Instructions on how to create a layer containing recent earthquakes from a CSV file downloaded from GNS Sciences GeoNet website to a Web Map.The CSV file must contain latitude and longitude fields for the earthquake location for it to be added to a Web Map as a point layer.Document designed to support the Natural Hazards - Earthquakes story map

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

City Of Sacramento's Survey Division has developed a high accuracy GPS control point grid. This file currently contains data points for the entire City of Sacramento. The latitude and longitude values have an accuracy level of +/- .05 feet. Elevation data has accuracy of +/- .24 feet.

Field: GPSNUMBER Alias: Survey reference number Field Description: Reference to latitude/longitude minute

Field: NORTHINGFT Alias: False Northing, California State Plane, Zone II, Feet

Field: EASTINGFT Alias: False Easting, California State Plane, Zone II, Feet

Field: ELVORTHOFT Alias: Elevation Ortho (ft)- a preliminary ground elevation to which the orthometric leveling correction has been applied

Field: DFNGVD29FT Alias: Differential NGVD 29- elevation obtained by spirit leveling based on the national geodetic vertical datum of 1929

Field: STREET Alias: Street location of control point

Field: XSTREET Alias: Cross street or reference information

Field: MONTYPE Alias: Control point or monument type

Field: LAT_DMS Alias: Latitude values in Degrees, Minutes, Seconds

Field: LONG_DMS Alias: Latitude values in Degrees, Minutes, Seconds

Field: ELLIPSHT Alias: Ellipsoid Height- the distance, measured along the mormal, from the surface of the ellipsoid to a point

Field: CNVERGENCE Alias: The angle difference at a given location between grid north and astronomic north

Field: GRDSCLFCTR Alias: Grid Scale Factor- a multiplier for reducing a sea level lengths to grid lengths

Field: COMBNDFCTR Alias: Combined Factor- multiplier obtained from the product of the sea level and grid scale factor and applied to ground distance to obtain grid distance

Field: GEOIDHT Alias: Distance of the geoid above (positive) or below (negative) the mathematical reference spheroid

Field: ARCHIVELOC Alias: Use To be Determined Field Description: Associated with crossed out GPS No.-Point ID

Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal Buffers Counties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal BuffersWithout Coastal BuffersCities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.With Coastal BuffersWithout Coastal BuffersCity and County AbbreviationsUnincorporated Areas (Coming Soon)Census Designated Places (this dataset)Cartographic CoastlinePolygonLine source (Coming Soon)State BoundaryWith Bay CutsWithout Bay Cuts Point of ContactCalifornia Department of Technology, Office of Digital Services, gis@state.ca.gov Field and Abbreviation DefinitionsPLACENS: An assigned an eight-digit National Standard (NS) code.GEOID: Place identifier; a concatenation of the current state FIPS code and place FIPS codeGEOIDFQ: facilitates joining Census Bureau spatial data to Census Bureau summary file data from data.census.govNAMELSAD: describe the particular typology for each geographic entity.CLASSFP: defines the current FIPS class of a geographic entity.FUNCSTAT: defines the current functional status of a geographic entity.ALAND: Current land areaAWATER: Current water area INTPTLAT: Current latitude of the internal point INTPTLON: Current longitude of the internal point Offline UseThis service is fully enabled for sync and export using Esri Field Maps or other similar tools. Importantly, the GlobalID field exists only to support that use case and should not be used for any other purpose (see note in field descriptions). Updates and Date of Processing(Section coming soon)

Section boundaries as defined by the US Public Land Survey System (PLSS). PLSS is a way of subdividing and describing land in the United States. Most lands in the public domain are subject to subdivision by this rectangular system of surveys, which is regulated by the U.S. Department of the Interior, Bureau of Land Management. Section boundaries were generated from geodetic latitude and longitude coordinate pairs as recorded on BLM's official protraction diagrams of the state of Alaska. Most corners are protracted corners, calculated by the Bureau of Land Management in lieu of field or survey locations. In 2013 and 2015 the Matanuska-Susitna Borough (MSB) shifted portions of this dataset to more accurately reflect the actual locations of section corners on the ground. These shifts occurred in the more populated areas of the MSB. Contact the MSB GIS division for more information.

A comprehensive dataset of 1,513 Pakistani cities, towns, tehsils, districts and places with latitude/longitude, administrative region, population (when available) and Wikidata IDs — ideal for mapping, geospatial analysis, enrichment, and location-based ML.

Why this dataset is valuable:

• Full geocoordinates for every entry (100% coverage) — ready for mapping and spatial joins.
• Wide geographic coverage across all 7 major regions of Pakistan (provinces / administrative regions).
• Wikidata IDs included for reliable cross-referencing and automatic enrichment from external knowledge bases.
• Useful for data scientists, GIS engineers, civic tech projects, academic research, and startups building Pakistan-focused location services.

Highlights (fetched from the data):

• Total rows: 1,513
• Unique places (city field): 1,497
• Rows with population > 0: 526 (≈34.8%)
• Coordinate coverage: 1513 / 1513 (100%) — directly usable with mapping libraries.

Column definitions (short):

• id — Internal numeric row id (unique integer).
• wikiDataId — Wikidata QID (e.g., Q####) for the place; use to fetch rich metadata.
• type — Administrative/place type (e.g., ADM1, ADM2, city, district, tehsil).
• city — Common/local city/place name (short label).
• name — Full name / official name of the place (may include “District”, “Tehsil”, etc.).
• country — Country name (Pakistan).
• countryCode — ISO country code (e.g., PK).
• region — Primary administrative region / province (e.g., Punjab, Sindh).
• regionCode — Short code for region (e.g., PB, KP depending on your encoding).
• regionWdId — Wikidata QID for the region.
• latitude — Latitude in decimal degrees (float).
• longitude — Longitude in decimal degrees (float).
• population — Integer population (0 or NA where unknown).

Typical & high-value use cases:

• Mapping & visualization: choropleth maps, point overlays, heatmaps of population or density.
• Geospatial analysis: distance calculations, nearest-neighbor queries, clustering of urban centers.
• Data enrichment: join with other datasets (OpenStreetMap, Wikidata, census data) using wikiDataId and coordinates.
• Machine learning & NLP: training geolocation models, geoparsing, toponym resolution, place name disambiguation.
• Urban planning & research: analyze distribution of population-ready places vs administrative units.
• Mobile / location-based apps: lookup & reverse geocoding fallback, seeding POI databases for Pakistan.
• Humanitarian & disaster response: baseline location lists for logistics and situational awareness.

Township and Range boundaries as defined by the US Public Land Survey System (PLSS). PLSS is a way of subdividing and describing land in the United States. Most lands in the public domain are subject to subdivision by this rectangular system of surveys, which is regulated by the U.S. Department of the Interior, Bureau of Land Management. Township and Range boundaries were generated from geodetic latitude and longitude coordinate pairs as recorded on BLM's official protraction diagrams of the state of Alaska. Most corners are protracted corners, calculated by the Bureau of Land Management in lieu of field or survey locations. In 2013 and 2015 the Matanuska-Susitna Borough shifted portions of this dataset to more accurately reflect the actual locations of section corners on the ground. These shifts occurred in the more populated areas of the Matanuska-Susitna Borough. Contact the MSB GIS division for more information.

Authority In the 1963 general session, the Utah State Legislature charged the Division of Water Resources with the responsibility of developing a State Water Plan. This plan is to coordinate and direct the activities of state and federal agencies concerned with Utah’s water resources. As a part of this objective, the Division of Water Resources collects water-related land use data for the entire state. This data includes the types and extent of irrigated crops as well as information concerning phreatophytes, wet/open water areas, dry land agriculture and urban areas. The data produced by the water-related land use program are used for various planning purposes. Some of these include: determining cropland water use, evaluating irrigated land losses and conversion to urban uses, planning for new water development, estimating irrigated acreages for any area, and developing water budgets. Additionally, the data are used by many other state and federal agencies. Previous Methods The land use inventory methods used by the division in conducting water-related land use studies have varied with regard to the procedures used and the precision obtained. During the 1960s and 70s, inventories were prepared using large format vertical-aerial photographs supplemented with field surveys to label boundaries, vegetation types, and other water use information. After identifying crops and labeling photographs, the information was transferred onto a base map and then planimetered or "dot-counted" to determine the acreage. Tables for individual townships and ranges were prepared showing the amount of land in each land use category within each section. Data were then available for use in preparing water budgets. In the early 1980s, the division began updating its methodology for collecting water-related land use data to take advantage of the rapidly growing fields of Remote Sensing and computerized Geographic Information Systems (GIS). For several years during the early 1980’s, the division contracted with the University of Utah Research Institute, Center for Remote Sensing and Cartography (CRSC), to prepare water-related land use inventories. During this period, water-related land use data was obtained by using high altitude color infrared photography and laboratory interpretation, with field checking. In March 1984, several division staff members visited the California Department of Water Resources to observe its methodology for collecting water-related land use data for state water planning purposes. Based on its review of the California methodology and its own experience, the division developed a water-related land use inventory program. This program included the use of 35mm slides, United States Geological Survey (USGS) 7-1/2 minute quadrangle maps, field-mapping using base maps produced from the 35mm photography and a computerized GIS to process, store and retrieve land use data. Areas for survey were first identified from previous land use studies and any other available information. The identified areas were then photographed using an aircraft carrying a high quality 35mm single lens reflex camera mounted to focus along a vertical axis to the earth. Photos were taken between 6,000 and 6,500 feet above the ground using a 24mm lens. This procedure allowed each slide to cover a little more than one square mile with approximately 30 percent overlap on the wide side of the slide and 5 percent on the slide's narrow side. The slides were then indexed according to a flight-line number, slide number, latitude and longitude. All 35mm slides were stored in files at the division offices and cataloged according to township, range and section, and quadrangle map location. Water-related land use areas were then transferred from the slide to USGS 7-1/2 minute quadrangle maps using a standard slide projector with a 100-200mm zoom lens. This step allowed the technician to project the slide onto the back of a quadrangle map. The image showing through the map was adjusted to the map scale with the zoom lens. Field boundaries and other water-use boundaries were then traced on the 7-1/2 minute quadrangle map. Next, a team was sent to use the map in the field to check the boundaries and current year land use field data on the 7-1/2 minute quadrangles. The final step was to digitize and process the field data using ARC/INFO software developed by Environmental Systems Research Institute (ESRI). Starting in 2000 with the land use survey of the Uintah Basin, the division further improved its land use program by using digital data for the purposes of outlining agricultural and other land cover boundaries. The division used satellite data, USGS Digital Orthophoto Quadrangles (DOQs), National Agricultural Imagery Program (NAIP), and other digital images in a heads-up digitizing mode for this process. This allowed the division to use multiple technicians for the digitizing process. Digitizing was done as line and polygon files using ArcView 3.2 with a satellite image, DOQ or NAIP image as a background with other layers added for reference. Boundary files were created in logical groups so that the process of edge-matching along quad lines was eliminated and precision increased. Subsequent inventories were digitized in the ArcMap 9.x software versions. Present Methodology Using the latest statewide NAIP Imagery and ArcGIS 10, all boundaries of individual agricultural fields, urban areas, and significant riparian areas are precisely digitized. Once the process of boundary digitizing is done, the polygons are loaded onto tablet PCs. Field crews are then sent to field check the crop and irrigation type for each agricultural polygon and label the shapefiles accordingly. Each tablet PC is attached to a GPS unit for real-time tracking to continuously update the field crew’s location during the field labeling process. This improved process has saved the division much time and money and even greater savings will be realized as the new statewide field boundaries are completed. Once processed and quality checked, the data is filed in the State Geographic Information Database (SGID) maintained by the State Automated Geographic Reference Center (AGRC). Once in the SGID, the data becomes available to the public. At this point, the data is also ready for use in preparing various planning studies. In conducting water-related land use inventories, the division attempts to inventory all lands or areas that consume or evaporate water other than natural precipitation. Areas not inventoried are mainly desert, rangeland and forested areas. Wet/open water areas and dry land agriculture areas are mapped if they are within or border irrigated lands. As a result, the numbers of acres of wet/open water areas and dry land agriculture reported by the division may not represent all such areas in a basin or county. During land use inventories, the division uses 11 hydrologic basins as the basic collection units. County data is obtained from the basin data. The water-related land use data collected statewide covers more than 4.3 million acres of dry and irrigated agricultural land. This represents about 8 percent of the total land area in the state. Due to changes in methodology, improvements in imagery, and upgrades in software and hardware, increasingly more refined inventories have been made in each succeeding year of the Water-Related Land Use Inventory. While this improves the data we report, it also makes comparisons to past years difficult. Making comparisons between datasets is still useful; however, increases or decreases in acres reported should not be construed to represent definite trends or total amounts of change up or down. To estimate such trends or change, more analysis is required.

GIS shapefile of recovered or verified manatee carcass locations within Florida from April 1974 through to the latest available spatially verified data. Locations are based both on coordinates provided by field staff (gathered either by GPS or by using navigation charts to ascertain latitudes and longitudes) and maps provided by the field staff. FWRI GIS staff in the Marine Mammal subsection verify that the provided coordinates match the intent of the plotted location. Points representing carcass locations were entered into a GIS using a digital shoreline basemap taken largely from NOAA navigation charts (1:40,000) and from USGS quadrangles (1:24,000) or in reference to the latest available NAIP aerial imagery when the data were processed. The scale is considered to be 1:40,000.

This data layer is an element of the Oregon GIS Framework. The purpose is to provide a seamless raster image for Oregon of the 2000 one-meter orthoimagery. This data depicts physical features on the surface of the earth. It has been constructed to be used for online access. Digital orthoimages serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The imagery (or extracts from it) may be useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps. Orthophotos combine the image characteristics of a photograph with the geometric qualities of a map. The primary digital orthophotoquad (DOQ) is a 1-meter ground resolution, quarter-quadrangle (3.75-minutes of latitude by 3.75-minutes of longitude) image cast on the Universal Transverse Mercator Projection (UTM) on the North American Datum of 1983 (NAD83).The geographic extent of the DOQ is equivalent to a quarter-quad plus The overedge ranges a minimum of 50 meters to a maximum of 300 meters beyond the extremes of the primary and secondary corner points. The overedge is included to facilitate tonal matching for mosaicking and for the placement of the NAD83 and secondary datum corner ticks. The normal orientation of data is by lines (rows) and samples (columns). Each line contains a series of pixels ordered from west to east with the order of the lines from north to south. The standard, archived digital orthophoto is formatted as four ASCII header records, followed by a series of 8-bit binary image data records. The radiometric image brightness values are stored as 256 gray levels ranging from 0 to 255. The imagery is provided in the Web Mercator Auxiliary Sphere projection as a tiled service, and in the State Lambert projection as an image service. Using web services to stream imagery: https://imagery.oregonexplorer.info/arcgis/rest/services/NAIP_2000

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

This layer presents detectable thermal activity from MODIS satellites for the last 7 days. MODIS Global Fires is a product of NASA’s Earth Observing System Data and Information System (EOSDIS), part of NASA's Earth Science Data. EOSDIS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource managers and other stakeholders around the World.

Area Covered: World

What can I do with this layer?
The MODIS thermal activity layer can be used to visualize and assess wildfires worldwide. However, it should be noted that this dataset contains many “false positives” (e.g., oil/natural gas wells or volcanoes) since the satellite will detect any large thermal signal.


It takes approximately 2 – 4 hours after satellite overpass for MODIS Rapid Response to process the data, and for the Fire Information for Resource Management System (FIRMS) to update the website. Occasionally, hardware errors can result in processing delays beyond the 2-4 hour range. Additional information on the MODIS system status can be found at MODIS Rapid Response.

Attribute Information

• Latitude and Longitude: The center point location of the 1km (approx.) pixel flagged as containing one or more fires/hotspots (fire size is not 1km, but variable). Stored by Point Geometry. See What does a hotspot/fire detection mean on the ground?
• Brightness: The brightness temperature measured (in Kelvin) using the MODIS channels 21/22 and channel 31.
• Scan and Track: The actual spatial resolution of the scanned pixel. Although the algorithm works at 1km resolution, the MODIS pixels get bigger toward the edge of the scan. See What does scan and track mean?
• Date and Time: Acquisition date of the hotspot/active fire pixel and time of satellite overpass in UTC (client presentation in local time). Stored by Acquisition Date.
  
• Acquisition Date: Derived Date/Time field combining Date and Time attributes.
• Satellite: Whether the detection was picked up by the Terra or Aqua satellite.
• Confidence: The detection confidence is a quality flag of the individual hotspot/active fire pixel.
• Version: Version refers to the processing collection and source of data. The number before the decimal refers to the collection (e.g. MODIS Collection 6). The number after the decimal indicates the source of Level 1B data; data processed in near-real time by MODIS Rapid Response will have the source code “CollectionNumber.0”. Data sourced from MODAPS (with a 2-month lag) and processed by FIRMS using the standard MOD14/MYD14 Thermal Anomalies algorithm will have a source code “CollectionNumber.x”. For example, data with the version listed as 5.0 is collection 5, processed by MRR, data with the version listed as 5.1 is collection 5 data processed by FIRMS using Level 1B data from MODAPS.
• Bright.T31: Channel 31 brightness temperature (in Kelvins) of the hotspot/active fire pixel.
• FRP: Fire Radiative Power. Depicts the pixel-integrated fire radiative power in MW (MegaWatts). FRP provides information on the measured radiant heat output of detected fires. The amount of radiant heat energy liberated per unit time (the Fire Radiative Power) is thought to be related to the rate at which fuel is being consumed (Wooster et. al. (2005)).
• DayNight: The standard processing algorithm uses the solar zenith angle (SZA) to threshold the day/night value; if the SZA exceeds 85 degrees it is assigned a night value. SZA values less than 85 degrees are assigned a day time value. For the NRT algorithm the day/night flag is assigned by ascending (day) vs descending (night) observation. It is expected that the NRT assignment of the day/night flag will be amended to be consistent with the standard processing.
• Hours Old: Derived field that provides age of record in hours between Acquisition date/time and latest update date/time. 0 = less than 1 hour ago, 1 = less than 2 hours ago, 2 = less than 3 hours ago, and so on.

This map is provided for informational purposes and is not monitored 24/7 for accuracy and

The U.S. Fish and Wildlife Service Corporate Master Table (CMT) is the official source of Service organization codes and related information. Information in the CMT includes, but is not limited to, organization codes, organization names, Federal Budget Management System (FBMS), cost center codes, fire unit identifiers, program names, mailing and physical/shipping addresses, telephone and fax numbers as well as latitude and longitude coordinates. The CMT enables all Service automated systems to utilize a corporate data set of known quality, eliminating the workload required to maintain each system's data set, and thereby facilitating data sharing. Other customers for the CMT are Service personnel who maintain directories, communicate with Congress and with the Public, maintain World Wide Web sites, etc. These spatial data were created using the information in the CMT. The CMT contains location information on all the offices within the Service that have an organization code. Unstaffed offices and some other facilities may not be included. The latitude and longitude points used are usually the location of the main administrative site. The latitude and longitude data is not completely verified but is the best we have at this time. This data set is intended to give an overview of where USFWS has stations across the United States and Territories, including locations outside the 50 states. It is not intended to be the exact location of every USFWS office. The CMT is primarily used for accounting purposes and therefore one location in the CMT can represent many different offices. Some points are duplicates where a station, most usually an Ecological Field Office, may be associated with more than one USFWS program. This data is updated from an internal authoritative source every night at 2:30am EST.For a direct link to the official Enterprise Geospatial dataset and metadata: *link pending*Data Trustee: Rich Wooten rich_wooten@fws.govData Steward: Amy Gibbs amy_gibbs@fws.gov

Spatial datasets describe area boundaries, streams, site locations and other geographic features for the Catalina - Jemez CZO field areas. These data are intended for the visualization of research areas and support geo-spatial analysis.

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: Global Positioning System Ground Control Points and Field Site Locations from 1993

The Biospheric Sciences Branch (formerly Earth Resources Branch) within the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center and associated University investigators are involved in a research program entitled Forest Ecosystem Dynamics (FED) which is fundamentally concerned with vegetation change of forest ecosystems at local to regional spatial scales (100 to 10,000 meters) and temporal scales ranging from monthly to decadal periods (10 to 100 years). The nature and extent of the impacts of these changes, as well as the feedbacks to global climate, may be addressed through modeling the interactions of the vegetation, soil, and energy components of the boreal ecosystem.

The Howland Forest research site lies within the Northern Experimental Forest of International Paper. The natural stands in this boreal-northern hardwood transitional forest consist of spruce-hemlock-fir, aspen-birch, and hemlock-hardwood mixtures. The topography of the region varies from flat to gently rolling, with a maximum elevation change of less than 68 m within 10 km. Due to the region's glacial history, soil drainage classes within a small area may vary widely, from well drained to poorly drained. Consequently, an elaborate patchwork of forest communities has developed, supporting exceptional local species diversity.

This data set is in ARC/INFO export format and contains Global Positioning Systems (GPS) ground control points in and around the International Paper Experimental Forest, Howland ME. A Trimble roving receiver placed on the top of the cab of a pick-up truck and leveled was used to collect position information at selected sites (road intersections) across the FED project study area. The field collected data was differentially corrected using base files measured by a Trimble Community Base Station. The Community Base Station is run by the Forestry Department at the University of Maine, Orono (UMO). The base station was surveyed by the Surveying Engineering Department at UMO using classical geodetic methods. Trimble software was used to produce coordinates in Universal Transverse Mercator (UTM) WGS84. Coordinates were adjusted based on field notes. All points were collected during December 1993 and differentially corrected.

This dataset includes the proposed field camp locations for the 2003/04 science expedition to Heard Island, the locations of the camp sites that were used during the expedition and the locations of some of the refuges on the island that were surveyed during the expedition. It is a point dataset stored in the Geographical Information System (GIS). The proposed field camp locations are shown in a map (refer to link below).

This dataset contains the name, location, date, and acquisition details of the sediment cores collected as part of the Long Island Sound mapping project Phase II.Time period of content: 2018-04-04 to 2018-08-24Attribute accuracy: Name, platform, date and time are accurate. Positions are accurate when provided by DGPS (see below). Water depth is based on depth sounder reading, core length is measured after opening the core.Completeness: The dataset is complete.Positional accuracy: Location is based on DGPS using the ship GPS antenna for most cores resulting +/- 5 m accuracy. For some cores the ship GPS location wasn’t noted in the logs and the navigation recording was lost. The position is based on target location and visual estimates of the position (+/- 20 m)Attributes: Survey: text field that describes the identifier of the field survey Name: text field describing the sediment core identifier, consisting of survey name, GC for gravity core and a numberLat: Latitude of core location in decimal degreesLon: Longitude of core location in decimal degreesDate: Date when the core was taken (in ISO format)Time: Time when the core was taken (in 24-hour ISO format)Platform: name of the ship used to retrieve the sediment coreType: Text describing the type of coring device used for retrieving the core (text)Position: Text describing the positioning system used to determine the location of the coreW_depth_m: water depth at the location where the core was retrieved (in meter) based on ship sounderLength_m: length of the retrieved sediment core (in meter)

This is a point feature class of environmental monitoring stations maintained in the California Department of Water Resources’ (hereafter the Department) Water Data Library Database (WDL) for discrete “grab” water quality sampling stations. The WDL database contains DWR-collected, current and historical, chemical and physical parameters found in drinking water, groundwater, and surface waters throughout the state. This dataset is comprised of a Stations point feature class and a related “Period of Record by Station and Parameter” table. The Stations point feature class contains basic information about each station including station name, station type, latitude, longitude, and the dates of the first and last sample collection events on record. The related Period of Record Table contains the list of parameters (i.e. chemical analyte or physical parameter) collected at each station along with the start date and end date (period of record) for each parameter and the number of data points collected. The Lab and Field results data associated with this discrete grab water quality stations dataset can be accessed from the California Natural Resources Agencies Open Data Platform at https://data.cnra.ca.gov/dataset/water-quality-data or from DWR’s Water Data Library web application at https://wdl.water.ca.gov/waterdatalibrary/index.cfm.

Original provider: Florida Fish and Wildlife Conservation Commission - Fish and Wildlife Research Institute

Dataset credits: Florida Fish and Wildlife Conservation Commission - Fish and Wildlife Research Institute

Abstract: This dataset contains data from the geographic information system (GIS) shapefile of recovered Florida manatee (Trichechus manatus latirostris) carcass locations within Florida from April 1974 through to the latest spatially verified data presently available. Locations are based both on coordinates provided by field staff (gathered either by geographic positioning system [GPS] or by using navigation charts to ascertain latitudes and longitudes) and maps provided by the field staff. Fish and Wildlife Research Institute (FWRI) GIS staff in the Marine Mammal subsection verify that the provided coordinates match the intent of the plotted location. Points representing carcass locations were entered into a GIS using a digital shoreline basemap taken largely from NOAA navigation charts (1:40,000) and from USGS quadrangles (1:24,000). The scale is considered to be 1:40,000.

What does the data show?

This data shows the monthly averages of maximum surface temperature (°C) for 2070-2099 using a combination of the CRU TS (v. 4.06) and UKCP18 global RCP2.6 datasets. The RCP2.6 scenario is an aggressive mitigation scenario where greenhouse gas emissions are strongly reduced.

The data combines a baseline (1981-2010) value from CRU TS (v. 4.06) with an anomaly from UKCP18 global. Where the anomaly is the change in temperature at 2070-2099 relative to 1981-2010.

The data is provided on the WGS84 grid which measures approximately 60km x 60km (latitude x longitude) at the equator.

Limitations of the data

We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.

What are the naming conventions and how do I explore the data?

This data contains a field for each month’s average over the period. They are named 'tmax' (temperature maximum), the month and ‘upper’ ‘median’ or ‘lower’. E.g. ‘tmax Mar Lower’ is the average of the daily minimum temperatures in March throughout 2070-2099, in the second lowest ensemble member.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘tmax Jan Median’ values.

What do the ‘median’, ‘upper’, and ‘lower’ values mean?

Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.

To select which ensemble members to use, the monthly averages of maximum surface temperature for the period 2070-2099 were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location.

The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.

This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.

Data source

CRU TS v. 4.06 - (downloaded 12/07/22)

UKCP18 v.20200110 (downloaded 17/08/22)

Useful links

Further information on CRU TS Further information on the UK Climate Projections (UKCP) Further information on understanding climate data within the Met Office Climate Data Portal