MCGD_Data_V2.2 contains all the data that we have collected on locations in modern China, plus a number of locations outside of China that we encounter frequently in historical sources on China. All further updates will appear under the name "MCGD_Data" with a time stamp (e.g., MCGD_Data2023-06-21)

You can also have access to this dataset and all the datasets that the ENP-China makes available on GitLab: https://gitlab.com/enpchina/IndexesEnp

Altogether there are 464,970 entries. The data include the name of locations and their variants in Chinese, pinyin, and any recorded transliteration; the name of the province in Chinese and in pinyin; Province ID; the latitude and longitude; the Name ID and Location ID, and NameID_Legacy. The Name IDs all start with H followed by seven digits. This is the internal ID system of MCGD (the NameID_Legacy column records the Name IDs in their original format depending on the source). Locations IDs that start with "DH" are data points extracted from China Historical GIS (Harvard University); those that start with "D" are locations extracted from the data points in Geonames; those that have only digits (8 digits) are data points we have added from various map sources.

One of the main features of the MCGD Main Dataset is the systematic collection and compilation of place names from non-Chinese language historical sources. Locations were designated in transliteration systems that are hardly comprehensible today, which makes it very difficult to find the actual locations they correspond to. This dataset allows for the conversion from these obsolete transliterations to the current names and geocoordinates.

From June 2021 onward, we have adopted a different file naming system to keep track of versions. From MCGD_Data_V1 we have moved to MCGD_Data_V2. In June 2022, we introduced time stamps, which result in the following naming convention: MCGD_Data_YYYY.MM.DD.

UPDATES

MCGD_Data2023.12.22 contains all the data that we have collected on locations in China, whatever the period. Altogether there are 465,603 entries (of which 187 place names without geocoordinates, labelled in the Lat Long columns as "Unknown"). The dataset also includes locations outside of China for the purpose of matching such locations to the place names extracted from historical sources. For example, one may need to locate individuals born outside of China. Rather than maintaining two separate files, we made the decision to incorporate all the place names found in historical sources in the gazetteer. Such place names can easily be removed by selecting all the entries where the 'Province' data is missing.

This is the data repository for the PLOS ONE Manuscript: "Meeting radiation dosimetry capacity requirements of population-scale exposures by geostatistical sampling". This repository contains the following data:

1. "State-and-Subdivision-Boundary-Files.Edited-for-ArcMap-10.4.KML-Format.zip":

This file contains modified U.S. state and sub-division boundary files [in KML format], which can be imported into ArcMap using its KMLtoLayer function. These files have been modified to prevent sub-division naming issues that we encountered when importing boundary data into ArcMap: A) State sub-divisions with identical names are considered a single sub-division by ArcMap (corrected by adding a letter after each sub-division of the same name, i.e. CenterA, CenterB, etc), and; B) ArcMap would only identify the sub-division by its first word if sub-division name contained spaces (corrected by converting all spaces into dashes).

1. "HPAC-Plumes.Processed.zip" and "HPAC-Plumes.Unprocessed.zip":

These files contain HPAC plume coordinate (WGS1984) and dose (in cGy) values for all scenarios discussed in the manuscript. We provide "processed" and "unprocessed" HPAC plume data files. The "unprocessed" HPAC plume data is provided in its original XML format, which cannot be imported into ArcMap directly. The "processed" HPAC plumes are provided in tab-delimited X,Y,Z format (Latitude, Longitude, and Dose). We have also added a "0 cGy" contour in the "processed" plumes (surrounding the HPAC plume), as the presence of unirradiated data points adjacent to the plume was found to be crucial for accurate kriging, since these points served as boundaries for kriging.

1. "Final-Derived-Plumes.Data-Points.zip":

This file contains geostatistically-derived plume coordinate (WGS1984) and dose (in cGy) values for all scenarios discussed in the manuscript. Data is in comma-delimited format (Latitude, Longitude, and Dose). Data points consist of a set of initial coordinates generated at random locations within each Census sub-division using the ArcMap tool, ‘CreateRandomPoints_management’, and subsequent points generated by densification (the geostatistical procedure that targets and localizes an additional small cohort of irradiated individuals to mitigate uncertainty in environmental measurements). These data points were assigned radiation level values corresponding to the adjacent outer HPAC contour by a script comparing each sample with its location within the HPAC plume of the same scenario.

1. “Intermediate-Derived-Plumes.Data-Points.zip”

This archive contains coordinate data (WGS1984) and dose values (in cGy) for all intermediary steps of plume development (using our geostatistical method) for all scenarios. Like (3), the data is comma-delimited (Latitude, Longitude, and Dose), and were assigned radiation level values by a script comparing sampling locations with the location of the HPAC plume of the same scenario. Scenario replicate folders contains text files for each iteration step of the plume derivation process, including a file containing just the initial random sampling (“Iteration-1”), a file containing initial sampling and sampling locations selected by the first densification step (“Iteration-2”), a file containing initial sampling and sampling locations selected by the first and second densification steps (“Iteration-3”), and so on.

This archive also contains a Table (“Progression-of-New-Densification-Selected-Sampling-Locations-For-All-Scenarios.xslx”) which provides a categorical breakdown of how many unique densification-selected sampling locations occur within the irradiated region (i.e. overlap the HPAC plume) for each iteration of all scenario replicates. The fraction of irradiated to unirradiated sampling locations varies among each scenario and individual replicates for the same scenario. Our analysis shows that these results depend on the population densities and exact topography of the HPAC plume which is different among each scenario.

1. "Geostatistical-Sampling-Project.All-Scripts.zip"

This archive contains all programs required for this project. This includes Python scripts meant to be run within the ArcMap software environment (for random point generation and data extraction), and Perl scripts used to process HPAC and U.S. State and Sub-division boundary files, and to assign radiation values to sample locations based on a modified HPAC plume. A java program, “CompareReplicates.jar”, compares the overlapping areas between a pair of polygons that overlap one other using the ArcMap software environment, and requires access to the ArcGIS Runtime SDK (https://developers.arcgis.com/arcgis-runtime/).

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.

Last update: October 16, 2025 OverviewThis point data was generated and filtered from OpenStreetMap and is intended to represent places of interest in the state of Utah. These may include businesses, restaurants, places of worship, airports, parks, schools, event centers, apartment complexes, hotels, car dealerships…almost anything that you can find in OpenStreetMap (OSM). There are over 23,000 features in the original dataset (March 2022) and users can directly contribute to it through openstreetmap.org. This data is updated approximately once every month and will likely continue to grow over time with user activity. Data SourcesThe original bulk set of OSM data for the state of Utah is downloaded from Geofabrik: https://download.geofabrik.de/north-america/us/utah-latest-free.shp.zipAdditional attributes for the Utah features are gathered via the Overpass API using the following query: https://overpass-turbo.eu/s/1geRData Creation ProcessThe Open Source Places layer is created by a Python script that pulls statewide OSM data from a nightly archive provided by Geofabrik (https://www.geofabrik.de/data/download.html). The archive data contains nearly 20 shapefiles, some that are relevant to this dataset and some that aren't. The Open Source Places layer is built by filtering the polygon and point data in those shapefiles down to a single point feature class with specific categories and attributes that UGRC determines would be of widest interest. The polygon features (buildings, areas, complexes, etc.) are converted to points using an internal centroid. Spatial filtering is done as the data from multiple shapefiles is combined into a single layer to minimize the occurrence of duplicate features. (For example, a restaurant can be represented in OSM as both a point of interest and as a building polygon. The spatial filtering helps reduce the chances that both of these features are present in the final dataset.) Additional de-duplication is performed by using the 'block_id' field as a spatial index, to ensure that no two features of the same name exist within a census block. Then, additional fields are created and assigned from UGRC's SGID data (county, city, zip, nearby address, etc.) via point-in-polygon and near analyses. A numeric check is done on the 'name' field to remove features where the name is less than 3 characters long or more than 50% numeric characters. This eliminates several features derived from the buildings layer where the 'name' is simply an apartment complex building number (ex: 3A) or house number (ex: 1612). Finally, additional attributes (osm_addr, opening_hours, phone, website, cuisine, etc.) are pulled from the Overpass API (https://wiki.openstreetmap.org/wiki/Overpass_API) and joined to the filtered data using the 'osm_id' field as the join key. Field Descriptionsaddr_dist - the distance (m) to the nearest UGRC address point within 25 mosm_id - the feature ID in the OSM databasecategory - the feature's data class based on the 4-digit code and tags in the OSM databasename - the name of the feature in the OSM databasecounty - the county the feature is located in (assigned from UGRC's county boundaries)city - the city the feature is located in (assigned from UGRC's municipal boundaries)zip - the zip code of the feature (assigned from UGRC's approximation of zip code boundaries)block_id - the census block the feature is located in (assigned from UGRC's census block boundaries)ugrc_addr - the nearest address (within 25 m) from the UGRC address point databasedisclaimer - a note from UGRC about the ugrc_near_addr fieldlon - the approximate longitude of the feature, calculated in WGS84 EPSG:4326lat - the approximate latitude of the feature, calculated in WGS84 EPSG:4326amenity - the amenity available at the feature (if applicable), often similar to the categorycuisine - the type of food available (if applicable), multiple types are separated by semicolons (;)tourism - the type of tourist location, if applicable (zoo, viewpoint, hotel, attraction, etc.)shop - the type of shop, if applicablewebsite - the feature's website in the OSM database, if availablephone - the feature's phone number(s) in the OSM database, if availableopen_hours - the feature's operating hours in the OSM database, if availableosm_addr - the feature's address in the OSM database, if availableMore information can be found on the UGRC data page for this layer:https://gis.utah.gov/data/society/open-source-places/

SLKs or Straight Line Kilometers are a location reference system used by Main Roads Western Australia to define the location of features or events along a road. This layer shows SLK points (every 100m) along the left and single carriageways for all State and Local Roads, Main Roads controlled paths contained within the road centreline of Main Roads road asset database. The purpose of this layer is to identify and label the measure of SLK along a particular route and is provided for information only. The SLK points are based on geometric measure and include points of equation. This means that you may notice “jumps” in the SLK between two points that are not equal to 100m. This is as a result of network changes that have been incorporated into the spatial road centr eline.A point of equation is a business term used to describe a point on the road network, which has two SLK references, one for the section leading up to it, and one for the section leaving from it. A Point of Equation is either: • A gap, which occurs when the new deviation/realignment is built shorter than the existing road. An SLK range is missing. • An overlap, which occurs when the new deviation/realignment is built longer than the existing road. An SLK range is duplicatedNote that you are accessing this data pursuant to a Creative Commons (Attribution) Licence, which has a disclaimer of warranties and limitation of liability. You accept that the data provided pursuant to the Licence is subject to changes. Pursuant to section 3 of the Licence you are provided with the following notice to be included when you Share the Licenced Material:- The Commissioner of Main Roads is the creator and owner of the data and Licenced Material, which is accessed pursuant to a Creative Commons (Attribution) Licence, which has a disclaimer of warranties and limitation of liability. Creative Commons CC BY 4.0Data Dictionary

Field Name
Type
Description


ObjectID
OID
System generated unique number, overridden on data update


Shape
Point M
System generated identifier for shape type


RoadCway
Text,255
Concatenation of Main Roads Road Number and Carriageway columns. Used to generate unique routes per road carriageway combination.


SLKMin
Double
The maximum SLK (measure) of the RoadCway


SLKMax
Double
The maximum SLK (measure) of the RoadCway


SLKGen
Double
The SLK measure generated at 100m intervals (0.1, 0.2 etc..)


POINT_X
Double
The Longitude of the SLK point


POINT_Y
Double
The latitude of the SLK point


StreetviewURL
Text.100
A Google Maps Streeview URL link to the SLK point on the road


RoadSLK
Text,50
A concatenation of the RoadCway and SLKGen columns


Road_Name
Text, 80
The Main Roads route name of the road


Common_Usage_Name
Text, 80
The name of the road


RN_SLK
Text, 100
A concatenation of the Road_Name and SLKGen columns


CN_SLK
Text, 100
A concatenation of the Common Usage Name and SLKGen columns

Colorado Community Anchor Institutions (CAI) Feature Class Summary This layer represents the National Telecommunications Information Administration (NTIA) State Broadband Data Development Program (SBDD) Community Anchor Institutions (CAI) which subscribe to broadband. Description Introduction This layer represents the National Telecommunications Information Administration (NTIA) State Broadband Data Development Program (SBDD) Community Anchor Institutions (CAI) which subscribe to broadband. ''Community Anchor Institutions'' consist of schools, libraries, medical and healthcare providers, public safety entities, community colleges and other institutions of higher education, and other community support organizations and entities. These locations may not offer broadband availability to the public (although most libraries and many schools, and community centers do) but rather offer an opportunity for policy makers to understand where community anchor institutions who have broadband access are which can help in identifying challenges and opportunities to reaching national connectivity goals. For additional information visit NOFA (Notice of Funding Availability) website: http://www.ntia.doc.gov/broadbandgrants/nofa.html Intent The primary source of information has been online address and location research, in combination with google maps and NAIP aerial imagery. Ideally, our end goal is to have every county maintain and provide data directly. The advantage being that local officials have more direct access to acquiring accurate data for their respective counties, and more experience within these counties. Secondly, it will allow each county to sustain accurate CAI data without being reliant on the state government. For example, if Hinsdale county sustained its own CAIs, it would not need to wait on the state to complete and update their CAI data. Achieving this goal will provide the counties in Colorado with accurate and useful data without the limitations of being bottle necked by a single data editing source. Process The existing CAI point data is edited and maintained using ESRI Arc Desktop 10.1. Points have first been verified for their spatial accuracy. They are overlayed onto NAIP aerial imagery. Using a combination of online sources, such as Google Maps and Google Earth, the address and location of each point is verified. If the point is inaccurately positioned, it is moved to the correct location. Attributes are also check for accuracy and updated. Sometimes street names or address numbers are not present, and must be identified through research. Presently a total of 5478 CAI locations have been researched and edited. We were unable to indentify the definitive location of 4% of these CAIs. This results in a favorable 96% accuracy rate thus far. This dataset will be continuously checked and improved upon as time goes on. In addition, CAI locations have been contacted in order to acquire internet speed test results. Currently 1356 of the total Community Anchor Institutions have speed test results. We will continute to add to this number as time goes on. Finally, this data will be accessible and modifiable via GIS services. This will allow county officials to actively edit the data. Data Fields The following items are the fields within the CAI feature class. There are several different field types within this dataset. The bold faced portion is representative of the field name, while the following text represents the type of the field as well as length, precision, and scale. Additionally, OBJECTIDand SHAPE are generated by Arc Map. OBJECTID- ObjectID Longitude- Double P38 S8 OITIndex- Short Latitude- Double P38 S8 AnchorName- String 200 FKProvider- Short FullAddress- String 200 KEY_- Short StreetAddress- 50 URL- String 100 Status- Short CAICategory - String 2 AddressNumber- Long CAIID- String 50 NumberSuffix - String 15 FullCensusBlockID- String 16 StreetPreModifier - String 10 TransTech- Double P38 S8 StreetPreDirectional - String 20 BBService- String 1 StreetPreType- String 20 PublicWiFi- String 1 StreetSeparator - String 10 CAIComments- String 255 StreetName - String 75 BBComments- String 255 StreetPostType- String 20 MaxAdDown- String 2 StreetPostDirectional- String 20 MaxAdUp- String 2 StreetPostModifier- String 20 SubScrbDown - String 2 SubAddress- String 50 SubScrbUp- String 2 Intersection- String 100 ActualDown- Double P38 S8 PlaceName- String 100 ActualUp- Double P38 S8 District- String 100 TestDate- String 255 County- String 50 ProviderNM- String 255 StateAbbrev- String 50 LocationChanged_Y_N- String 1 ZipCode- Long Done- String 1 Zip4- Short SHAPE- Geometry AddressLocDesc- String 255

Credits State of Colorado, Governor's Office of Information Technology (OIT) Archuleta County Baca County City and County of Broomfield Custer County Eagle County El Paso - Teller E911 Authority Garfield County Grand County La Plata County Larimer County Las Animas County E911 Authority Lincoln County Mesa County Moffat County Montezuma County North Central All - Hazards Region Pueblo County Routt County Use limitations None Extent West -109.011097 East -102.082504 North 40.994186 South 37.005858 Scale Range Maximum (zoomed in) 1:5,000 Minimum (zoomed out) 1:150,000,000 ArcGIS Metadata ► Topics and Keywords ► THEMES OR CATEGORIES OF THE RESOURCE  structure, location, health, utilitiesCommunication * CONTENT TYPE  Downloadable Data EXPORT TO FGDC CSDGM XML FORMAT AS RESOURCE DESCRIPTION No

DISCIPLINE KEYWORDS  Public Service Facilities Broadband Internet Service

PLACE KEYWORDS  Colorado

TEMPORAL KEYWORDS  2014

THEME KEYWORDS  Public Use Structures, Community Anchor Institutions, Essential Facilities, Landmark Features, Key Geographic Locations, Points of Interest, Structures, Public Buildings, Facilities of General Interest, Civic or Government Buildings, Public Service Facilities, Fire Station, Police Station, School, Library, Post Office, Town Hall.

Hide Topics and Keywords ▲ Citation ► TITLE Colorado Community Anchor Institutions (CAI) ALTERNATE TITLES  Colorado CAIs CREATION DATE 2012-08-31 00:00:00 REVISION DATE 2013-02-07 00:00:00 EDITION Early 2013 Local Review Edition EDITION DATE 2013-02-07 PRESENTATION FORMATS  digital map SERIES  NAME Colorado Broadband Map Database

COLLECTION TITLE Colorado Broadband Map Database OTHER CITATION DETAILS The locations and Internet broadband speeds of Community Anchor Institututions within the State are required deliverables to the National Telecommunications and Information Administrations (NTIA) in accordance with the State Broadband Data and Development Grant Program requirements found in Federal Register /Vol. 74, No. 129 /Wednesday, July 8, 2009 /Notices, pages 32548 and 32563. Hide Citation ▲ Citation Contacts ► RESPONSIBLE PARTY  INDIVIDUAL'S NAME Nathan Lowry ORGANIZATION'S NAME State of Colorado, Governor's Office of Information Technology CONTACT'S POSITION GIS Outreach Coordinator CONTACT'S ROLE  publisher RESPONSIBLE PARTY  INDIVIDUAL'S NAME Tudor Stanescu ORGANIZATION'S NAME Governor's Office of Information Technology CONTACT'S POSITION GIS Technician CONTACT'S ROLE  publisher

CONTACT INFORMATION  ► PHONE  VOICE (303)-764-6861 FAX N/A

ADDRESS  TYPE both DELIVERY POINT 601 East 18th Avenue Suite 220 CITY Denver ADMINISTRATIVE AREA Colorado POSTAL CODE 80203-1494 COUNTRY US E-MAIL ADDRESS tudor.stanescu@state.co.us

HOURS OF SERVICE 7:00am - 4:00pm Hide Contact information ▲

Hide Citation Contacts ▲ Resource Details ► DATASET LANGUAGES  English (UNITED STATES) DATASET CHARACTER SET  utf8 - 8 bit UCS Transfer Format STATUS  on-going SPATIAL REPRESENTATION TYPE  vector GRAPHIC OVERVIEW  FILE NAME ColoradoCAIs.png at https://docs.google.com/file/d/0B_O_LJbuRH4azB0RlZ1SUVKMXc/edit?usp=sharing FILE DESCRIPTION Colorado Community Anchor Institutions (CAIs) FILE TYPE Portable Network Graphic file (.png)

* PROCESSING ENVIRONMENT Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.1.1.3143 CREDITS State of Colorado, Governor's Office of Information Technology (OIT) Archuleta County Baca County City and County of Broomfield Custer County Eagle County El Paso - Teller E911 Authority Garfield County Grand County La Plata County Larimer County Las Animas County E911 Authority Lincoln County Mesa County Moffat County Montezuma County North Central All - Hazards Region Pueblo County Routt County

ARCGIS ITEM PROPERTIES  * NAME CAIs.DBO.ColoradoCAI * LOCATION Server=10.12.1.28; Service=sde:sqlserver:10.12.1.28; Database=CAIs; User=stanescut; Version=dbo.DEFAULT * ACCESS PROTOCOL ArcSDE Connection

Hide Resource Details ▲ Extents ► EXTENT  DESCRIPTION The State of Colorado, United States of America GEOGRAPHIC EXTENT  BOUNDING RECTANGLE  WEST LONGITUDE -114.996946 EAST LONGITUDE -96.104491 SOUTH LATITUDE 32.485329 NORTH LATITUDE 45.503973 EXTENT CONTAINS THE RESOURCE No

TEMPORAL EXTENT  BEGINNING DATE 2010-01-01 00:00:00 ENDING DATE 2010-12-31 00:00:00

EXTENT  GEOGRAPHIC EXTENT  BOUNDING RECTANGLE  EXTENT TYPE  Extent used for searching * WEST LONGITUDE -109.011097 * EAST LONGITUDE -102.082504 * NORTH LATITUDE 40.994186 * SOUTH LATITUDE 37.005858

EXTENT IN THE ITEM'S COORDINATE SYSTEM  * WEST LONGITUDE -109.011097 * EAST LONGITUDE -102.082504 * SOUTH LATITUDE 37.005858 * NORTH LATITUDE 40.994186 * EXTENT CONTAINS THE RESOURCE Yes

Hide Extents ▲ Resource Points of Contact ► POINT OF CONTACT  INDIVIDUAL'S NAME Nathan Lowry ORGANIZATION'S NAME State of

1. PUBLICATION CORRESPONDING TO THESE DATA Sloan, Sean*; Locatelli, Bruno; Andela, Niels; Cattau, Megan E.; Gaveau, David; Tacconi, Luca. 2022 ‘Declining Severe Fire Activity on Managed Lands in Equatorial Asia’. Communications Earth & Environment. DOI: 10.1038/s43247-022-00522-6. *Corresponding author email: sean.sloan@viu.ca 2. ABSTRACT OF THE DATA The GIS data and corresponding attribute data described here pertain to discrete fire events, their severity, and their ignitions, as derived on the basis of daily MODIS Collection 6 MCD14ML active-fire detections (AFDs). Data on fire events and their ignitions are provided separately, as two data files. These data files on fire events and ignitions may however be linked to each other by the data user. Fire-event severity is quantified per fire event and reported in the data file for fire events. A fire event is a cluster of MODIS Collection 6 MCD14ML active-fire detections (AFDs) wherein each AFD has a spatial (<=1-km) and temporal (<=4-day) proximity to another AFD in the same fire event, inferring thus a relational co-occurrence amongst AFDs in time and space. In other words, a fire event is considered a likely occasion of burning wherein all constituent AFDs are related to each other in time and space, either directly (as for proximate AFDs) or indirectly (as in the case of a large area of fire activity that spread progressively over time and space from an initial source). Each fire event has a designated ignition AFD, being the AFD of the fire event with the earliest detection date. A given fire event can have more than one ignition AFD if the ignitions all share same earliest detection date. The ignition AFD(s) is the nominal initial source of the burning described by the corresponding fire event. All other, non-ignition AFDs of a fire event are deemed its ‘propagation’ AFDs, since these AFDs follow from the ignitions, temporally and spatially. See Figure 4 in the publication by Sloan et al. for an illustration of the geography of fire events and their ignition AFDs. Fire events and their ignitions were derived from standard science-quality MODIS Collection 6 MCD 14ML AFD data, commonly referred to as fire ‘hotspot’ data. Data were detected by both the Terra and Aqua satellite sensors daily for Indonesia between July 2002 and December 2019. Information on these input data are provide by the two citations below. The publication of Sloan et al. provides methodological details on how the MODIS Collection 6 MCD 14ML AFD data were processed into discrete fire events and ignitions. EarthData. MODIS Collection 6 Active-Fire Detections standard scientific data (MCD14ML), NASA EarthData, https://earthdata.nasa.gov/firms (2019). Giglio, L., Schroeder, W. & Justice, C. O. The Collection 6 MODIS active fire detection algorithm and fire products. Remote Sensing of Environment 178, 31-41, (2016). 3. DATA FILES Two data files are distributed here – one for discrete fire events, and another for the ignition AFDs of each fire event. The data files are provided in a GIS-compatible format, and also as a generic text format, as described below. 3.1 GIS VERSION Data files in GIS-compatible format are provided as ‘feature classes’ within an ArcGIS file geodatabase ‘Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb’. These data files can be viewed and manipulated using either ArcGIS Desktop or ArcGIS Pro software. There is one feature class for fire events, and another file for ignitions. Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb fire4_all_spatial_fire_2002_2019_joins_sp_LC This file pertains to fire events. All AFDs of a given fire event are included, without differentiation as to whether the AFDs are ignition AFDs or other (propagation) AFDs. Fire events are assigned unique ID values and basic attribute data. Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb fire4_all_spatial_fire_2002_2019_igs_sp_LC This file pertains to ignitions. Only ignition AFDs are included for a given fire event. Fire events corresponding to the ignitions are assigned unique ID values and basic attribute data. 3.2 CSV TEXT VERSION Both data files are also supplied as comma-separated value (CSV) text files for viewing and manipulation in non-GIS software, such as Excel, text editors, or any statistical software. The text files can also be read into various GIS software. CSV-formatted files have the same file name and attribute fields as the corresponding GIS-formatted data files. These CSV-formatted data files (as well as the GIS-formatted data files) include attribute data on the latitude and the longitude of each AFD. Attribute field names are included as the first row of values in a CSV file. No ‘text qualifiers’ like quotations (“ ”) or inverted commas (‘’) are used to designate text/string values within the CSV file. Text values appear directly between commas in the CSV data file, e.g., …,Kalimantan_Southern,… . Note two points of caution for working with these CSV data: i) Microsoft Excel may be used for a partial view of the data file nfire4_all_spatial_fire_2002_2019_joins_sp_LC.csv, but it is not recommended for working with this data file. This is because the number of records/rows in this csv file slightly exceeds that maximum that may be read by Excel, which is just over 1 million. This limitation does not apply to the other csv file, however. ii) The GIS-formatted data files employ ‘null values’ in their attribute tables, and so the corresponding ‘values’ in the CSV-formatted data files are similarly null. For null values, no value whatsoever is ascribed, not even 0. In the syntax of a CSV file (apparent upon opening the file in any text editor like Microsoft Notepad), a null value is denoted by two consecutive commas without any value, text, or space between them. If a CSV file were opened in Excel, a cell assigned a null value would be blank, not 0 or otherwise. This denotes the correct transcription of the GIS-formatted data. This feature will not impede the correct reading of these CSV data by whatever software. Users are made aware of this feature merely to ensure the proper input of these data into whatever software. 4. DATA STRUCTURE / GEOGRAPHY The GIS-formatted data files are ‘point data’, i.e., they map the geography of AFDs as individual ‘points’, in keeping with how these MODIS MCD14ML AFD data were originally structured. For the GIS-formatted data files, each record/row in its corresponding attribute tables corresponds geographically to single AFD ‘point’, regardless of whether that AFD belongs to a fire event comprised of many AFDs. In the parlance of GIS files, the files depict ‘single-part’ point features. The unique ID field [nfireID2] serves to denote the fire event to which a given AFD belongs. Similarly, for the CSV-formatted data files, each record/row of values corresponds to a single AFD. There are 1,232,377 records for the data file ‘nfire4_all_spatial_fire_2002_2019_joins_sp_LC’. There are 720795 records for the data file ‘nfire4_all_spatial_fire_2002_2019_igs_sp_LC’. 5. ATTRIBUTE FIELDS In the data files, while some attribute fields pertain to the individual AFD as the unit of observation (e.g., the land-cover class coincident with the AFD), other attribute fields correspond to the larger ‘fire event’ to which the individual AFD belongs (e.g., the total duration of fire activity for the fire event). Accordingly, for certain attribute fields pertaining to the fire event as a whole, their values will appear ‘duplicated’ in the data file amongst those individual AFDs (records) that constitute the fire event in question. Whether a given attribute field pertains to the individual AFD or to its constituent fire event is denoted below for each field. Each AFD is assigned a unique ID field denoting its constituent fire event, [nfireID2]. This field is consistent between both data files, so that attribute data for a given fire event may be ‘matched’ to attribute data for its corresponding ignition AFD(s), and vice versa, on the basis of the common value of the field [nfireID2]. Note that many attributes below are as originally defined/measured by the input MCD 14ML data, or are derived directly thereof. 5.1 DATASET nfire4_all_spatial_fire_2002_2019_joins_sp_LC Field Name Geography of Attribute Value Definition OID AFD Object ID value. Unique values for each AFD (record) in the GIS-formatted data file when viewed in ArcGIS. Field values are -1 in the CSV-formatted data file. Peat AFD Denotes whether the AFD occurs on peatlands (value=1) as defined in Sloan et al. MIN_CONFIDE Fire Event The minimum detection confidence of all AFDs in the fire event, where confidence ranges from 1-100%. MAX_CONFIDE Fire Event The maximum detection confidence of all AFDs in the fire event, where confidence ranges from 1-100%. MEAN_CONFIDE Fire Event The mean detection confidence of all AFDs in the fire event, where confidence ranges from 1-100%. STD_CONFIDE Fire Event The standard deviation of detection confidence of all AFDs in the fire event, where confidence ranges from 1-100%. SUM_FRP Fire Event The sum total of all fire-radiative power (FRP) measures for all AFDs in the fire event. Units are megawatts. MEAN_FRP Fire Event The mean of all fire-radiative power (FRP) measures for all AFDs in the fire event. Units are megawatts. MIN_FRP Fire Event The minimum of all fire-radiative power (FRP) measures for all AFDs in the fire event. Units are megawatts. MAX_FRP Fire Event The maximum of all fire-radiative power (FRP) measures for all AFDs in the fire event. Units are megawatts. MEAN_LATITUD Fire Event The mean latitude of all AFDs in the fire event. MEAN_LONGITU Fire Event The mean longitude of all AFDs in the fire event. MIN_ACQ_DAT Fire Event The minimum acquisition date of all AFDs in the fire event (i.e., the ignition AFD detection date). MAX_ACQ_DAT Fire Event The maximum acquisition date of all AFDs in the

2000 Census County Lines, clipped to the H-GAC region. TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

Hosted Feature ServiceThe heart of the Idaho Trails Experience web app is the geographic data served by the Idaho Recreation Trails collection of Hosted Feature Layers. The Hosted service can be updated more frequently and on-the-fly than the previous technology used to maintain Idaho Trails-- changes now appear on the App and through the Feature Service in real time. The newest web presentation technology under AGOL, Experience Builder, served by this dataset, will make possible several extended features in the Web App.Under the hood Linear routes, closure routes and areas, and boundary area Hosted Feature Layers can be directly consumed from the Service via REST and are the source of features displayed in the Idaho Trails Web App. In addition to view settings for attributes popups set in the Web Map, additional visibility option not managed directly in the Hosted Feature data or controllable in the Web Map are further processed in the Idaho Trails Experience App presentation.Underlying Classes in the Idaho Recreation Trails dataset: One single linear class "Idaho Routes" contains all road and trail features (57,000+ route segment features): Routes characterized as recreational in nature include: High-clearance (previously "Jeep" treated as a road type, now as a full-width "trail" type), Special Vehicle Designation (mostly OHVs >50"), OHVs 50" and under, and single-track motorized (each width class separated by open year-long and motorized-seasonal); E-Bike (Class noted in Narrative); and, non-motorized and non-mechanized trails.Routes where vehicles either must be highway-legal (i.e., OHVs prohibited, typically paved roads), or routes requiring Restricted plate for legal OHV travel (mostly JURISDICTION = County); combined from previously-separate Layers: Highway-legal, Automobile, Other Roads (each with subcategories for seasonal access restrictions). (Note: Different route types are no longer kept in separate layers as with the legacy Map Service dataset. Route symbology, and selectable visibility is filtered based on the value in the SYMBOL attribute from the above linear class within the Web Map and Experience App. If dynamically consuming the Feature Service (REST), provisions will need to be made to filter to select visibility by road and trail types based on the value in the attribute field SYMBOL.)"Points of Interest" (point type data) is comprised of a layer previously titled "Trailheads" and now includes the flexibility of other types of lat/lon point-based information such as links to external maps and "attractions" information such as site seeing destinations not previously included in IDPR's map presentation. "Emergency Route Closures" contains linear route Closures (overlays any route where a Closure Order applies in web map)"Area Restrictions" is added for areas such as defined by human exclusion Orders (polygon; usually planned annual human or vehicle exclusion areas, but can be emergency closure such as for wildfires as well)Multiple "Boundary" polygon classes contain boundary outlines and attributes information for IDPR Regions (3), Counties (44), Wildernesses (42), National Forests and Ranger Districts (39), and BLM District and Field Offices (12), and BLM land units (700+). These separate classes reduce the data footprint of the Routes data and are joined in App popups by geographic Intersection logic. Bonus Material:Added to the web app are several optional, dynamic layers via publicly-available REST services selectable for visibility:NIFC Current and Historic Fire primetersIdaho Department of Lands- Lands Available for Recreational Use (visible by-default)Idaho Department of Fish & Game Hunting Units boundaries and numbers BLM Surface Management Agency layer for all local, state, and federal agencies which manage public lands (accessible, and not) US Forest Service Motor Vehicle Use Map, National Dataset (mirrors local MVUM paper and GeoPDF maps, where data available, lags local data when changes are made)National Park Service (NPS) Parks and Monuments areas and boundariesNOHRSC Snow Depth Other REST Services to be added based on utility in researching recreational accessThis dataset is published for the use of the individuals who fund this Program. Organizations wishing to consume this Feature Service into their own application should inquire to IDPR to obtain a use agreement and schema information to aid in development.AGOL Experience App here: https://experience.arcgis.com/experience/97a42a2a73c944ba918042faf518c689 Inquire to maps@idpr.idaho.gov

The U.S. Department of Housing and Urban Development's Real Estate Owned (REO) properties are the result of the Federal Housing Administration (FHA) paying a claim to a lending institution on a foreclosed property which was financed with an FHA Insured Mortgage, and the lender has transferred ownership of the property of to HUD. Typically, title to the property is not transferred (or the claim paid) until the previous owner is evicted from the property. Normally, after the home is transferred to HUD, the property will go up for auction on the HUD Home store website.Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. Note that these data only include latitude and longitude coordinates and associated attributes for those addresses that can be geocoded to an interpolated point along a street segment, or to a ZIP+4 centroid location. While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD.To learn more about HUD Real Estate Owned Properties visit: https://www.hud.gov/program_offices/housing/sfh/reo, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD FHA REO Properties for SaleDate of Coverage: 03/2025 SnapshotLast Updated: 03/2025

Redirect Notice: The website https://transbase.sfgov.org/ is no longer in operation. Visitors to Transbase will be redirected to this page where they can view, visualize, and download Traffic Crash data.A. SUMMARYThis table contains all crashes resulting in an injury in the City of San Francisco. Fatality year-to-date crash data is obtained from the Office of the Chief Medical Examiner (OME) death records, and only includes those cases that meet the San Francisco Vision Zero Fatality Protocol maintained by the San Francisco Department of Public Health (SFDPH), San Francisco Police Department (SFPD), and San Francisco Municipal Transportation Agency (SFMTA). Injury crash data is obtained from SFPD’s Interim Collision System for 2018 through the current year-to-date, Crossroads Software Traffic Collision Database (CR) for years 2013-2017 and the Statewide Integrated Transportation Record System (SWITRS) maintained by the California Highway Patrol for all years prior to 2013. Only crashes with valid geographic information are mapped. All geocodable crash data is represented on the simplified San Francisco street centerline model maintained by the Department of Public Works (SFDPW). Collision injury data is queried and aggregated on a quarterly basis. Crashes occurring at complex intersections with multiple roadways are mapped onto a single point and injury and fatality crashes occurring on highways are excluded.The crash, party, and victim tables have a relational structure. The traffic crashes table contains information on each crash, one record per crash. The party table contains information from all parties involved in the crashes, one record per party. Parties are individuals involved in a traffic crash including drivers, pedestrians, bicyclists, and parked vehicles. The victim table contains information about each party injured in the collision, including any passengers. Injury severity is included in the victim table. For example, a crash occurs (1 record in the crash table) that involves a driver party and a pedestrian party (2 records in the party table). Only the pedestrian is injured and thus is the only victim (1 record in the victim table). To learn more about the traffic injury datasets, see the TIMS documentationB. HOW THE DATASET IS CREATEDTraffic crash injury data is collected from the California Highway Patrol 555 Crash Report as submitted by the police officer within 30 days after the crash occurred. All fields that match the SWITRS data schema are programmatically extracted, de-identified, geocoded, and loaded into TransBASE. See Section D below for details regarding TransBASE. C. UPDATE PROCESSAfter review by SFPD and SFDPH staff, the data is made publicly available approximately a month after the end of the previous quarter (May for Q1, August for Q2, November for Q3, and February for Q4). D. HOW TO USE THIS DATASETThis data is being provided as public information as defined under San Francisco and California public records laws. SFDPH, SFMTA, and SFPD cannot limit or restrict the use of this data or its interpretation by other parties in any way. Where the data is communicated, distributed, reproduced, mapped, or used in any other way, the user should acknowledge TransBASE.sfgov.org as the source of the data, provide a reference to the original data source where also applicable, include the date the data was pulled, and note any caveats specified in the associated metadata documentation provided. However, users should not attribute their analysis or interpretation of this data to the City of San Francisco. While the data has been collected and/or produced for the use of the City of San Francisco, it cannot guarantee its accuracy or completeness. Accordingly, the City of San Francisco, including SFDPH, SFMTA, and SFPD make no representation as to the accuracy of the information or its suitability for any purpose and disclaim any liability for omissions or errors that may be contained therein. As all data is associated with methodological assumptions and limitations, the City recommends that users review methodological documentation associated with the data prior to its analysis, interpretation, or communication.This dataset can also be queried on the TransBASE Dashboard. TransBASE is a geospatially enabled database maintained by SFDPH that currently includes over 200 spatially referenced variables from multiple agencies and across a range of geographic scales, including infrastructure, transportation, zoning, sociodemographic, and collision data, all linked to an intersection or street segment. TransBASE facilitates a data-driven approach to understanding and addressing transportation-related health issues,informed by a large and growing evidence base regarding the importance of transportation system design and land use decisions for health. TransBASE’s purpose is to inform public and private efforts to improve transportation system safety, sustainability, community health and equity in San Francisco.E. RELATED DATASETSTraffic Crashes Resulting in Injury: Parties InvolvedTraffic Crashes Resulting in Injury: Victims InvolvedTransBASE DashboardiSWITRSTIMSData pushed to ArcGIS Online on December 2, 2025 at 4:11 AM by SFGIS.Data from: https://data.sfgov.org/d/ubvf-ztfxDescription of dataset columns:

 unique_id
 unique table row identifier


 cnn_intrsctn_fkey
 nearest intersection centerline node key


 cnn_sgmt_fkey
 nearest street centerline segment key (empty if crash occurred at intersection)


 case_id_pkey
 unique crash report number


 tb_latitude
 latitude of crash (WGS 84)


 tb_longitude
 longitude of crash (WGS 84)


 geocode_source
 geocode source


 geocode_location
 geocode location


 collision_datetime
 the date and time when the crash occurred


 collision_date
 the date when the crash occurred


 collision_time
 the time when the crash occurred (24 hour time)


 accident_year
 the year when the crash occurred


 month
 month crash occurred


 day_of_week
 day of the week crash occurred


 time_cat
 generic time categories


 juris
 jurisdiction


 officer_id
 officer ID


 reporting_district
 SFPD reporting district


 beat_number
 SFPD beat number


 primary_rd
 the road the crash occurred on


 secondary_rd
 a secondary reference road that DISTANCE and DIRECT are measured from


 distance
 offset distance from secondary road


 direction
 direction of offset distance


 weather_1
 the weather condition at the time of the crash


 weather_2
 the weather condition at the time of the crash, if a second description is necessary


 collision_severity
 the injury level severity of the crash (highest level of injury in crash)


 type_of_collision
 type of crash


 mviw
 motor vehicle involved with


 ped_action
 pedestrian action involved


 road_surface
 road surface


 road_cond_1
 road condition


 road_cond_2
 road condition, if a second description is necessary


 lighting
 lighting at time of crash


 control_device
 control device status


 intersection
 indicates whether the crash occurred in an intersection


 vz_pcf_code
 California vehicle code primary collision factor violated


 vz_pcf_group
 groupings of similar vehicle codes violated


 vz_pcf_description
 description of vehicle code violated


 vz_pcf_link
 link to California vehicle code section


 number_killed
 counts victims in the crash with degree of injury of fatal


 number_injured
 counts victims in the crash with degree of injury of severe, visible, or complaint of pain


 street_view
 link to Google Streetview


 dph_col_grp
 generic crash groupings based on parties involved


 dph_col_grp_description
 description of crash groupings


 party_at_fault
 party number indicated as being at fault


 party1_type
 party 1 vehicle type


 party1_dir_of_travel
 party 1 direction of travel


 party1_move_pre_acc
 party 1 movement preceding crash


 party2_type
 party 2 vehicle type (empty if no party 2)


 party2_dir_of_travel
 party 2 direction of travel (empty if no party 2)


 party2_move_pre_acc
 party 2 movement preceding crash (empty if no party 2)


 point
 geometry type of crash location


 data_as_of
 date data added to the source system


 data_updated_at
 date data last updated the source system


 data_loaded_at
 date data last loaded here (in the open data portal)


 analysis_neighborhood



 supervisor_district



 police_district



 Current Police Districts
 This column was automatically created in order to record in what polygon from the dataset 'Current Police Districts' (qgnn-b9vv) the point in column 'point' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.


 Current Supervisor Districts
 This column was automatically created in order to record in what polygon from the dataset 'Current Supervisor Districts' (26cr-cadq) the point in column 'point' is located. This

A treatment is a specific location and scope of work or activity within a project. For example if a project was applying a microsurface to half of the project and chip seal to the other half, they would create two treatments, one identifying each activity or work type. Treatments do not correlate directly to routes but are often one-to-one. Projects with no treatments are in this file but have empty treatment fields.This file contains one record per treatment per project. A project with five treatments will have five records. All project fields are identical to the Projects API. Unique treatment fields include the following:treatment_database_id - unique value identifying the treatmenttreatment_owner - the group that created the treatment, multiple groups may have treatments on the same projectroute - the ALRS routebeg_lm - the ALRS beginning milepointend_lm - the ALRS ending milepointbeg_lm_xy - lat/long location of beginning milepointend_lm_xy - lat/long location of ending milepointtreatment_class - the parent-level category of treatmenttreatment_type - the child-level treatment type, this is the most descriptive and consistentdescription - free text description of the treatment, this may often be emptyestimated_cost - estimated treatment costprogram - the program (funds) being used to pay for the treatmentThis layer is sourced from Workflow Manager and is refreshed

This web map sample includes the active storms, track points, track lines, and rainfall hazards (inches) layers for all active tropical cyclone systems around the world as a web map. DATA OVERVIEWKinetic Analysis Tropical Cyclone datasets draw on a broad array of real-time weather and forecast data to drive in-house, advanced numerical modeling that computes the spatial distribution of maximum wind speedwinds by Saffir-Simpson categorieswave heightsstorm surge inundationcumulative rainfallUSE CASESWhile this data may be used in a variety of ways, the most common ways we see it in action is by insurance, emergency management, disaster relief, supply chain, and governmental agencies/organization in making decisions about actions to take before, during, and after a tropical cyclone. Adjustors, for example, can use modeled hazards to determine which sites to visit and with what level of urgency. Government agencies can use impact data to determine where to focus on building climate resilience safeguards and resources next.DATA SOURCEHazard footprints are based on observed and forecasted storm track, intensity and wind radii provided by the designated expert-reviewed sources NHC (National Hurricane Center), JTWC (Joint Typhoon Warning Center), CPHC (Central Pacific Hurricane Center) - collectively termed OFCL (Official). UPDATE FREQUENCYData from Kinetic Analysis model runs are updated every time a new forecast is released by one of the aforementioned sources.SCALE/RESOLUTIONThis near real-time data is provided at 60 arc-second (~2 km) resolution. Shortly after a storm dissipates or transitions to a non-tropical cyclone, a post-event wind and storm surge dataset can be provided at a 30 arc-second (~1 km) resolution upon request.AREA COVEREDWorldINTERESTED IN MORE?Our full ArcGIS Marketplace listing grants you a monthly license for access to the Kinetic Analysis Corporation's proprietary near real-time data, which includes industry-standard shapefile datasets of multiple hazard footprints for all active hurricanes, typhoons, cyclones and tropical storms around the globe. Discounted price options are available for those who wish to purchase an annual license instead of a monthly one. Customized resolutions, forecast agencies, and data units (default is SI) are available upon request to sales@kinanco.com. Learn more on the Kinetic Analysis website.NOTE: Preview images of data on ArcGIS Marketplace only show rain footprints for confidentiality purposes. Licensors of the full listing will receive access to all hazard footprints.GLOSSARY/DATA LAYERS AND FIELDSActive Storms - These points indicate the most-recently-updated location of active storms around the world, as observed by the National Hurricane Center (NHC), the Central Pacific Hurricane Center (CPHC), or the Joint Typhoon Warning Center (JTWC) - together termed "Official" (OFCL).Track Points - These points indicate the locations of a storm over time - where it has been, where it currently is, and where it is forecast to be. They are generated by forecast agencies and numerical model guidance.Track Line - This is the line formed by connecting all the track points. It depicts a continuous path for the storm by interpolating between any two track points.ATCF ID - Unique ID associated with a tropical cyclone, defined using the Automated Tropical Cyclone Forecasting (ATCF) system. The format is usually a two-letter abbreviation of the ocean basin (see "Storm Basin" below for list) in which the storm can be found, the annual cyclone number starting from 1 for the first storm in each basin per year, and the 4-digit year. For example, AL112017 (Hurricane Irma) refers to AL (Atlantic basin), 11th storm of the year in that basin, in the year 2017.Storm Name - The World Meteorological Organization (WMO) tropical cyclone name, such as Irma, Katrina, and Rai.Storm Basin - Ocean basin in which the storm is taking place. These include AL (North Atlantic), WP (Western North Pacific), CP (Central North Pacific), EP (Eastern North Pacific), IO (North Indian Ocean), SH (South-West Indian Ocean, Australian region, and South Pacific Ocean), and LS (Southern Atlantic).Storm Age - Number of days the storm has been active at time of forecastCategory Description - How the selected layer would be categorized against similar data. For example, data in a wind layer may be categorized into groups of 5 mph each, such as 100-105 mph for one group and 105-110 mph for another group. In such a case, the category description field displays which grouping the selected location belongs to. This is a variable/field separate from the name of each map layer.Latitude & Longitude - Geographic indicators of a storm's past, current, or forecast location derived from dividing the Earth into grids measured in degrees.Wind Speed - Maximum wind speed of the storm at that location. The units are knots for track points and track line layers and miles per hour (mph) for the wind speed hazard layer. These represent terrain-adjusted, 2-minute sustained winds at 10-meter elevation and are consistent with wind speeds reported by Automated Surface Observing Stations (ASOS weather stations). They can differ from wind speed forecast by different agencies because, in contrast with winds forecast by agencies such as the NHC, Kinetic Analysis-generated winds account for the effects of surface roughness and topography. In addition, different agencies can report winds based on different averaging times. For example, the NHC and JTWC report 1-minute sustained winds while the World Meteorological Organization (WMO) standard is 10-minute sustained winds.Minimum Sea Level Pressure - The lowest sea level pressure at that storm location. Measured in millibars.Radius of Max Winds - The distance between the storm's center, where the central pressure is lowest, and the maximum winds of a storm. Measured in nautical miles. Forward Speed - How fast a storm is moving at the selected location. Measured in meters per second (m/s).Storm Direction - The direction toward which a storm is moving at the selected location. Measured with a 360-degree system where North is represented by 0 degrees and East by 90 degrees.Current Latitude & Longitude - The latitude and longitude of the storm at its current location, which might not be the selected location. The current location of the storm is indicated by the active storms layer.Current Wind Speed - The wind speed of the storm at its current location, which might not be the selected location. Measured in knots and mph depending on the layer type (see "Wind Speed" above for more information).Current Forward Speed - How fast a storm is moving at its current location, which might not be the selected location. Measured in knots.Current Storm Direction - The direction toward which a storm is moving at its current location, which might not be the selected location.Forecast Time - Time at which an agency (such as OFCL) released its newest update of storm track data. This is the set of data used to simulate the model results displayed. Simulation Time - Time at which Kinetic Analysis's models processed the current data.Model in Simulation - The forecast agency, or model that generated the inputs for the Kinetic Analysis-simulated storm hazard data.Valid Time Relative to Current Position - The time in hours relative to "Forecast Time" that a storm position represents. For example, a point with a valid time of 12 would represent the storm forecast position 12 hours after the current forecast time.NOTE: This map and its data are provided for informational purposes only. Due to limitations in modern modeling technology, this data may not reflect the ultimate path, hazards, and/or impacts of a storm with 100% accuracy. Usage of this map and its data voids Kinetic Analysis of any responsibilities for consequences that may arise from using it to make personal or business decisions.

This feature class describes properties listed on the National Register of Historic Places, classified as historic buildings, and depicted as points. The National Register of Historic Places requires the submission of a single UTM coordinate pair for properties under 10 acres or a series of bounding UTM coordinate pairs for properties over 10 acres. The polygons contained within this dataset represent boundaries created from connecting the bounding UTM coordinates submitted with the nomination. A building, such as a house, barn, church, hotel, or similar construction, iscreated principally to shelter any form of human activity. A building may also be used to refer to a historically and functionally related unit, such as a courthouse and jail or a house and barn. Buildings include: houses, barns, stables, sheds, garages, courthouses, city halls, social halls, commercial buildings, libraries, factories, mills, train depots, stationary mobile homees, hotels, theaters, schools, stores and churches. Attribute data in this dataset are intentionally limited to those necessary for spatial data maintenance and feature level metadata necessary to document the lineage of the geography itself. Data from external database systems, such as the National Register Information System, are intended to link with these data to provide basic feature attributes. The means to maintain unique identifiers for each historic site (CR_ID), Survey_ID, as well as unique geometries associated with that feature (Geometry_ID) are through the use of Globally Unique Identifiers (GUIDs) assigned by the database. Information about the genesis of individual points is documented by feature level metadata fields in the spatial attribute table.

The Wildland Fire Interagency Geospatial Services (WFIGS) Group provides authoritative geospatial data products under the interagency Wildland Fire Data Program. Hosted in the National Interagency Fire Center ArcGIS Online Organization (The NIFC Org), WFIGS provides both internal and public facing data, accessible in a variety of formats.This service contains wildland fire incidents from the IRWIN (Integrated Reporting of Wildland Fire Information) integration service that meet the following criteria:Categorized in IRWIN as a Wildfire (WF) or Prescribed Fire (RX) recordHas not been declared contained, controlled, nor outHas not had fire report records completed (certified)Is Valid and not "quarantined" in IRWIN due to potential conflicts with other records"Fall-off" rules are used to ensure that stale records are not retained. Records are removed from this service under the following conditions:Fire Discovery Date Time is within the last 24 hours.Data are refreshed from IRWIN every 5 minutes.Fall-off rules are enforced hourly.Attributes:SourceOIDThe OBJECTID value of the source record in the source dataset providing the attribution.ABCDMiscA FireCode used by USDA FS to track and compile cost information for emergency IA fire suppression on A, B, C & D size class fires on FS lands.ADSPermissionStateIndicates the permission hierarchy that is currently being applied when a system utilizes the UpdateIncident operation.ContainmentDateTimeThe date and time a wildfire was declared contained.ControlDateTimeThe date and time a wildfire was declared under control.CreatedBySystemArcGIS Server Username of system that created the IRWIN Incident record.IncidentSizeReported for a fire. The minimum size is 0.1.DiscoveryAcresAn estimate of acres burning when the fire is first reported by the first person to call in the fire. The estimate should include number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.DispatchCenterIDA unique identifier for a dispatch center responsible for supporting the incident.EstimatedCostToDateThe total estimated cost of the incident to date.FinalAcresReported final acreage of incident.FinalFireReportApprovedByTitleThe title of the person that approved the final fire report for the incident.FinalFireReportApprovedByUnitNWCG Unit ID associated with the individual who approved the final report for the incident.FinalFireReportApprovedDateThe date that the final fire report was approved for the incident.FireBehaviorGeneralA general category describing how the fire is currently reacting to the influences of fuel, weather, and topography.FireBehaviorGeneral1A more specific category further describing the general fire behavior (how the fire is currently reacting to the influences of fuel, weather, and topography).FireBehaviorGeneral2A more specific category further describing the general fire behavior (how the fire is currently reacting to the influences of fuel, weather, and topography). FireBehaviorGeneral3A more specific category further describing the general fire behavior (how the fire is currently reacting to the influences of fuel, weather, and topography).FireCauseBroad classification of the reason the fire occurred identified as human, natural or unknown. FireCauseGeneralAgency or circumstance which started a fire or set the stage for its occurrence; source of a fire's ignition. For statistical purposes, fire causes are further broken into specific causes. FireCauseSpecificA further categorization of each General Fire Cause to indicate more specifically the agency or circumstance which started a fire or set the stage for its occurrence; source of a fire's ignition. FireCodeA code used within the interagency wildland fire community to track and compile cost information for emergency fire suppression expenditures for the incident. FireDepartmentIDThe U.S. Fire Administration (USFA) has created a national database of Fire Departments. Most Fire Departments do not have an NWCG Unit ID and so it is the intent of the IRWIN team to create a new field that includes this data element to assist the National Association of State Foresters (NASF) with data collection.FireDiscoveryDateTimeThe date and time a fire was reported as discovered or confirmed to exist. May also be the start date for reporting purposes.FireMgmtComplexityThe highest management level utilized to manage a wildland fire event. FireOutDateTimeThe date and time when a fire is declared out. FireStrategyConfinePercentIndicates the percentage of the incident area where the fire suppression strategy of "Confine" is being implemented.FireStrategyFullSuppPercentIndicates the percentage of the incident area where the fire suppression strategy of "Full Suppression" is being implemented.FireStrategyMonitorPercentIndicates the percentage of the incident area where the fire suppression strategy of "Monitor" is being implemented.FireStrategyPointZonePercentIndicates the percentage of the incident area where the fire suppression strategy of "Point Zone Protection" is being implemented.FSJobCodeSpecific to the Forest Service, code use to indicate the FS job accounting code for the incident. Usually displayed as 2 char prefix on FireCode.FSOverrideCodeSpecific to the Forest Service, code used to indicate the FS override code for the incident. Usually displayed as a 4 char suffix on FireCode. For example, if the FS is assisting DOI, an override of 1502 will be used.GACC"A code that identifies the wildland fire geographic area coordination center (GACC) at the point of origin for the incident. A GACC is a facility used for the coordination of agency or jurisdictional resources in support of one or more incidents within a geographic area."ICS209ReportDateTimeThe date and time of the latest approved ICS-209 report.ICS209ReportForTimePeriodFromThe date and time of the beginning of the time period for the current ICS-209 submission.ICS209ReportForTimePeriodToThe date and time of the end of the time period for the current ICS-209 submission. ICS209ReportStatusThe version of the ICS-209 report (initial, update, or final). There should never be more than one initial report, but there can be numerous updates and multiple finals (as determined by business rules).IncidentManagementOrganizationThe incident management organization for the incident, which may be a Type 1, 2, or 3 Incident Management Team (IMT), a Unified Command, a Unified Command with an IMT, National Incident Management Organization (NIMO), etc. This field is null if no team is assigned.IncidentNameThe name assigned to an incident.IncidentShortDescriptionGeneral descriptive location of the incident such as the number of miles from an identifiable town. IncidentTypeCategoryThe Event Category is a sub-group of the Event Kind code and description. The Event Category breaks down the Event Kind into more specific event categories.IncidentTypeKindA general, high-level code and description of the types of incidents and planned events to which the interagency wildland fire community responds.InitialLatitudeThe latitude of the initial reported point of origin specified in decimal degrees.InitialLongitudeThe longitude of the initial reported point of origin specified in decimal degrees.InitialResponseAcresAn estimate of acres burning at the time of initial response (when the IC arrives and performs initial size up) The minimum size must be 0.1. The estimate should include number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.InitialResponseDateTimeThe date/time of the initial response to the incident (when the IC arrives and performs initial size up)IrwinIDUnique identifier assigned to each incident record in IRWIN.IsFireCauseInvestigatedIndicates if an investigation is underway or was completed to determine the cause of a fire.IsFSAssistedIndicates if the Forest Service provided assistance on an incident outside their jurisdiction.IsMultiJurisdictionalIndicates if the incident covers multiple jurisdictions.IsReimbursableIndicates the cost of an incident may be another agency’s responsibility.IsTrespassIndicates if the incident is a trespass claim or if a bill will be pursued.IsUnifiedCommandIndicates whether the incident is being managed under Unified Command. Unified Command is an application of the ICS used when there is more than one agency with incident jurisdiction or when incidents cross political jurisdictions. Under Unified Command, agencies work together through their designated IC at a single incident command post to establish common objectives and issue a single Incident Action Plan.LocalIncidentIdentifierA number or code that uniquely identifies an incident for a particular local fire management organization within a particular calendar year.ModifiedBySystemArcGIS Server username of system that last modified the IRWIN Incident record.PercentContainedIndicates the percent of incident area that is no longer active. Reference definition in fire line handbook when developing standard.PercentPerimeterToBeContainedIndicates the percent of perimeter left to be completed. This entry is appropriate for full suppression, point/zone protection, and confine fires, or any combination of these strategies. This entry is not used for wildfires managed entirely under a monitor strategy. (Note: Value is not currently being passed by ICS-209)POOCityThe closest city to the incident point of origin.POOCountyThe County Name identifying the county or equivalent entity at point of origin designated at the time of collection.POODispatchCenterIDA unique identifier for the dispatch center that intersects with the incident point of origin.POOFipsThe code which uniquely identifies counties and county equivalents. The first two digits are the FIPS State code and the last three are the county code within the state.POOJurisdictionalAgencyThe agency having land and resource