This dataset contains model-based place (incorporated and census designated places) estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia —at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population estimates, and American Community Survey (ACS) 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the 2020 Census place boundary file in a GIS system to produce maps for 40 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

The Residential Schools Locations Dataset in Geodatabase format (IRS_Locations.gbd) contains a feature layer "IRS_Locations" that contains the locations (latitude and longitude) of Residential Schools and student hostels operated by the federal government in Canada. All the residential schools and hostels that are listed in the Residential Schools Settlement Agreement are included in this dataset, as well as several Industrial schools and residential schools that were not part of the IRRSA. This version of the dataset doesn’t include the five schools under the Newfoundland and Labrador Residential Schools Settlement Agreement. The original school location data was created by the Truth and Reconciliation Commission, and was provided to the researcher (Rosa Orlandini) by the National Centre for Truth and Reconciliation in April 2017. The dataset was created by Rosa Orlandini, and builds upon and enhances the previous work of the Truth and Reconcilation Commission, Morgan Hite (creator of the Atlas of Indian Residential Schools in Canada that was produced for the Tk'emlups First Nation and Justice for Day Scholar's Initiative, and Stephanie Pyne (project lead for the Residential Schools Interactive Map). Each individual school location in this dataset is attributed either to RSIM, Morgan Hite, NCTR or Rosa Orlandini. Many schools/hostels had several locations throughout the history of the institution. If the school/hostel moved from its’ original location to another property, then the school is considered to have two unique locations in this dataset,the original location and the new location. For example, Lejac Indian Residential School had two locations while it was operating, Stuart Lake and Fraser Lake. If a new school building was constructed on the same property as the original school building, it isn't considered to be a new location, as is the case of Girouard Indian Residential School.When the precise location is known, the coordinates of the main building are provided, and when the precise location of the building isn’t known, an approximate location is provided. For each residential school institution location, the following information is provided: official names, alternative name, dates of operation, religious affiliation, latitude and longitude coordinates, community location, Indigenous community name, contributor (of the location coordinates), school/institution photo (when available), location point precision, type of school (hostel or residential school) and list of references used to determine the location of the main buildings or sites. Access Instructions: there are 47 files in this data package. Please download the entire data package by selecting all the 47 files and click on download. Two files will be downloaded, IRS_Locations.gbd.zip and IRS_LocFields.csv. Uncompress the IRS_Locations.gbd.zip. Use QGIS, ArcGIS Pro, and ArcMap to open the feature layer IRS_Locations that is contained within the IRS_Locations.gbd data package. The feature layer is in WGS 1984 coordinate system. There is also detailed file level metadata included in this feature layer file. The IRS_locations.csv provides the full description of the fields and codes used in this dataset.

Spreadsheets and graphs are powerful tools that make data come alive and tell a story. Now, use maps to see the story from another perspective. ArcGIS Maps for Office enables Microsoft Excel and PowerPoint users worldwide to ask location-related questions of data, get powerful insights, and make the best decisions. You can:Map your spreadsheet data – whether you want to see customer locations, ZIP code aggregations, custom sales territories and more – you can see it all.Add geographic context to your spreadsheet data and communicate these insights via interactive maps in PowerPoint.Gain insight into demographic, spending, behavior, and landscape information, among many more.Use the authoritative content on the ArcGIS platform to supplement your location data and add context to the locations in your spreadsheet.Securely share your maps with colleagues and stakeholders.Bring the power of the ArcGIS platform into your spreadsheets and presentations. To use ArcGIS Maps for Office you need an ArcGIS Online paid or trial subscription or a Portal for ArcGIS Named User License and Microsoft Office 2010, 2013, or 2016. Visit the online documentation for information on how to use this app.

Deprecation notice: This tool is deprecated because this functionality is now available with out-of-the-box tools in ArcGIS Pro. The tool author will no longer be making further enhancements or fixing major bugs.Use Add GTFS to a Network Dataset to incorporate transit data into a network dataset so you can perform schedule-aware analyses using the Network Analyst tools in ArcMap.After creating your network dataset, you can use the ArcGIS Network Analyst tools, like Service Area and OD Cost Matrix, to perform transit/pedestrian accessibility analyses, make decisions about where to locate new facilities, find populations underserved by transit or particular types of facilities, or visualize the areas reachable from your business at different times of day. You can also publish services in ArcGIS Server that use your network dataset.The Add GTFS to a Network Dataset tool suite consists of a toolbox to pre-process the GTFS data to prepare it for use in the network dataset and a custom GTFS transit evaluator you must install that helps the network dataset read the GTFS schedules. A user's guide is included to help you set up your network dataset and run analyses.Instructions:Download the tool. It will be a zip file.Unzip the file and put it in a permanent location on your machine where you won't lose it. Do not save the unzipped tool folder on a network drive, the Desktop, or any other special reserved Windows folders (like C:\Program Files) because this could cause problems later.The unzipped file contains an installer, AddGTFStoaNetworkDataset_Installer.exe. Double-click this to run it. The installation should proceed quickly, and it should say "Completed" when finished.Read the User's Guide for instructions on creating and using your network dataset.System requirements:ArcMap 10.1 or higher with a Desktop Standard (ArcEditor) license. (You can still use it if you have a Desktop Basic license, but you will have to find an alternate method for one of the pre-processing tools.) ArcMap 10.6 or higher is recommended because you will be able to construct your network dataset much more easily using a template rather than having to do it manually step by step. This tool does not work in ArcGIS Pro. See the User's Guide for more information.Network Analyst extensionThe necessary permissions to install something on your computer.Data requirements:Street data for the area covered by your transit system, preferably data including pedestrian attributes. If you need help preparing high-quality street data for your network, please review this tutorial.A valid GTFS dataset. If your GTFS dataset has blank values for arrival_time and departure_time in stop_times.txt, you will not be able to run this tool. You can download and use the Interpolate Blank Stop Times tool to estimate blank arrival_time and departure_time values for your dataset if you still want to use it.Help forum

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.

This dataset contains model-based place (incorporated and census designated places) level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the 2019 Census TIGER/Line place boundary file in a GIS system to produce maps for 29 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

In this course, you will learn about some common types of data used for GIS mapping and analysis, and practice adding data to a file geodatabase to support a planned project.Goals Create a file geodatabase. Add data to a file geodatabase. Create an empty geodatabase feature class.

The way to access Layers Quickly.

Quick Layers is an Add-In for ArcGIS Pro 3 that allows rapid access to the DNR's Geospatial Data Resource Site (GDRS). The GDRS is a data structure that serves core geospatial dataset and applications for not only DNR, but many state agencies, and supports the Minnesota Geospatial Commons. Data added from Quick Layers is pre-symbolized, helping to standardize visualization and map production. Current version: 3.11

To use Quick Layers with the GDRS, there's no need to download QuickLayers from this location. Instead, download a full copy or a custom subset of the public GDRS (including Quick Layers for ArcGIS Pro 3) using GDRS Manager.

Quick Layers also allows users to save and share their own pre-symbolized layers, thus increasing efficiency and consistency across the enterprise.

Installation:

After using GDRS Manager to create a GDRS, including Quick Layers, add the path to the Quick Layers addin to the list of shared folders:
1. Open ArcGIS Pro
2. Project -> Add-In Manager -> Options
3. Click add folder, and enter the location of the Quick Layers Pro app. For example, if your GDRS is mapped to the V drive, the path would be V:\gdrs\apps\pub\us_mn_state_dnr\quick_layers_pro3
4. After you do this, the Quick Layers ribbon will be available. To also add Quick Layers to the Quick Access Toolbar at the top, right click Quick Layers, and select Add to Quick Access Toolbar

The link below is only for those who are using Quick Layers without a GDRS. To get the most functionality out of Quick Layers, don't install it separately, but instead download it as part of a GDRS build using GDRS Manager.

This dataset contains model-based place (incorporated and census designated places) level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities Project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the 2019 Census TIGER/Line place boundary file in a GIS system to produce maps for 29 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=024cf3f6f59e49fe8c70e0e5410fe3cf

This dataset contains model-based county-level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2022 county population estimates, and American Community Survey (ACS) 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the census 2022 county boundary file in a GIS system to produce maps for 40 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

Data Driven Detroit created the data by selecting locations from NETS and ESRI business data with proper NAICS codes, then adding and deleting though local knowledge and confirmation with Google Streetview. These locations are Grocery stores which primarily sell food and don't include convenience stores. Visual confirmation cues included the existence of the word "grocery" in the name, or the presence of shopping carts.

Geoform is a configurable app template for form based data editing of a Feature Service. This application allows users to enter data through a form instead of a map's pop-up while leveraging the power of the Web Map and editable Feature Services. This app geo-enables data and workflows by lowering the barrier of entry for completing simple tasks. Use CasesProvides a form-based experience for entering data through a form instead of a map pop-up. This is a good choice for users who find forms a more intuitive format than pop-ups for entering data.Useful to collect new point data from a large audience of non technical staff or members of the community.Configurable OptionsGeoform has an interactive builder used to configure the app in a step-by-step process. Use Geoform to collect new point data and configure it using the following options:Choose a web map and the editable layer(s) to be used for collection.Provide a title, logo image, and form instructions/details.Control and choose what attribute fields will be present in the form. Customize how they appear in the form, the order they appear in, and add hint text.Select from over 15 different layout themes.Choose the display field that will be used for sorting when viewing submitted entries.Enable offline support, social media sharing, default map extent, locate on load, and a basemap toggle button.Choose which locate methods are available in the form, including: current location, search, latitude and longitude, USNG coordinates, MGRS coordinates, and UTM coordinates.Supported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsThis web app includes the capability to edit a hosted feature service or an ArcGIS Server feature service. Creating hosted feature services requires an ArcGIS Online organizational subscription or an ArcGIS Developer account. Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to Create a Web AppOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.

The way to access Layers Quickly.

Quick Layers is an Add-In for ArcMap 10.6+ that allows rapid access to the DNR's Geospatial Data Resource Site (GDRS). The GDRS is a data structure that serves core geospatial dataset and applications for not only DNR, but many state agencies, and supports the Minnesota Geospatial Commons. Data added from Quick Layers is pre-symbolized, helping to standardize visualization and map production. Current version: 1.164

To use Quick Layers with the GDRS, there's no need to download QuickLayers from this location. Instead, download a full copy or a custom subset of the public GDRS (including Quick Layers) using GDRS Manager.

Quick Layers also allows users to save and share their own pre-symbolized layers, thus increasing efficiency and consistency across the enterprise.

Installation:

After using GDRS Manager to create a GDRS, including Quick Layers, add the path to the Quick Layers addin to the list of shared folders:
1. Open ArcMap
2. Customize -> Add-In Manager… -> Options
3. Click add folder, and enter the location of the Quick Layers app. For example, if your GDRS is mapped to the V drive, the path would be V:\gdrs\apps\pub\us_mn_state_dnr\quick_layers
4. After you do this, the Quick Layers toolbar will be available. To add it, go to Customize -> Toolbars and select DNR Quick Layers 10

The link below is only for those who are using Quick Layers without a GDRS. To get the most functionality out of Quick Layers, don't install it separately, but instead download it as part of a GDRS build using GDRS Manager.

This Guide is designed to assist you with using ArcGIS Online (AGOL)'s Map Viewer.An ArcGIS web map is an interactive display of geographic information. Web maps are made by adding and combining layers. The layers are made from data, they are logical collections of geographic data.Map Viewer can be used to view, explore and create web maps in ArcGIS Online.

This dataset contains model-based place (incorporated and census designated places) level estimates for the PLACES project 2020 release in GIS-friendly format. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the 2019 Census TIGER/Line place boundary file in a GIS system to produce maps for 27 measures at the place level. An ArcGIS Online feature service is also available at https://www.arcgis.com/home/item.html?id=8eca985039464f4d83467b8f6aeb1320 for users to make maps online or to add data to desktop GIS software.

The Minnesota DNR Toolbox and Hydro Tools provide a number of convenience geoprocessing tools used regularly by MNDNR staff. Many of these may be useful to the wider public. However, some tools may rely on data that is not available outside of the DNR. All tools require at least ArcGIS 10+.

If you create a GDRS using GDRS Manager and include this toolbox resource and MNDNR Quick Layers, the DNR toolboxes will automatically be added to the ArcToolbox window whenever Quick Layers GDRS Location is set to the GDRS location that has the toolboxes.

Toolsets included in MNDNR Tools V10:
- Analysis Tools
- Conversion Tools
- Division Tools
- General Tools
- Hydrology Tools
- LiDAR and DEM Tools
- Raster Tools
- Sampling Tools

These toolboxes are provided free of charge and are not warrantied for any specific use. We do not provide support or assistance in downloading or using these tools. We do, however, strive to produce high-quality tools and appreciate comments you have about them.

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 establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making.

   BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions.


   Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself.


   For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise.


   Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. 


   This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery.


   See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt


   See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt

The Viewshed analysis layer is used to identify visible areas. You specify the places you are interested in, either from a file or interactively, and the Viewshed service combines this with Esri-curated elevation data to create output polygons of visible areas. Some questions you can answer with the Viewshed task include:What areas can I see from this location? What areas can see me?Can I see the proposed wind farm?What areas can be seen from the proposed fire tower?The maximum number of input features is 1000.Viewshed has the following optional parameters:Maximum Distance: The maximum distance to calculate the viewshed.Maximum Distance Units: The units for the Maximum Distance parameter. The default is meters.DEM Resolution: The source elevation data; the default is 90m resolution SRTM. Other options include 30m, 24m, 10m, and Finest.Observer Height: The height above the surface of the observer. The default value of 1.75 meters is an average height of a person. If you are looking from an elevation location such as an observation tower or a tall building, use that height instead.Observer Height Units: The units for the Observer Height parameter. The default is meters.Surface Offset: The height above the surface of the object you are trying to see. The default value is 0. If you are trying to see buildings or wind turbines add their height here.Surface Offset Units: The units for the Surface Offset parameter. The default is meters.Generalize Viewshed Polygons: Determine if the viewshed polygons are to be generalized or not. The viewshed calculation is based upon a raster elevation model which creates a result with stair-stepped edges. To create a more pleasing appearance, and improve performance, the default behavior is to generalize the polygons. This generalization will not change the accuracy of the result for any location more than one half of the DEM's resolution.By default, this tool currently works worldwide between 60 degrees north and 56 degrees south based on the 3 arc-second (approximately 90 meter) resolution SRTM dataset. Depending upon the DEM resolution pick by the user, different data sources will be used by the tool. For 24m, tool will use global dataset WorldDEM4Ortho (excluding the counties of Azerbaijan, DR Congo and Ukraine) 0.8 arc-second (approximately 24 meter) from Airbus Defence and Space GmbH. For 30m, tool will use 1 arc-second resolution data in North America (Canada, United States, and Mexico) from the USGS National Elevation Dataset (NED), SRTM DEM-S dataset from Geoscience Australia in Australia and SRTM data between 60 degrees north and 56 degrees south in the remaining parts of the world (Africa, South America, most of Europe and continental Asia, the East Indies, New Zealand, and islands of the western Pacific). For 10m, tool will use 1/3 arc-second resolution data in the continental United States from USGS National Elevation Dataset (NED) and approximately 10 meter data covering Netherlands, Norway, Finland, Denmark, Austria, Spain, Japan Estonia, Latvia, Lithuania, Slovakia, Italy, Northern Ireland, Switzerland and Liechtenstein from various authoritative sources.To learn more, read the developer documentation for Viewshed or follow the Learn ArcGIS exercise called I Can See for Miles and Miles. To use this Geoprocessing service in ArcGIS Desktop 10.2.1 and higher, you can either connect to the Ready-to-Use Services, or create an ArcGIS Server connection. Connect to the Ready-to-Use Services by first signing in to your ArcGIS Online Organizational Account:Once you are signed in, the Ready-to-Use Services will appear in the Ready-to-Use Services folder or the Catalog window:If you would like to add a direct connection to the Elevation ArcGIS Server in ArcGIS for Desktop or ArcGIS Pro, use this URL to connect: https://elevation.arcgis.com/arcgis/services. You will also need to provide your account credentials. ArcGIS for Desktop:ArcGIS Pro:The ArcGIS help has additional information about how to do this:Learn how to make a ArcGIS Server Connection in ArcGIS Desktop. Learn more about using geoprocessing services in ArcGIS Desktop.This tool is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.

This map presents transportation data, including highways, roads, railroads, and airports for the world.

The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.