The "Map Imager Layer - Administrative Boundaries" is a Map Image Layer of Administrative Boundaries. It has been designed specifically for use in ArcGIS Online (and will not directly work in ArcMap or ArcPro). This data has been modified from the original source data to serve a specific business purpose. This data is for cartographic purposes only.The Administrative Boundaries Data Group contains the following layers: Populated Places (USGS)US Census Urbanized Areas and Urban Clusters (USCB)US Census Minor Civil Divisions (USCB)PLSS Townships (MnDNR, MnGeo)Counties (USCB)American Indian, Alaska Native, Native Hawaiian (AIANNH) Areas (USCB)States (USCB)Countries (MPCA)These datasets have not been optimized for fast display (but rather they maintain their original shape/precision), therefore it is recommend that filtering is used to show only the features of interest. For more information about using filters please see "Work with map layers: Apply Filters": https://doc.arcgis.com/en/arcgis-online/create-maps/apply-filters.htmFor additional information about the Administrative Boundary Dataset please see:United States Census Bureau TIGER/Line Shapefiles and TIGER/Line Files Technical Documentation: https://www.census.gov/programs-surveys/geography/technical-documentation/complete-technical-documentation/tiger-geo-line.htmlUnited States Census Bureau Census Mapping Files: https://www.census.gov/geographies/mapping-files.htmlUnited States Census Bureau TIGER/Line Shapefiles: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html and https://www.census.gov/cgi-bin/geo/shapefiles/index.php

Point features representing nodes in the sewer and stormwater collection system. These features include manholes, cleanouts, outfalls, valves, and other types of collection nodes.-- Additional Information: Category: Collection System Purpose: For mapping and analysis of the BES Collection System. Update Frequency: Continuous-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=52646

Information from mapping polymorphisms on the genome. Derived from "Dump JSNP" http://snp.ims.u-tokyo.ac.jp/map/cgi-bin/Dump/snp_region_filter.cgi .

The original historic plat maps for Wisconsin were created between 1832 and 1866. In most cases, the UW Digital Collections Center does not record a specific creation date for the original maps. However, the collection also contains maps which correct previous editions. These more modern maps typically have a specific date or year defined. To view the survey notes associated with this plat map, please visit http://digicoll.library.wisc.edu/cgi-bin/SurveyNotes/SurveyNotes-idx?type=PLSS&town=T013N&range=R004W.

Describes the mapped plot data and the mapped plot site data taken by TE-23.

New Zonage “A/B/C” applicable from 01/10/2014 (Ministerial Decree of 01 August 2014).

The “A/B/C” zoning, created in 2003 at the time when Robien’s rental investment scheme was introduced, characterises the tension of the local real estate market, i.e. the adequacy of the demand for and the supply of available housing on a territory. It consists of five modalities ranging from the most tense (Abis) to the most relaxed (C).Franche-Comté is only affected by zones B2 and C. Several financial schemes use this zoning to determine the eligibility of territories for aid or to adjust their parameters (level of aid, ceiling of rents, etc.). These include the Intermediate Rental Investment Facility for Individuals (see Duflot Zoning), the Old Borloo, the Intermediate Rental Loan (PLI), the Zero Rate Loan (PTZ), the Social Accession Rental Loan (PSLA) and the Social Access Loan (PAS) to property, and the reduced rate VAT in the ANRU area.Some ANAH aid to social lenders is also linked to a ceiling on rent and the amount of resources of the tenant, which varies according to the zoning A/B/C. Following a consultation conducted by the Regional Prefect with the local authorities in the 4th quarter of 2013, the new zoning A/B/C was adopted by the Minister in charge of Housing on 1 August 2014. For Franche-Comté, 19 new municipalities were reclassified from C to B2, while no decommissioning was recorded. Its entry into force varies between 1 October 2014 and 1 February 2015 depending on the arrangements attached to it:

as of 1 October 2014 for: — the zero-rate loan; — the guarantee scheme of the FGAS; — the reduced rate VAT scheme for intermediate rental accommodation (279-0a A of the CGI); — the aid scheme for intermediate rental investment for private individuals (199 novitiies of the General Tax Code (CGI); — promises of sales of public land, pursuant to Article R. 3211-15 of the General Code of Ownership of Public Persons;

on 1 January 2015 for: — the benefit of aid from the National Housing Agency, the ‘old Borloo’ tax scheme; — the intermediate rental loan; — reduced VAT in ANRU area; — devices related to HLM promotion; — the assessment of resources for new intermediate dwellings held by HLML bodies in the context of their service of general economic interest;

as of 1 February 2015 for: — approvals of social loans for leasing-accession.

Data sources: order of the Minister of Housing dated 01 August 2014

This file of geologic unit polygons is for educational use. There are known errors and omissions. The file is part of a recompilation of the 1968 Geologic Map of Maryland.DATA is for educational use only - there are known errors and omissions. These data are only valid for the intended use. The user is responsible for the outcome of the data resulting from use of this product. Neither the licensor, nor the owner of these data makes any warranties of merchantability or fitness for a particular purpose of use. Disclaimer for Towson University, CGIS and for Martin F. Schmidt, Jr. ("GIS FILE ORIGINATORS"): THE LICENSEE EXPRESSLY ACKNOWLEDGES THAT THE DATA CONTAIN SOME NONCONFORMITIES, DEFECTS, OR ERRORS. GIS FILE ORIGINATORS DO NOT WARRANT THAT THE DATA WILL MEET LICENSEE'S NEEDS OR EXPECTATIONS; THAT THE USE OF THE DATA WILL BE UNINTERUPPTED; OR THAT ALL NONCONFORMITIES, DEFECTS, OR ERRORS CAN OR WILL BE CORRECTED. GIS FILE ORIGINATORS ARE NOT INVITING RELIANCE ON THIS DATA, AND THE LICENSEE SHOULD ALWAYS VERIFY ACTUAL DATA. THE DATA AND RELATED MATERIALS CONTAIN THEREIN ARE PROVIDED "AS-IS," WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR USE. Acknowledgement of Towson University Center for Geographic Information Sciences & Martin F. Schmidt, Jr., for the educational GIS file and credit to the original authors/compilers of the source map are expected in products derived from this data.This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Geoscientific/MD_Geology/MapServer/0

A variety of cumulative (over reporting periods) data points for Rescue Plan projects: individual recipient count, business recipient count, non profit recipient count, and expenditure.-- Additional Information: Category: ARPA Update Frequency: As Necessary-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=61045

This data was collected by St. Louis County Board of Elections. It is part of a larger collection (Historical St. Louis County Elections), organized by municipality. Faculty in the Department of Political Science at Washington University in St. Louis, Dr. Brian Crisp and Dr. Matt Gabel, digitized the materials at Washington University in St. Louis and agreed with St. Louis County to have the digital copies deposited in the Open Scholarship Digital Research Materials Repository at Washington University to make it more widely accessible.

This dataset is based on the Geologic Map of North America (scale 1 to 3,000,000, Reed et al., 2005) from DDS 424 (Garrity and Soller, 2009) and the Sherrod et al. (2007) compilation of Hawaii (scale 1 to 100000). The dataset is distributed as the USA USGIN 3M Geology Web Map Service (WMS) by the Arizona Geological Survey for inclusion with One Geology. Data were prepared by clipping data from Garrity and Soller (2009) to the boundaries of the United States including the offshore exclusive economic zone, as defined by NOAA (coastalmap.marine.usgs.gov/GISdata/basemaps/boundaries/eez/NOAA/useez_noaa.htm). US Pacific Island territories are not included. Data for Hawaii were acquired from Sherrod et al. (2007), and units were reclassified to better match the granularity of the Reed et al. (2005) map, and boundaries between reclassified units were dissolved to simplify the map. Offshore data around Hawaii were not found that could be included in the compilation. Data from Garrity and Soller (2009) and the Sherrod et al. (2007) generalization were merged into a single database using the NCGMP09 data structure (USGS NCGMP, 2010). Representative lithology and age properties were associated with each map unit. These property values are specified using CGI vocabularies for rock type (CGI Simple Lithology, resource.geosciml.org/Vocab2011html/SimpleLithology201012.html) and stratigraphic age (International Stratigraphic Chart, 2009-08, resource.geosciml.org/ISC2009/CGI2011TimeScale.rdf). Finer-scale granularity on some polygon-level representative lithology and age assignments than that presented in the Reed et al. (2005) mapping using the state geologic map compilation by the USGS Mineral Resources Division (e.g. Ludington et al., 2007). Data were exported from the NCGMP09 database into database tables conforming to the CGI GeoSciML Portrayal schema, and web services are deployed using these tables as the data source. Spatial data from Garrity and Soller (2009) has been reprojected into WGS 1984 decimal degrees. The Web map service view of the data presents three portrayals, based on representative age, representative lithology and lithostratigraphy. The representative age portrayal uses the color scheme presented on the International Stratigraphic Chart, 2009-08 (pdf cached at resource.geosciml.org/ISC2009/ISChart2009.pdf). RGB and CMYK colors for this legend were imported from OneGeology Europe color scheme (Asch et al., 2009, accessed at onegeology-europe.brgm.fr/how_to201002/OneGeologyWP3-DataSpec_Portrayal_v 201 205KA.doc, Table 1-1). The color scheme for the representative lithology portrayal was updated from a scheme developed by the GeoSciML workgroup (thanks to Eric Boisvert, GSC) using URN identifiers; the colors in that scheme were creatively adapted from Moyer,Hasting and Raines (2005, pubs.usgs.gov/of/2005/1314/of2005-1314.pdf) which provides xls spreadsheets for various color schemes. Most of the colors come from lithclass 6.1 and 6.2 (see www.nadm-geo.org/dmdt/pdf/lithclass61.pdf for lithclass 6.1). The lithostratigraphic scheme was created from the map legend included with Garrity and Soller (2009) by removing overlay patterns because they are incompatible with OGC Styled Layer Description (SLD) of map symbolization, and adjusting colors to preserve distinction between map units defined by Reed et al. (2005). Portrayal of the contact and fault themes use conventional geologic map symbolization. Additional feature classes that can not be mapped into the GeoSciML Portrayal scheme are included on the Reed et al. (2005) map and were digitized by Garrity and Soller (2009). These features are not currently exposed via web services. The additional features were clipped to the extent of the US geology polygons, and have been included in the NCGMP09-format geodatabase distribution of this dataset. Miscellaneous geologic line features including special submarine features, calderas, glaciation extent, impact structure outlines from Reed et al. (2005) were digitized by Garrity and Soller (2009) into a variety of feature classes. These were merged into a single otherLines feature class in the NCGMP09 version of the dataset. FeatureType terms correspond to the names of the original feature classes or feature types within the original feature classes if there were multiple kinds of features. Miscellaneous geologic point features including diapirs, mineral occurrences, gas seeps, hydrothermal vents, unusual igneous rock occurrences, volcanic vents from Reed et al. (2005) were digitized by Garrity and Soller (2009) into a variety of feature classes. These were merged into a single geoPointFeature feature class as an extension to the NCGMP09 model in this dataset. FeatureType terms correspond to the names of the original feature classes or feature types within the original feature classes if there were multiple kinds of features. Miscellaneous geologic overlay polygons that delineate areas of metamorphism, continental deposits, zones of abundant diapirs, and offshore outcrops (?) from Reed et al. (2005) were digitized by Garrity and Soller (2009) into multiple feature classes. These were merged back into a single OverlayPoly feature class of the NCGMP09 model. FeatureType terms correspond to the names of the original feature classes or feature types within the original feature classes if there were multiple kinds of features. References Garrity, C.P., and Soller, D.R., 2009, Database of the Geologic Map of North America- Adapted from the Map by J.C. Reed, Jr. and others (2005), U. S. Geological Survey USGS Data Series DS-DS424, 1 CDROM. 2009 Sherrod, D. R., Sinton, J. M., Watkins, S. E., and Brunt, K. M., 2007, Geologic Map of the State of Hawai I Reston, VA, U. S. Geological Survey Open-File Report 2007 1089, resolution variable. Reed Jr., J. C., Wheeler, J.O., and Tucholke, J.E., 2005, Geologic Map of North America Geological Society of America, DNAG Continent Scale Map 001, Scale 1 to 5,000,000, 3 sheets. USGS National Cooperative Geologic Mapping Program (NCGMP), 2010, NCGMP09 Draft Standard Format for Digital Publication of Geologic Maps, Version 1.1 in Soller, D.R. Editor, Digital Mapping Techniques 2009 Workshop Proceedings USGS Open File Report 2010 1335, p. 93 147. (accessed at pubs.usgs.gov/of/2010/1335/pdf/usgs_of2010 1335_NCGMP09.pdf 2012/01/25) Ludington, Steve, Moring, B.C., Miller, R.J., Stone, P.A., Bookstrom, A.A., Bedford, D.R., Evans, J.G., Haxel, G.A., Nutt, C. J., Flyn, K.S., and Hopkins, M.J., 2007, Preliminary integrated geologic map databases for the United States, Western States: California, Nevada, Arizona, Washington, Oregon, Idaho, and Utah, Version 1.3, updated December 2007: U. S. Geological Survey Open file Report 2005 1305, accessed online at pubs.usgs.gov/of/2005/1305/ (2011/11/08).

In ArcGIS OnLine an active join (one to many) was created between each town's parcel bounds and related assess table. In ArcPro those 6 joined layers were merged together into one feature layer. This file provides faster response time in web apps that permit filtering the data. The properties of the layer are set in such a way that the boundaries will not appear on the map until zoomed in.Please note: Any building related information associated with the parcel may or may not represent ALL buildings on the parcel.All parcel data meets the MassGIS Level 3 Parcel data standard. Each town has a parcel data consultant (either CAI Technologies or CGIS) who compiles their parcel bounds and export assessing data. All users are encouraged to read the 'attribute' section of the MassGIS metadata so there is clear understanding as to what these data represent.

Timeseries data from 'MAPEL RANCH NEAR ROCKLAND LANDING 3NE (MAP)' (gov_noaa_nws_hads_mapel_ranch_ne) _NCProperties=version=2,netcdf=4.8.1,hdf5=1.12.2 cdm_data_type=TimeSeries cdm_timeseries_variables=station,longitude,latitude contributor_email=feedback@axiomdatascience.com contributor_name=Axiom Data Science contributor_role=processor contributor_role_vocabulary=NERC contributor_url=https://www.axiomdatascience.com Conventions=IOOS-1.2, CF-1.6, ACDD-1.3 defaultDataQuery=battery_voltage,battery_voltage_qc_agg,lwe_thickness_of_precipitation_amount,z,time,lwe_thickness_of_precipitation_amount_qc_agg&time>=max(time)-3days Easternmost_Easting=-121.477222 featureType=TimeSeries geospatial_lat_max=36.023333 geospatial_lat_min=36.023333 geospatial_lat_units=degrees_north geospatial_lon_max=-121.477222 geospatial_lon_min=-121.477222 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=0.0 geospatial_vertical_positive=up geospatial_vertical_units=m history=Downloaded from Hydrometeorological Automated Data System (HADS) at id=130916 infoUrl=https://sensors.ioos.us/#metadata/130916/station institution=Hydrometeorological Automated Data System (HADS) naming_authority=com.axiomdatascience Northernmost_Northing=36.023333 platform=fixed platform_name=MAPEL RANCH NEAR ROCKLAND LANDING 3NE (MAP) platform_vocabulary=http://mmisw.org/ont/ioos/platform processing_level=Level 2 references=https://hads.ncep.noaa.gov/cgi-bin/hads/interactiveDisplays/displayMetaData.pl?table=dcp&nesdis_id=CA2827FE,, sourceUrl=https://hads.ncep.noaa.gov/cgi-bin/hads/interactiveDisplays/displayMetaData.pl?table=dcp&nesdis_id=CA2827FE Southernmost_Northing=36.023333 standard_name_vocabulary=CF Standard Name Table v72 station_id=130916 time_coverage_end=2025-11-10T11:00:00Z time_coverage_start=2015-05-05T14:00:00Z Westernmost_Easting=-121.477222

This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of eight Landsat 7-ETM+ scenes from 1999 acquired from the Tropical Rain Forest Information Center (TRFIC) at Michigan State University. Nine land cover classes covering the Ji-Parana Basin were identified. There is one GeoTiff file with this data set.

Question Paper Solutions of chapter HTML, Image Maps, XML & CGI Scripts of Internet Technology, 7th Semester , Computer Science and Engineering

This web feature layer references the Chelsea Structures view dataset, which consists of 2-dimensional roof outlines ("roofprints") for all buildings larger than 150 square feet, as interpreted by a contractor (Rolta) for the whole area of the Commonwealth using DigitalGlobe ortho images obtained in 2011 and 2012, supplemented with LiDAR (Light Detection And Ranging) data collected from 2002 to 2011 for the eastern half of the state. The roofprints as delivered were enhanced by MassGIS using Normalized Digital Surface Models (NDSMs) derived from the same LiDAR data. Other layers were used, including the Level 3 Parcels, to aid in review, especially where LiDAR data were not available.This feature class is being updated using ortho imagery captured in 2013, 2014, 2015 and 2016. Last updated on 10/2/2017. Shapefile downloaded from MassGIS on 7/16/2019 by CGIS Mapping, LLC. Imported 6 updated building polygons as requested by the City of Chelsea, 7/16/2019.Original Chelsea Structures view dataset : (https://chelseamass.maps.arcgis.com/home/item.html?id=4ed8b550216341f3a40d882151548c7a),

This dataset is grids of peatland extent, peat depth, peatland organic carbon storage, peatland total nitrogen storage and approximate extent of ombrotrophic/minerotrophic peatlands.

The grids are geotiff files in 10 km pixel resolution projected in the World Azimuthal Equidistant projection. Note that the peat depth grid shows potential peat depth everywhere,also where there is no peatland cover. For files on peatland organic carbon, total nitrogen extent and extent of ombrotrophic/minerotrophic peatlands, there are separate files for Histosols (non-frozen peatlands) and Histels (frozen peatlands).

For further details on how the data was created we refer to the paper by Hugelius et al (2020) in the journal Proceedings of the National Academy of Sciences of the United States of America: "Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw" (https://www.pnas.org/cgi/doi/10.1073/pnas.1916387117)

Portrayal in which units are categorized according to the representative lithology from the CGI SimpleLithology vocabulary as specified by the representativeLithology_URI property in the underlying dataset. The data in this layer are portrayed based on lithology using the color scheme encoded in http://schemas.usgin.org/schemas/slds/LithologyCGI201001URI.sld. Lithology for polygons was assigned by intersecting polygon from Reed at al, 2005 with polygons in the state geologic map compilation for the lower 48 states by the USGS Mineral Resources division. In that map compilation, lithology was generalized to a major and minor rock type using the scheme documented in Ludington et al. 2007 (also known as LithClass 6). The LithClass6 categories were mapped into the CGI Simple Lithology vocabulary (see https://www.seegrid.csiro.au/wiki/CGIModel/ConceptDefinitionsTG) for OneGeology data integration by SM Richard. Lithology for polygons in Alaska, marine areas, Puerto Rico and Virgin Islands is based on mapping of lithogenetic categories from Reed et al, 2005 into the CGI simple Lithology vocabulary (see https://www.seegrid.csiro.au/wiki/CGIModel/ConceptDefinitionsTG) for OneGeology data integration by SM Richard. Lithology for polygons in Alaska, marine areas, Puerto Rico and Virgin Islands is based on mapping of lithogenetic categories from Reed et al, 2005 into the CGI simple Lithology vocabulary (see https://www.seegrid.csiro.au/wiki/CGIModel/ConceptDefinitionsTG) for OneGeology data integration by SM Richard.

The BOREAS RSS-08 team utilized Landsat TM images to perform mapping of snow extent over the SSA. This data set consists of two Landsat TM images which were used to determine the snow-covered pixels over the BOREAS SSA on 18-Jan-1993 and on 06-Feb-1994.

This data set, LBA-ECO LC-24 Forest Cover Map from MODIS, 500-m, South America: 2001, contains forest cover information for 2001 for all of South America. The data were collected by the MODerate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Earth Observing System, TERRA (AM-1) satellite platform and released by the MODIS science team as an image showing percent canopy cover. This information was then reclassified so that all pixels with a percent canopy cover greater than 40% (40% after the 1973 UNESCO standard) were classified as forest (a value of 1), and all other pixels were classified as non-forest (a value of 2). Water features were given a value of 3. This data has a pixel resolution of 500 meters and is unprojected with the WGS-1984 datum (Hansen et al. 2006). There is one GeoTIFF data file for this data set.

This data was collected by St. Louis County Board of Elections. It is part of a larger collection (Historical St. Louis County Elections), organized by municipality. Faculty in the Department of Political Science at Washington University in St. Louis, Dr. Brian Crisp and Dr. Matt Gabel, digitized the materials at Washington University in St. Louis and agreed with St. Louis County to have the digital copies deposited in the Open Scholarship Digital Research Materials Repository at Washington University to make it more widely accessible.