 54,741 polygons, 54,741 points
Washington = 97,922 polygons, 102,309 points
This is a MetroGIS Regionally Endorsed dataset.
Each of the seven Metro Area counties has entered into a multiparty agreement with the Metropolitan Council to assemble and distribute the parcel data for each county as a regional (seven county) parcel dataset.
A standard set of attribute fields is included for each county. The attributes are identical for the point and polygon datasets. Not all attributes fields are populated by each county. Detailed information about the attributes can be found in the MetroGIS Regional Parcels Attributes 2006 document.
Additional information may be available in the individual metadata for each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person listed in the individual county metadata.
Anoka = http://www.anokacounty.us/315/GIS
Caver = http://www.co.carver.mn.us/GIS
Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx
Hennepin: http://www.hennepin.us/gisopendata
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://www.scottcountymn.gov/1183/GIS-Data-and-Maps
Washington = http://www.co.washington.mn.us/index.aspx?NID=1606
These data depict the western United States Map Unit areas as defined by the USDA NRCS. Each Map Unit area contains information on a variety of soil properties and interpretations. The raster is to be joined to the .csv file by the field "mukey." We keep the raster and csv separate to preserve the full attribute names in the csv that would be truncated if attached to the raster. Once joined, the raster can be classified or analyzed by the columns which depict the properties and interpretations. It is important to note that each property has a corresponding component percent column to indicate how much of the map unit has the dominant property provided. For example, if the property "AASHTO Group Classification (Surface) 0 to 1cm" is recorded as "A-1" for a map unit, a user should also refer to the component percent field for this property (in this case 75). This means that an estimated 75% of the map unit has a "A-1" AASHTO group classification and that "A-1" is the dominant group. The property in the column is the dominant component, and so the other 25% of this map unit is comprised of other AASHTO Group Classifications. This raster attribute table was generated from the "Map Soil Properties and Interpretations" tool within the gSSURGO Mapping Toolset in the Soil Data Management Toolbox for ArcGIS™ User Guide Version 4.0 (https://www.nrcs.usda.gov/wps/PA_NRCSConsumption/download?cid=nrcseprd362255&ext=pdf) from GSSURGO that used their Map Unit Raster as the input feature (https://gdg.sc.egov.usda.gov/). The FY2018 Gridded SSURGO Map Unit Raster was created for use in national, regional, and state-wide resource planning and analysis of soils data. These data were created with guidance from the USDA NRCS. The fields named "*COMPPCT_R" can exceed 100% for some map units. The NRCS personnel are aware of and working on fixing this issue. Take caution when interpreting these areas, as they are the result of some data duplication in the master gSSURGO database. The data are considered valuable and required for timely science needs, and thus are released with this known error. The USDA NRCS are developing a data release which will replace this item when it is available. For the most up to date ssurgo releases that do not include the custom fields as this release does, see https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/home/?cid=nrcs142p2_053628#tools For additional definitions, see https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053627.
Display location, shape, and attributes of SDOT, other public agency, and some private retaining walls recorded in SDOT asset management system. | Attribute Information: https://www.seattle.gov/Documents/Departments/SDOT/GIS/Retaining_Walls_OD.pdf | Data Confidence: Medium | Data Confidence Source: 2015 SDOT Asset Management, Status and Condition Report | Update Cycle: Weekly | Contact Email: DOT_IT_GIS@seattle.gov
description: This dataset represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific 'production' or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys), and the Bureau of Census 2015 Cartographic State Boundaries. The Entity-Attribute section of this metadata describes these components in greater detail. Please note that the data on this site, although published at regular intervals, may not be the most current PLSS data that is available from the BLM. Updates to the PLSS data at the BLM State Offices may have occurred since this data was published. To ensure users have the most current data, please refer to the links provided in the PLSS CadNSDI Data Set Availability accessible here: https://gis.blm.gov/EGISDownload/Docs/PLSS_CadNSDI_Data_Set_Availability.pdf or contact the BLM PLSS Data Set Manager.; abstract: This dataset represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific 'production' or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys), and the Bureau of Census 2015 Cartographic State Boundaries. The Entity-Attribute section of this metadata describes these components in greater detail. Please note that the data on this site, although published at regular intervals, may not be the most current PLSS data that is available from the BLM. Updates to the PLSS data at the BLM State Offices may have occurred since this data was published. To ensure users have the most current data, please refer to the links provided in the PLSS CadNSDI Data Set Availability accessible here: https://gis.blm.gov/EGISDownload/Docs/PLSS_CadNSDI_Data_Set_Availability.pdf or contact the BLM PLSS Data Set Manager.
[Metadata] This feature class represents the special soil features that are delineated as one or more points. Downloaded statewide dataset from USDA/NRCS (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database) 11/28/23. It is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The features are linked to attributes in the featdesc attribute table. The map data are in a state-wide extent format.
For more information, see metadata at https://files.hawaii.gov/dbedt/op/gis/data/soils.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.
This wye pipes feature class represents current wastewater information connecting the sewer service to either side of the street in the City of Los Angeles. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most rigorous geographic information of the sanitary sewer system using a geometric network model, to ensure that its sewers reflect current ground conditions. The sanitary sewer system, pump plants, wyes, maintenance holes, and other structures represent the sewer infrastructure in the City of Los Angeles. Wye and sewer information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works.Associated information about the wastewater Wye is entered into attributes. Principal attributes include:WYE_SUBTYPE: wye subtype is the principal field that describes various types of points as either Chimney, Chimney Riser, Offset Chimney Riser, Siphon, Special Case, Spur, Tap, Tee, Unclassified, Vertical Tee, Vertical Tee Riser, Wye, Wye Drawn as a Tap.For a complete list of attribute values, please refer to (TBA Wastewater data dictionary).Wastewater Wye pipes lines layer was created in geographical information systems (GIS) software to display the location of wastewater wye pipes. The wyes lines layer is a feature class in the LACityWastewaterData.gdb Geodatabase dataset. The layer consists of spatial data as a line feature class and attribute data for the features. The lines are entered manually based on wastewater sewer maps and BOE standard plans, and information about the lines is entered into attributes. The wye pipes lines features are sewer pipe connections for buildings. The features in the Wastewater connector wye points layer is a related structure connected with the wye pipe line. The WYE_ID field value is the unique ID. The WYE_ID field relates to the Sewer Permit tables. The annotation wye features are displayed on maps alongside features from the Wastewater Sewer Wye pipes lines layer. The wastewater wye pipes lines are inherited from a sewer spatial database originally created by the City's Wastewater program. The database was known as SIMMS, Sewer Inventory and Maintenance Management System. Wye pipe information should only be added to the Wastewater wye pipes layer if documentation exists, such as a wastewater map approved by the City Engineer. Sewers plans and specifications proposed under private development are reviewed and approved by by Bureau of Engineering. The Department of Public Works, Bureau of Engineering's, Brown Book (current as of 2010) outlines standard specifications for public works construction. For more information on sewer materials and structures, look at the Bureau of Engineering Manual, Part F, Sewer Design, F 400 Sewer Materials and Structures section, and a copy can be viewed at http://eng.lacity.org/techdocs/sewer-ma/f400.pdf.List of Fields:SPECIAL_STRUCT: This attribute is the basin number.TOP_: When a chimney is present, this is the depth at the top of the chimney.BOTTOM: When a chimney is present, this is the depth at the bottom of the chimney.PL_HUNDS: This value is the hundreds portion of the stationing at the property line.SHAPE: Feature geometry.USER_ID: The name of the user carrying out the edits of the wye pipes data.TYPE: This is the old wye status and is no longer referenced.REMARKS: This attribute contains additional comments regarding the wye line segment, such as a line through in all caps when lined out on wye maps.WYE_NO: This value is the number of the line segment for the wye structure located along the pipe segment. This is a 2 digit value. The number starts at 1 for the first wye connected to a pipe. The numbers increase sequentially with each wye being unique.WYE_ID: The value is a combination of PIPE_ID and WYE_NO fields, forming a unique number. This 19 digit value is a key attribute of the wye lines data layer. This field relates to the Permit tables.C_TENS: This value is the tens portion of the stationing at the curb line.C_HUNDS: This value is the hundreds portion of the stationing at the curb line.WYE_SUBTYPE: This value is the type of sewer connection. Values: • 2 - Tap. • 8 - Siphon. • 13 - Wye Drawn as a Tap. • 9 - Special Case. • 6 - Chimney riser. • 4 - Chimney. • 5 - Vertical Tee Riser. • 7 - Vertical tee. • 10 - Spur. • 11 - Unclassified. • 12 - Offset Chimney Riser. • 1 - Wye. • 3 - Tee.SIDE: The side of the pipe looking up stream to which structure attaches. Values: • U - Unknown. • L - Left. • R - Right. • C - Centered.ASSETID: User-defined unique feature number that is automatically generated.PL_DEPTH: This value is the depth of the service connection at the property line.DEPTH: This value is the depth of the Wye from the surface in feet.STAT_HUND: This value is the hundreds portion of the stationing.ENG_DIST: LA City Engineering District. The boundaries are displayed in the Engineering Districts index map. Values: • H - Harbor Engineering District. • C - Central Engineering District. • V - Valley Engineering District. • W - West LA Engineering District.PIPE_ID: The value is a combination of the values in the UP_STRUCT, DN_STRUCT, and PIPE_LABEL fields. This is the 17 digit identifier of each pipe segment and is a key attribute of the pipe line data layer. This field named PIPE_ID relates to the field in the Annotation Pipe and to the field named PIPE_ID in the Pipe line feature class data layers.OBJECTID: Internal feature number.ENABLED: Internal feature number.REHAB: This attribute indicates if the wye pipe has been rehabilitated.C_DEPTH: This value is the depth of the service connection at the curb line.STAT_TENS: This value is the tens portion of the stationing.BASIN: This attribute is the basin number.LAST_UPDATE: Date of last update of the point feature.STATUS: This value is the active or inactive status of the wye pipes. Values: • Capped - Capped. • INACTIVE - Inactive.PL_TENS: This value is the tens portion of the stationing at the property line.CRTN_DT: Creation date of the point feature.SERVICEID: User-defined unique feature number that is automatically generated.SHAPE_Length: Length of feature in internal units.
This layer contains address point features which are used for geocoding addresses and property identification numbers. Data attributes include property addresses and property identification numbers. Addresses are stored in both parsed and concatenated fields.
Link to Attribute Table Information: http://gis.hennepin.us/OpenData/Metadata/Address%20Points.pdf
Use Limitations: This data (i) is furnished "AS IS" with no representation as to completeness or accuracy; (ii) is furnished with no warranty of any kind; and (iii) is not suitable for legal, engineering or surveying purposes. Hennepin County shall not be liable for any damage, injury or loss resulting from this data. General questions about this data set, including errors, omissions, corrections and/or updates should be directed to the Hennepin County GIS Office at 612-596-9484.
© This data set was created by Hennepin County Resident and Real Estate Services Survey Division, and modified by the Hennepin County GIS office.
Statewide dataset containing the location of state, local and selected private roads and their associated attributes, including road names. For attribute data dictionary, see the file RDIUserGuide.pdf.
This dataset is a compilation of tax parcel polygon and point layers from the seven Twin Cities, Minnesota metropolitan area counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington. The seven counties were assembled into a common coordinate system. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. (See section 5 of the metadata). The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.
The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties will polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. The primary example of this is the condominium. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated.
The polygon layer is broken into individual county shape files. The points layer is one file for the entire metro area.
In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties.
Polygon and point counts for each county are as follows (based on the January, 2005 dataset):
Anoka = 124,042 polygons, 124,042 points
Carver = 32,910 polygons, 32,910 points
Dakota = 130,989 polygons, 141,444 points
Hennepin = 353,759 polygons, 399,184 points
Ramsey = 148,266 polygons, 163,376 points
Scott = 49,958 polygons, 49,958 points
Washington = 93,794 polygons, 96,570 points
This is a MetroGIS Regionally Endorsed dataset.
Each of the seven Metro Area counties has entered into a multiparty agreement with the Metropolitan Council to assemble and distribute the parcel data for each county as a regional (seven county) parcel dataset.
A standard set of attribute fields is included for each county. The attributes are identical for the point and polygon datasets. Not all attributes fields are populated by each county. Detailed information about the attributes can be found in the MetroGIS Regional Parcels Attributes 2005 document.
Additional information may be available in the individual metadata for each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person listed in the individual county metadata.
Anoka = http://www.anokacounty.us/315/GIS
Caver = http://www.co.carver.mn.us/GIS
Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx
Hennepin: http://www.hennepin.us/gisopendata
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://www.scottcountymn.gov/1183/GIS-Data-and-Maps
Washington = http://www.co.washington.mn.us/index.aspx?NID=1606
Current households at a parcel level within Fairfax County as of the VALID_TO date in the attribute table.
For methodology and a data dictionary please view the IPLS data dictionary
This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.