If you have geographic information stored as a table, ArcGIS Pro can display it on a map and convert it to spatial data. In this tutorial, you'll create spatial data from a table containing the latitude-longitude coordinates of huts in a New Zealand national park. Huts in New Zealand are equivalent to cabins in the United States—they may or may not have sleeping bunks, kitchen facilities, electricity, and running water. The table of hut locations is stored as a comma-separated values (CSV) file. CSV files are a common, nonproprietary file type for tabular data.Estimated time: 45 minutesSoftware requirements: ArcGIS Pro

what3words is an addressing and location reference system based on a global grid of 57 trillion squares of 3mx3m; each square has a unique pre-assigned 3 word address. For example, crayon.giants.liking is a perfect spot in the Grand Canyon to take a picture of the Kaibab Suspension Bridge across the Colorado River. Poor addressing is frustrating & costly in developed countries, and it hampers the growth and development of many nations around the world. Street addressing is irregular and incomplete; finding an address and communicating it to others is still a very imperfect science. Whilst coordinates work well for many GIS professionals, they are error-prone and badly understood by non-GIS users, which prohibits their more widespread use.

Addressing just got easier “Geographical information is a fundamental business tool. A simple way to communicate location is essential to unleash its full potential for everyone, what3words has solved a major aspect of that, particularly in geographies that are disadvantaged with lack of addressing and place name description data.” said Jack Dangermond, President of Esri. “Addressing has just got easier.” Technically flexible The simple what3words system is now available as a locator, accessible via the industry-leading ArcGIS platform from Esri. The locator allows ArcGIS platform users to display the 3 word address for any location or search for a 3 word address, either individually or via batch conversion to and from coordinates. It makes full use of the Esri Geoinformation Model and is accessible online or offline, anywhere in the world. The what3words locator can be configured at an organization level, whatever the ArcGIS deployment model, so that any roles and users can access it across the entire ArcGIS platform.

Words beat alphanumeric codes “Using 3 words instead of long sequences of coordinates or complicated alphanumeric codes means that people can identify any location accurately and communicate it more quickly, more easily and with less ambiguity.” Chris Sheldrick, CEO what3words. “Our conversations with Esri partners and users have been overwhelmingly positive and those who have participated in our beta trials are keen to introduce what3words throughout their workflow.” Human communication The what3words system is non-sequential and non-hierarchical to ensure human communication errors are intercepted. The system distributes similar 3 word addresses far apart, often in different countries, to allow manual or automated error detection in real time.

Better addressing for everyone Better addressing can significantly improve customer experiences for the navigation, logistics, post, utilities, census and data collection sectors where inaccuracies and friction towards coordinates cause erroneous data, incomplete data and ambiguity. Municipalities and governments exchanging geographic data with their citizens will also benefit by introducing a system which can be easily understood by the general population. The human-friendly nature of 3 word addresses combined with the scale and reach of ArcGIS means not only that everywhere now has a simple address, but that absolutely everyone can use it. Learn more and access the locator at what3words.com/esri.

USGS is assessing the feasibility of map projections and grid systems for lunar surface operations. We propose developing a new Lunar Transverse Mercator (LTM), the Lunar Polar Stereographic (LPS), and the Lunar Grid Reference Systems (LGRS). We have also designed additional grids designed to NASA requirements for astronaut navigation, referred to as LGRS in Artemis Condensed Coordinates (ACC), but this is not released here. LTM, LPS, and LGRS are similar in design and use to the Universal Transverse Mercator (UTM), Universal Polar Stereographic (LPS), and Military Grid Reference System (MGRS), but adhere to NASA requirements. LGRS ACC format is similar in design and structure to historic Army Mapping Service Apollo orthotopophoto charts for navigation. The Lunar Transverse Mercator (LTM) projection system is a globalized set of lunar map projections that divides the Moon into zones to provide a uniform coordinate system for accurate spatial representation. It uses a transverse Mercator projection, which maps the Moon into 45 transverse Mercator strips, each 8°, longitude, wide. These transverse Mercator strips are subdivided at the lunar equator for a total of 90 zones. Forty-five in the northern hemisphere and forty-five in the south. LTM specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large areas with high positional accuracy while maintaining consistent scale. The Lunar Polar Stereographic (LPS) projection system contains projection specifications for the Moon’s polar regions. It uses a polar stereographic projection, which maps the polar regions onto an azimuthal plane. The LPS system contains 2 zones, each zone is located at the northern and southern poles and is referred to as the LPS northern or LPS southern zone. LPS, like is equatorial counterpart LTM, specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large polar areas with high positional accuracy, while maintaining consistent scale across the map region. LGRS is a globalized grid system for lunar navigation supported by the LTM and LPS projections. LGRS provides an alphanumeric grid coordinate structure for both the LTM and LPS systems. This labeling structure is utilized in a similar manner to MGRS. LGRS defines a global area grid based on latitude and longitude and a 25×25 km grid based on LTM and LPS coordinate values. Two implementations of LGRS are used as polar areas require a LPS projection and equatorial areas a transverse Mercator. We describe the difference in the techniques and methods report associated with this data release. Request McClernan et. al. (in-press) for more information. ACC is a method of simplifying LGRS coordinates and is similar in use to the Army Mapping Service Apollo orthotopophoto charts for navigation. These data will be released at a later date. Two versions of the shape files are provided in this data release, PCRS and Display only. See LTM_LPS_LGRS_Shapefiles.zip file. PCRS are limited to a single zone and are projected in either LTM or LPS with topocentric coordinates formatted in Eastings and Northings. Display only shapefiles are formatted in lunar planetocentric latitude and longitude, a Mercator or Equirectangular projection is best for these grids. A description of each grid is provided below: Equatorial (Display Only) Grids: Lunar Transverse Mercator (LTM) Grids: LTM zone borders for each LTM zone Merged LTM zone borders Lunar Polar Stereographic (LPS) Grids: North LPS zone border South LPS zone border Lunar Grid Reference System (LGRS) Grids: Global Areas for North and South LPS zones Merged Global Areas (8°×8° and 8°×10° extended area) for all LTM zones Merged 25km grid for all LTM zones PCRS Shapefiles:` Lunar Transverse Mercator (LTM) Grids: LTM zone borders for each LTM zone Lunar Polar Stereographic (LPS) Grids: North LPS zone border South LPS zone border Lunar Grid Reference System (LGRS) Grids: Global Areas for North and South LPS zones 25km Gird for North and South LPS zones Global Areas (8°×8° and 8°×10° extended area) for each LTM zone 25km grid for each LTM zone The rasters in this data release detail the linear distortions associated with the LTM and LPS system projections. For these products, we utilize the same definitions of distortion as the U.S. State Plane Coordinate System. Scale Factor, k - The scale factor is a ratio that communicates the difference in distances when measured on a map and the distance reported on the reference surface. Symbolically this is the ratio between the maps grid distance and distance on the lunar reference sphere. This value can be precisely calculated and is provided in their defining publication. See Snyder (1987) for derivation of the LPS scale factor. This scale factor is unitless and typically increases from the central scale factor k_0, a projection-defining parameter. For each LPS projection. Request McClernan et. al., (in-press) for more information. Scale Error, (k-1) - Scale-Error, is simply the scale factor differenced from 1. Is a unitless positive or negative value from 0 that is used to express the scale factor’s impact on position values on a map. Distance on the reference surface are expended when (k-1) is positive and contracted when (k-1) is negative. Height Factor, h_F - The Height Factor is used to correct for the difference in distance caused between the lunar surface curvature expressed at different elevations. It is expressed as a ratio between the radius of the lunar reference sphere and elevations measured from the center of the reference sphere. For this work, we utilized a radial distance of 1,737,400 m as recommended by the IAU working group of Rotational Elements (Archinal et. al., 2008). For this calculation, height factor values were derived from a LOLA DEM 118 m v1, Digital Elevation Model (LOLA Science Team, 2021). Combined Factor, C_F – The combined factor is utilized to “Scale-To-Ground” and is used to adjust the distance expressed on the map surface and convert to the position on the actual ground surface. This value is the product of the map scale factor and the height factor, ensuring the positioning measurements can be correctly placed on a map and on the ground. The combined factor is similar to linear distortion in that it is evaluated at the ground, but, as discussed in the next section, differs numerically. Often C_F is scrutinized for map projection optimization. Linear distortion, δ - In keeping with the design definitions of SPCS2022 (Dennis 2023), we refer to scale error when discussing the lunar reference sphere and linear distortion, δ, when discussing the topographic surface. Linear distortion is calculated using C_F simply by subtracting 1. Distances are expended on the topographic surface when δ is positive and compressed when δ is negative. The relevant files associated with the expressed LTM distortion are as follows. The scale factor for the 90 LTM projections: LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_K_grid_scale_factor.tif Height Factor for the LTM portion of the Moon: LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_EF_elevation_factor.tif Combined Factor in LTM portion of the Moon LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_CF_combined_factor.tif The relevant files associated with the expressed LPS distortion are as follows. Lunar North Pole The scale factor for the northern LPS zone: LUNAR_LGRS_NP_PLOT_LPS_K_grid_scale_factor.tif Height Factor for the north pole of the Moon: LUNAR_LGRS_NP_PLOT_LPS_EF_elevation_factor.tif Combined Factor for northern LPS zone: LUNAR_LGRS_NP_PLOT_LPS_CF_combined_factor.tif Lunar South Pole Scale factor for the northern LPS zone: LUNAR_LGRS_SP_PLOT_LPS_K_grid_scale_factor.tif Height Factor for the south pole of the Moon: LUNAR_LGRS_SP_PLOT_LPS_EF_elevation_factor.tif Combined Factor for northern LPS zone: LUNAR_LGRS_SP_PLOT_LPS_CF_combined_factor.tif For GIS utilization of grid shapefiles projected in Lunar Latitude and Longitude, referred to as “Display Only”, please utilize a registered lunar geographic coordinate system (GCS) such as IAU_2015:30100 or ESRI:104903. LTM, LPS, and LGRS PCRS shapefiles utilize either a custom transverse Mercator or polar Stereographic projection. For PCRS grids the LTM and LPS projections are recommended for all LTM, LPS, and LGRS grid sizes. See McClernan et. al. (in-press) for such projections. Raster data was calculated using planetocentric latitude and longitude. A LTM and LPS projection or a registered lunar GCS may be utilized to display this data. Note: All data, shapefiles and rasters, require a specific projection and datum. The projection is recommended as LTM and LPS or, when needed, IAU_2015:30100 or ESRI:104903. The datum utilized must be the Jet Propulsion Laboratory (JPL) Development Ephemeris (DE) 421 in the Mean Earth (ME) Principal Axis Orientation as recommended by the International Astronomy Union (IAU) (Archinal et. al., 2008).

This Africa Geocoding locator is a view of the World Geocoding Service constrained to search for places in the countries of Africa. The World Geocoding Service finds addresses and places in all supported countries around the world in a single geocoding service. The service can find point locations of addresses, cities, landmarks, business names, and other places. The output points can be visualized on a map, inserted as stops for a route, or loaded as input for a spatial analysis.The service is available as both a geosearch and geocoding service:Geosearch Services – The primary purpose of geosearch services is to locate a feature or point of interest and then have the map zoom to that location. The result might be displayed on the map, but the result is not stored in any way for later use. Requests of this type do not require a subscription or a credit fee. Geocoding Services – The primary purpose of geocoding services is to convert an address to an x,y coordinate and append the result to an existing record in a database. Mapping is not always involved, but placing the results on a map may be part of a workflow. Batch geocoding falls into this category. Geocoding requires a subscription. An ArcGIS Online subscription will provide you access to the World Geocoding service for batch geocoding.The service can be used to find address and places for many countries around the world. For detailed information on this service, including a data coverage map, visit the World Geocoding service documentation.

This dataset comes from the Department of Licensing and Regulatory Affairs' Office of Land Survey and Remonumentation (OLSR). See Act 345 of 1990: State Survey and Remonumentation Act for more information.The system of record was queried for approved locations where grid coordinates were provided. Records with coordinates outside the state's geographical boundary were retained (34 locations). The columns "DMS LAT" and "DMS LONG" were added to the extraction table and populated with data from fields "Latitude N" and "Longitude W" and formatted to DMS2. The data was exported as feature class using geoprocessing tool "Convert Coordinate Notation," geographic coordinate system WGS 1984 Web Mercator (auxiliary sphere).This dataset was last updated June 6, 2022, with quarterly updates to begin in 2023.More Metadata

Myanmar pearl cultivation licence data as geodata based on 6th MEITI Data Summary Report (FY2018) annex. (https://myanmareiti.org/sites/myanmareiti.org/files/publication_docs/license_information1st_april_to_30_september2018.xlsx). It includes all reported pearl cultivation licence areas in the 6th MEITI Data Summary Report. This dataset includes the original and cleaned data columns and geodata for licence block boundary coordinates and licence areas. The coordinates nevertheless are not the true boundary coordinates as in the contract but merely a "bounding box" defined by 4 coordinates. Thus this dataset is only a very rough approximation of the true location of the pearl cultivation licence areas. This dataset includes the original and cleaned data columns. Additional processing attributes were added during the data generation by us. The detailed description of attribute fields can be found in attached metadata attributes excel sheet.Lineage:Version 2022-07-15: updated Metadata and attribute namesVersion 2021-07-01:Data downloaded from MEITI https://myanmareiti.org/sites/myanmareiti.org/files/publication_docs/license_information1st_april_to_30_september2018.xlsx on 2021-05-01.Data columns cleaned and standardized by P. Oswald (obvious typos corrected, removal of whitespaces and line breaks, standardize value domains where possible, etc.).Matching of descriptive location information with island names from topographic maps where possible.Geometry created based on coordinate information columns by conversion of coordinate values to GIS data and connecting the coordinates with straight lines (in ArcMap using SRS EPSG4326) to pearl cultivation licence area polygons.Linking the MEITI 6th report attribute data to the licence block geometries.As P. Oswald (as well as MEITI) has no access to the underlying individual licence contracts nor other verified reference data, the completeness and correctness of the data and cross-checking or reliable corrections cannot be undertaken. Preliminary assessments indicate that many coordinates in the licence information annex are simplified, inaccurate, wrong or completely missing.Thus, the generated licence geodata data inherits those data quality problems. In some cases P. Oswald corrected obviously wrong coordinates using a “best-guess” approach.

This data contains a set of geodetic control stations maintained by the National Geodetic Survey. Each geodetic control station in this dataset has either a precise Latitude/Longitude used for horizontal control or a precise Orthometric Height used for vertical control, or both. The National Geodetic Survey (NGS) serves as the Nation's depository for geodetic data. The NGS distributes geodetic data worldwide to a variety of users. These geodetic data include the final results of geodetic surveys, software programs to format, compute, verify, and adjust original survey observations or to convert values from one geodetic datum to another, and publications that describe how to obtain and use Geodetic Data products and services.

The following dataset includes "Active Benchmarks," which are provided to facilitate the identification of City-managed standard benchmarks. Standard benchmarks are for public and private use in establishing a point in space. Note: The benchmarks are referenced to the Chicago City Datum = 0.00, (CCD = 579.88 feet above mean tide New York). The City of Chicago Department of Water Management’s (DWM) Topographic Benchmark is the source of the benchmark information contained in this online database. The information contained in the index card system was compiled by scanning the original cards, then transcribing some of this information to prepare a table and map. Over time, the DWM will contract services to field verify the data and update the index card system and this online database.This dataset was last updated September 2011. Coordinates are estimated. To view map, go to https://data.cityofchicago.org/Buildings/Elevation-Benchmarks-Map/kmt9-pg57 or for PDF map, go to http://cityofchicago.org/content/dam/city/depts/water/supp_info/Benchmarks/BMMap.pdf. Please read the Terms of Use: http://www.cityofchicago.org/city/en/narr/foia/data_disclaimer.html.

This data set provides information about wells in the State of Missouri. The parent data set is the Wellhead Information Management System (WIMS) database that is maintained by the Missouri Geological Survey (MGS), Geological Survey Program (GSP), Wellhead Protection Section (WHP). The WIMS database resulted from implementation of the Water Well Drillers Law of 1985. The information about well location, well ownership, well completion date, well construction, well yield, static water level and borehole stratigraphy is provided by well drillers, as required by state statute RSMo 256.600-256.640. Wells drilled prior to July of 1987 are not included in this data set. A new WIMS well search is also available online at www.dnr.mo.gov/mowells/

Potential location errors may be present due to conversion of legal description to GPS coordinates. The well owner listed on a well record is the original owner. Ownership changes are not tracked. All information changes will occur on an annual basis during scheduled data updates.

Use the Sidebar template to include a set of tools and options that appear in a side panel next to the map. You can enable editing tools to allow users to add and update features in the map. Configure filters that app users can use to gain more information about your data. Include bookmarks to guide your users to important regions and add essential map tools for exploring the map. Examples: Showcase a detailed map of population data with supplementary text for further explanation. Allow data reviewers to investigate and update records with editing tools. Present public services in a map that your audience can filter for the types of services they need. Data requirements The Sidebar template has no specific data requirements. To use the Oriented imagery tool, the web map must have an oriented imagery layer. Key app capabilities Cover page - Include a cover page with custom text and logos to establish the purpose of the app. Edit tools - Provide options to add and update features in editable layers. Users can turn on snapping for more efficient and precise editing. Attribute filter - Configure map filter options that are available to app users. Bookmarks - Allow users to zoom and pan to a collection of preset extents that are saved in the map. Export - Print or export the search results or selected features as a .pdf, .jpg, or .png file that includes the pop-up content of returned features and an option to include the map. Measurement tools - Provide tools that measure distance and area and find and convert coordinates. 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.

Since 1984, the New Jersey Bureau of Marine Fisheries (BMF) has coordinated and held the permits for an intensive program of artificial reef construction and biological monitoring off the coast of New Jersey. The purpose is to create a network of artificial reefs in the ocean waters along the New Jersey coast to provide a hard substrate for fish, shellfish and crustaceans, fishing grounds for anglers, and underwater structures for scuba divers. Within each reef site, which range in size from one-half to over four square miles, numerous deployments or "patch reefs" have been constructed. A patch reef is an area within a reef site boundary where material has been deployed. In total, over 4000 patch reefs have been constructed on the state's 17 reef sites since the program began. Reefs are used extensively by anglers and divers who catch summer flounder, winter flounder, ling, black sea bass, tautog, scup, and lobster along with a myriad of other species.Deployments most often consist of three material types; concrete, rock, and metals. These deployments are frequently old bridges, dredge rock, or ships which have all been repurposed as artificial habitat. Over time, these materials become encrusted and a living reef matrix envelopes the structure. This matrix can be several layers thick as different types of encrusters compete for an available toehold, often growing on top of each other. At this stage of reef development, a multitude of minute organisms take up residence in this protective matrix and form an important component of the food chain. Deployed reef structure not only leads to more food for marine fish, but also increases the energy efficiency of reef feeding by dissipating underwater currents. The structure acts as a baffle, reducing current along the bottom, which allows energy from food to be used for growth rather than exertion. Additionally, as water flows over and around reef structure, eddies form, which carry food to waiting fishes.The DGPS coordinates upon which this GIS data is based were obtained through direct observation, i.e. by finding each structure at sea and then recording its exact location from LORAN C and DGPS receivers. Older patch reef coordinates were obtained using LORAN C devices. More recent reef drops were recorded with DGPS machines. To convert the earlier reef deployment coordinates that were obtained solely from LORAN C devices into DPGS, two techniques were used. Most of the conversions were obtained by on-site observations. If an on-site observation was not possible, mathematical equations were used to convert from Loran C into DGPS. Unfortunately, while close, these conversions are usually not accurate enough to find reef structures. The exact locations of structures can usually be found by using a wreck search patterns.This dataset includes all deployments located at reef sites and installed between 1905-2016 as well as deployments installed after 2016 which were sponsored.

The feature class comprises points and data generated/translatedfrom an excel spreadsheet containing bathymetric information fromvarious Land & Water Board public registries. Additional water licences were identified, reviewed, and incorporated into the spreadsheet during the review process against all files on the Public Registry.The public registry sources are listed below:Inuvialuit Water BoardGwich’in Land and Water BoardSahtu Land and Water BoardWek’eezhi Land and Water BoardTransboundary LicencesMackenzie Valley Land and Water BoardBathymetric information was collected by proponents under the NWT regulatory system and is contained within individual project files on the Land and Water Board (LWB) Public Registries. The data has been used for calculating water source capacity for water withdrawals and completing fish habitat assessments. Data compilation occurred in stages by Region and Activity. The first phase was completed in 2022, including available information from several Regions and Activities. The second phase includes the remainder of the Mackenzie Valley Land and Water Board activities and additional Water Licences added to the Public Registry after Phase 1.Data collection followed a common protocol. The LWB Public Registry website was accessed and filtered by Region, Authorization, and Activity. Each Water Licence webpage was then accessed and searched for bathymetric data. Information collected for each water source includes regulating Land and Water Board, project and water licence number, report reference, preparer, collection date, water body name, coordinates, surface area, maximum depth, average depth, ice depth, lake volume, volume of ice, and lake volume under ice cover. Estimated data is indicated as such within the spreadsheet. The data has been spot-checked for accuracy, with approximately 10% of hyperlinks tested and data checked for coordinate conversion and transcription errors. An Excel spreadhseet was created containing bathymetric information.This excel contained coordinate information that was used to spatialize the points of this data into this feature class. Pertinent attributes were included during this spatialization, some standardization was applied to different values of this data. I.e. Changing any Proponent value that had some variation of GNWT & INF(GNWT - INF, GNWT INF, GNWT Infrastructrure, etc.) to 'GNWT-INF", or fixing spelling errors in data values like 'Exporation' to "Exploration"and "Resurces" to "Resources". No data values were altered in a way that would reflect anything different than what was there originally.

This downloadable zip file contains an ESRI File Geodatabase (FGDB) that is compatible with most versions of ArcGIS Pro, ArcMap, and AutoCAD Map 3D or Civil 3D. To view the geodatabase’s contents, please download the zip file to a local directory and extract its contents. This zipped geodatabase will require approximately 2.85 GB of disc space (3.09 GB extracted). Due to its size, the zip file may take some time to download.This topographic contour layer was derived from LiDAR collected in spring of 2018 by Dewberry Engineers in coordination with Tallahassee - Leon County GIS. The contours were extracted at a 2 foot interval with index contours every 10 feet. Lidar Acquisition Executive SummaryThe primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (lidar) technology for the Tallahassee Leon County Project Area. The lidar data were processed and classified according to project specifications. Detailed breaklines and bare-earth Digital Elevation Models (DEMs) were produced for the project area. Data was formatted according to tiles with each tile covering an area of 5000 ft by 5000 ft. A total of 876 tiles were produced for the project encompassing an area of approximately 785.55 sq. miles.THE PROJECT TEAMDewberry served as the prime contractor for the project. In addition to project management, Dewberry was responsible for LAS classification, all lidar products, breakline production, Digital Elevation Model (DEM) production, and quality assurance. Dewberry’s Frederick C. Rankin completed ground surveying for the project and delivered surveyed checkpoints. His task was to acquire surveyed checkpoints for the project to use in independent testing of the vertical accuracy of the lidar-derived surface model. He also verified the GPS base station coordinates used during lidar data acquisition to ensure that the base station coordinates were accurate. Please see Appendix A to view the separate Survey Report that was created for this portion of the project. Digital Aerial Solutions, LLC completed lidar data acquisition and data calibration for the project area.SURVEY AREAThe project area addressed by this report falls within the Florida county of Leon.DATE OF SURVEYThe lidar aerial acquisition was conducted from February 05, 2018 thru April 25, 2018.ORIGINAL COORDINATE REFERENCE SYSTEMData produced for the project were delivered in the following reference system.Horizontal Datum: The horizontal datum for the project is North American Datum of 1983 with the 2011 Adjustment (NAD 83 (2011))Vertical Datum: The Vertical datum for the project is North American Vertical Datum of 1988 (NAVD88)Coordinate System: NAD83 (2011) State Plane Florida North (US survey feet)Units: Horizontal units are in U.S. Survey Feet, Vertical units are in U.S. Survey Feet.Geiod Model: Geoid12B (Geoid 12B) was used to convert ellipsoid heights to orthometric heights).

This topographic contour layer was derived from LiDAR collected in spring of 2020 by Dewberry Engineers in coordination with Tallahassee - Leon County GIS. The contours were extracted at a 2 foot interval with index contours every 10 feet. This tile layer was generated as a Map Tile Package (.mtpkx) in ArcGIS Pro and published to ArcGIS online as a hosted tile layer. For web mapping compatibility, this layer has been re-projected from its original coordinate system to the web standard used by ESRI, Google, and Bing (Web Mercator Auxiliary Sphere).The feature layer used to generate this tile layer can be downloaded as a zipped geodatabase from TLCGIS' geodatahub. Download LinkLidar Acquisition Executive SummaryThe primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (lidar) technology for the Tallahassee Leon County Project Area. The lidar data were processed and classified according to project specifications. Detailed breaklines and bare-earth Digital Elevation Models (DEMs) were produced for the project area. Data was formatted according to tiles with each tile covering an area of 5000 ft by 5000 ft. A total of 876 tiles were produced for the project encompassing an area of approximately 785.55 sq. miles.The Project TeamDewberry served as the prime contractor for the project. In addition to project management, Dewberry was responsible for LAS classification, all lidar products, breakline production, Digital Elevation Model (DEM) production, and quality assurance. Dewberry’s Frederick C. Rankin completed ground surveying for the project and delivered surveyed checkpoints. His task was to acquire surveyed checkpoints for the project to use in independent testing of the vertical accuracy of the lidar-derived surface model. He also verified the GPS base station coordinates used during lidar data acquisition to ensure that the base station coordinates were accurate. Please see Appendix A to view the separate Survey Report that was created for this portion of the project. Digital Aerial Solutions, LLC completed lidar data acquisition and data calibration for the project area.SURVEY AREAThe project area addressed by this report falls within the Florida county of Leon.DATE OF SURVEYThe lidar aerial acquisition was conducted from TBDORIGINAL COORDINATE REFERENCE SYSTEMData produced for the project were delivered in the following reference system.Horizontal Datum: The horizontal datum for the project is North American Datum of 1983 with the 2011 Adjustment (NAD 83 (2011))Vertical Datum: The Vertical datum for the project is North American Vertical Datum of 1988 (NAVD88)Coordinate System: NAD83 (2011) State Plane Florida North (US survey feet)Units: Horizontal units are in U.S. Survey Feet, Vertical units are in U.S. Survey Feet.Geiod Model: Geoid12B (Geoid 12B) was used to convert ellipsoid heights to orthometric heights).

LEOWEB 11 is a tool to convert geographic coordinates to PLSS legal land descriptions. The project is hosted at the Kansas Geological Survey and has been funded by Kansas GIS Policy Board and the Kansas Geological Survey. It is not a surveying tool and only provides an approximate conversion. The application runs via contemporary web browsers with server side interaction thru the Oracle APEX 4.0 environment.

Individual boundary polylines were created by first making a point shapefile of the line endpoints or a series of points, then converting the points to a polyline. The point/polyline conversion was done using XTools 'Make One Polyline from Points' tool. Point locations were based on latitude/longitude coordinates given in the technical report or geographic landmark (i.e. islands, points, state/international boundary lines, etc.). Points requiring an azimuth bearing were created in a projected view (UTM Zone 17 NAD27) using the Distance and Azimuth Tools v. 1.6 extension developed by Jenness Enterprises.The polyline shapefiles created in step 1 and an existing polyline shapefile of the international boundary were merged together using the ArcView GeoProcessing Wizard.The shapefile generated in step 2 was converted to a line coverage using the ArcToolbox Conversion Tools - Feature Class to Coverage.The line coverage topology was cleaned and updated using the ArcInfo Workstation CLEAN (dangle length and fuzzy tolerance both set to 0.001) and BUILD commands.The boundary line coverage and an existing Lake Erie shoreline shapefile (derived from ESRI 100k data) were merged together using the ArcView GeoProcessing Wizard.The shapefile generated in step 5 was converted to a line coverage using the ArcToolbox Conversion Tools - Feature Class to Coverage.Topology of the boundary/shoreline coverage was cleaned and updated using the ArcInfo Workstation CLEAN (dangle length and fuzzy tolerance both set to 0.00001) and BUILD commands. BUILD was done for both line and polygon topology.The polygon feature from the coverage generate in step 7 was converted to a shapefile using Theme\Convert to Shapefile in ArcView.

Metadata:I, J, and Object ID are references for the modeling, they can be ignored when viewing/mapping the data. Latitude and longitude are the coordinates of each data cell. del_2013_int1 through del_2016_int7 is the difference in degrees Celsius from the unmitigated UHI base case. For each year of meteorological data, there are 7 intervals. It is formatted as such: del_year of weather data used in the model_inteval #Note: This is a temperature DIFFERENCE, so to convert to Fahrenheit you must multiply by 1.8.

The Gilpin County Parcel Fabric provides a single source of titled and surveyed lands in Gilpin County, Colorado. This dataset is best viewed through the Gilpin County Parcel Fabric Viewer.Gilpin County is in the early stages of rebuilding all surveyed lands within the County. This is complicated by significant known positional errors in the BLM Cadastre of 1 to 300-meters on section corners along with information that has been lost over the last 150 years. The current focus is the residential core of Gilpin County and Central City. It is expected that this project will take several years to complete. Every attempt is made to enter the data as accurately as possible. THIS DATA IS NOT SURVEY-GRADE. It is intended to assist surveyors to locate monuments in the field and provide historical context for properties, when possible. The Records layer contains valuable information in the Notes field for any assumptions or alterations made to the conversion of surveys to GIS. NOTE TO SURVEYORS: To accurately calculate the ground-to-grid conversion of your plats, please submit the XYZ coordinates of the Basis of Bearing monuments in Colorado State Plane North, NAD83 (NAVD88 for Z), U.S. Survey Feet on your plat. Thank you.

Metadata:I, J, and Object ID are references for the modeling, they can be ignored when viewing/mapping the data. Latitude and longitude are the coordinates of each data cell. 2013_int1 through 2016_int7 is the difference in degrees Celsius from the unmitigated UHI base case. For each year of meteorological data, there are 7 intervals. It is formatted as such: year of weather data used in the model_inteval# The intervals represent the following time periods:Interval 1: June 1 – 15; Interval 2: June 16 – 30; Interval 3: July 1 – 15; Interval 4: July 16 – 31;Interval 5: August 1 – 15; Interval 6: August 16 – 31; and Interval 7: September 1 – 15.Conversion note: This is a temperature DIFFERENCE, so to convert to Fahrenheit you must multiply by 1.8.

WARNING: The download for the File Geodatabase is having issues with the parcel data. Instead, download the GeoJSON file and then use the ArcGIS GeoJSON to Features tool to convert the data. Sorry for the inconvenience.Parcel polygon data with parcel numbers and lat/lon centroid coordinates.To understand parcel numbers, see the following document at https://assessor.venturacounty.gov/site/assets/files/1643/instructions_for_identifying_assessor.pdf .Looking for Assessor attribute data? You can obtain secured roll data from the Ventura County Assessor. You will need to make a public records request and fill out a public info agreement contract at https://assessor.venturacounty.gov/assessor-data/public-records-request/. For more information you can contact the Assessor at https://assessor.venturacounty.gov/about-us/office-contact-info/.