Use this app to explore and visualise native title data, supporting the Native Title Act 1993 (Cth). About the data in this appCustodial geospatial data held by the National Native Title Tribunal (NNTT) consists of those datasets necessary to contribute to the statutory functions associated with Registers and other information, in support of the Native Title Act 1993 (Cth).Whilst these datasets do not form part of the statutory registers, they enable the visualisation and ability to search on these matters.For more information, see Native Title.Key featuresInteractive map: Zoom and pan in the interactive map to explore native title data. Layer control: Toggle between various map layers to customise your viewing experience. Add data: Add data to create your own custom map. Export: Export map views and native title data in various formats for your research. CurrencyModification frequency: As needed, refer to the Native Title dataset for details.ContactDigital Atlas of AustraliaChangelog Version 1.1.0 (2025-06-19)

Minor content changes Retitled app. Previous title: Native title

Version 1.0.0 (2024-08-23) ArcGIS Experience Builder app configured with the following: Native Title mapLocation search and other location toolsMap creation tools, such as map base map, add data and map layersLegendDrawing and measure toolsAnalysis tools, such as table and selectPrintHelp

The Digital City Map (DCM) data represents street lines and other features shown on the City Map, which is the official street map of the City of New York. The City Map consists of 5 different sets of maps, one for each borough, totaling over 8000 individual paper maps. The DCM datasets were created in an ongoing effort to digitize official street records and bring them together with other street information to make them easily accessible to the public. The Digital City Map (DCM) is comprised of seven datasets; Digital City Map, Street Center Line, City Map Alterations, Arterial Highways and Major Streets, Street Name Changes (areas), Street Name Changes (lines), and Street Name Changes (points). All of the Digital City Map (DCM) datasets are featured on the Streets App All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

The .csv table is part of a dataset package that was compiled for use as mineral assessment guidance in the Sagebrush Mineral-Resource Assessment project (SaMiRA). Mineral potential maps from previous mineral-resource assessments which included areas of the SaMiRA project areas were georeferenced. The images were clipped to the extent of the map and all explanatory text, gathered from map explanations or report text, was recorded into this table. This table is to be used in conjunction with the individual georeferenced raster images. It includes the image file name, map title and figure caption when appropriate. The images are also classified according to the legal definition of mineral resources: metallic, non-metallic, leasable non-fuel, leasable fuel, geothermal, paleontological, and saleable.

Introduction and Rationale: Due to our increasing understanding of the role the surrounding landscape plays in ecological processes, a detailed characterization of land cover, including both agricultural and natural habitats, is ever more important for both researchers and conservation practitioners. Unfortunately, in the United States, different types of land cover data are split across thematic datasets that emphasize agricultural or natural vegetation, but not both. To address this data gap and reduce duplicative efforts in geospatial processing, we merged two major datasets, the LANDFIRE National Vegetation Classification (NVC) and USDA-NASS Cropland Data Layer (CDL), to produce an integrated land cover map. Our workflow leveraged strengths of the NVC and the CDL to produce detailed rasters comprising both agricultural and natural land-cover classes. We generated these maps for each year from 2012-2021 for the conterminous United States, quantified agreement between input layers and accuracy of our merged product, and published the complete workflow necessary to update these data. In our validation analyses, we found that approximately 5.5% of NVC agricultural pixels conflicted with the CDL, but we resolved a majority of these conflicts based on surrounding agricultural land, leaving only 0.6% of agricultural pixels unresolved in our merged product. Contents: Spatial data

Attribute table for merged rasters

Technical validation data

Number and proportion of mismatched pixels Number and proportion of unresolved pixels Producer's and User's accuracy values and coverage of reference data Resources in this dataset:Resource Title: Attribute table for merged rasters. File Name: CombinedRasterAttributeTable_CDLNVC.csvResource Description: Raster attribute table for merged raster product. Class names and recommended color map were taken from USDA-NASS Cropland Data Layer and LANDFIRE National Vegetation Classification. Class values are also identical to source data, except classes from the CDL are now negative values to avoid overlapping NVC values. Resource Title: Number and proportion of mismatched pixels. File Name: pixel_mismatch_byyear_bycounty.csvResource Description: Number and proportion of pixels that were mismatched between the Cropland Data Layer and National Vegetation Classification, per year from 2012-2021, per county in the conterminous United States.Resource Title: Number and proportion of unresolved pixels. File Name: unresolved_conflict_byyear_bycounty.csvResource Description: Number and proportion of unresolved pixels in the final merged rasters, per year from 2012-2021, per county in the conterminous United States. Unresolved pixels are a result of mismatched pixels that we could not resolve based on surrounding agricultural land (no agriculture with 90m radius).Resource Title: Producer's and User's accuracy values and coverage of reference data. File Name: accuracy_datacoverage_byyear_bycounty.csvResource Description: Producer's and User's accuracy values and coverage of reference data, per year from 2012-2021, per county in the conterminous United States. We defined coverage of reference data as the proportional area of land cover classes that were included in the reference data published by USDA-NASS and LANDFIRE for the Cropland Data Layer and National Vegetation Classification, respectively. CDL and NVC classes with reference data also had published accuracy statistics. Resource Title: Data Dictionary. File Name: Data_Dictionary_RasterMerge.csv

This dataset provides title information (excluding ownership) where there is a relationship to one or more primary parcels.

A Record of Title is a record of a property's owners, legal description and the rights and responsibilities registered against the title.This dataset does not contain any ownership information so that it can be freely distributed. If ownership information is required, you need to apply for access.

There can be multiple parcels associated with a title, and a title may only have a part share in a parcel. This means the shape representing the title will be an aggregation of all parcels that the title is associated with. The ‘spatial extents shared’ attribute when equal to ‘false’ will indicate that title has exclusive interest over all of the shape (this will be case for the vast majority).

The originating data for parcel/title associations includes some non-official sources where the official data does not support a link. For more information see the LINZ website

APIs and web services This dataset is available via ArcGIS Online and ArcGIS REST services, as well as our standard APIs. LDS APIs and OGC web services ArcGIS Online map services

Abstract Custodial geospatial data held by the National Native Title Tribunal (NNTT) consists of those datasets necessary to contribute to the statutory functions associated with Registers and other information, in support of the Native Title Act 1993 (Cth). Whilst these datasets do not form part of the statutory registers, they enable the visualisation and ability to search on these matters. Currency Refer to the individual layer for date last updated. Modification frequency: As needed Data extent Spatial extent North: -8.881900° South: -43.193600° East: 163.192100° West: 109.233400° Source information The data is downloadable from the NNTT website Further information can be found on the NNTT's GIS page Lineage statement This data can be downloaded from the NNTT website and accessed through the NNTT Feature Service Contact Geoscience Australia, clientservices@ga.gov.au Data Dictionary The Geospatial corporate data model contains a brief data and dictionary definition for each geospatial dataset: Tribunal Geospatial Corporate Data Model Contact Geoscience Australia, clientservices@ga.gov.au

Digital data is provided for the indexes of: - 1:100,000 scale topographic maps - 1:250,000 scale topographic maps - 1:1,000,000 scale General Reference maps

These indexes are those used in the online map index dashboards and web maps. They contain value-add attributes, including map number, map name, map title, year published, the latitude and longitude of the extents of the maps sheets and data tiles covering Australia. They also include a link to download the map.

Available in ESRI Shapefile and GDB.

eXtension Foundation, the University of New Hampshire, and Virginia Tech have developed a mapping and data exploration tool to assist Cooperative Extension staff and administrators in making strategic planning and programming decisions. The tool, called the National Extension Web-mapping Tool (or NEWT), is the key in efforts to make spatial data available within cooperative extension system. NEWT requires no GIS experience to use. NEWT provides access for CES staff and administrators to relevant spatial data at a variety of scales (national, state, county) in useful formats (maps, tables, graphs), all without the need for any experience or technical skills in Geographic Information System (GIS) software. By providing consistent access to relevant spatial data throughout the country in a format useful to CES staff and administrators, NEWT represents a significant advancement for the use of spatial technology in CES. Users of the site will be able to discover the data layers which are of most interest to them by making simple, guided choices about topics related to their work. Once the relevant data layers have been chosen, a mapping interface will allow the exploration of spatial relationships and the creation and export of maps. Extension areas to filter searches include 4-H Youth & Family, Agriculture, Business, Community, Food & Health, and Natural Resources. Users will also be able to explore data by viewing data tables and graphs. This Beta release is open for public use and feedback. Resources in this dataset:Resource Title: Website Pointer to NEWT National Extension Web-mapping Tool Beta. File Name: Web Page, url: https://www.mapasyst.org/newt/ The site leads the user through the process of selecting the data in which they would be most interested, then provides a variety of ways for the user to explore the data (maps, graphs, tables).

Conservation planning in the Great Plains often depends on understanding the degree of fragmentation of the various types of grasslands and savannas that historically occurred in this region. To define ecological subregions of the Great Plains, we used a revised version of Kuchler’s (1964) map of the potential natural vegetation of the United States. The map was digitized from the 1979 physiographic regions map produced by the Bureau of Land Management, which added 10 physiognomic types. All analyses are based on data sources specific to the United States; hence, we only analyze the portion of the Great Plains occurring in the United States.We sought to quantify the current amount of rangeland in the US Great Plains converted due to 1) woody plant encroachment; 2) urban, exurban, and other forms of development (e.g., energy infrastructure); and 3) cultivation of cropland. At the time of this analysis, the most contemporary measure of land cover across the United States was the 2011 NLCD (Homer et al. 2015). One limitation of the NLCD is that some grasslands with high rates of productivity, such as herbaceous wetlands or grasslands along riparian zones, are misclassified as cropland. A second limitation is the inability to capture cropland conversion occurring after 2011 (Lark et al. 2015). Beginning in 2009 (and retroactively for 2008), the US Department of Agriculture - NASS has annually produced a Cropland Data Layer (CDL) for the United States from satellite imagery, which maps individual crop types at a 30-m spatial resolution. We used the annual CDLs from 2011 to 2017 to map the distribution of cropland in the Great Plains. We merged this map with the 2011 NLCD to evaluate the degree of fragmentation of grasslands and savannas in the Great Plains as a result of conversion to urban land, cropland, or woodland. We produced two maps of fragmentation (best case and worst case scenarios) that quantify this fragmentation at a 30 x 30 m pixel resolution across the US Great Plains, and make them available for download here. Resources in this dataset: Resource title: Data Dictionary for Figure 2 derived land cover of the US portion of the North American Great Plains File name: Figure2_Key for landcover classes.csv Resource title: Figure 1. Potential natural vegetation of US portion of the North American Great Plains, adapted from Kuchler (1964). File name: Figure1_Kuchler_GPRangelands.zip Resource description: Extracted grassland, shrubland, savanna, and forest communities in the US Great Plains from the revised Kuchler natural vegetation map Resource title: Figure 2. Derived land cover of the US portion of the North American Great Plains. File name: Figure2_Key for landcover classes.zip Resource description: The fNLCD-CDL product estimates that 43.7% of the Great Plains still consists of grasslands and shrublands, with the remainder consisting of 40.6% cropland, 4.4% forests, 3.0% UGC, 3.0% developed open space, 2.9% improved pasture or hay fields, 1.2% developed land, 1.0% water, and 0.2% barren land, with important regional and subregional variation in the extent of rangeland loss to cropland, forests, and developed land. Resource title: Figure 3. Variation in the degree of fragmentation of Great Plains measured in terms of distance to cropland, forest, or developed lands. File name: Figure3_bestcase_disttofrag.zip Resource description: This map depicts a “best case” scenario in which 1) croplands are mapped based only on the US Department of AgricultureNational Agricultural Statistics Service Cropland Data Layers (2011e2017), 2) all grass-dominated cover types including hay fields and improved pasture are considered rangelands, and 3) developed open space (as defined by the National Land Cover Database) are assumed to not be a fragmenting land cover type. Resource title: Figure 4. Variation in the degree of fragmentation of Great Plains measured in terms of distances to cropland, forest, or developed lands. File name: Figure4_worstcase_disttofrag.zip Resource description: This map depicts a ‘worst case’ scenario in which 1) croplands are mapped based on the US Department of AgricultureNational Agricultural Statistics Service Cropland Data Layers (2011e2017) and the 2011 National Land Cover Database (NLCD), 2) hay fields and improved pasture are not included as rangelands, and 3) developed open space (as defined by NLCD) is included as a fragmenting land cover type.

The map title is Rock Types. Map scale. North arrow pointing to the north. Map projection is Hammer-Aitoff. Border of Canada. Great Lakes Border for each theme category within Canada. Neat line around the map. Each theme category is identified by a number that corresponds to the legend. Legend is divided into three categories: Metamorphic rocks, Deformed Sedimentary and Igneous rocks, Flat Lying Sedimentary rocks. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

This series consists of a cadastral maps used to show application numbers for the conversion of General Law land deeds into Torrens system titles.

The first land tenure system to be introduced into Victoria in March 1838 was called the 'General Law' or 'Old Law System', or more commonly called today, NUA (Not Under Act). Land under the Torrens system (Real Property Act 1862) was therefore 'under Act'. This system was directly based on the principles of the English Common Law.

Under the General Law system, land ownership was based on a set of deeds, being the original deed held by the owner and a Memorial which was generally registered at the RGO. These documents helped prove ownership back to the Crown Grant, although there was no compulsion under this system to register the Memorial with the RGO.

Title was proven by producing the collection of deeds, which was commonly called the ‘Chain of Title’ held by successive owners, as well as a search of the Memorials lodged at the RGO. A Memorial is a copy of the original deed. Every time land changed hands, the chain of deeds needed to be produced and a new deed/Memorial needed to be drawn up by lawyers. It was a cumbersome and expensive system, in which the risk of deeds being lost or destroyed was high. Land ownership in the General Law system was and is still not guaranteed by the Victorian government.

The maps in this series were primarily created to identify active conversion areas, which were most commonly metropolitan areas. The maps were created by the Registrar Generals’ Office (RGO) to track and identify the application numbers for General Law conversion applications in the area depicted on the map. An application number was allocated to each parcel of land when the owner applied to have it converted from the original General Law deed into a title under the new Torrens system. This number was used in several General Law land ownership series, and is identified by the prefix AP, e.g. AP12345. The application number was unique to each application and can be used to track records about a particular parcel of land and its conversion to a title over multiple series.

The introduction of the Torrens system in Victoria on 2 October 1862, made legislative provisions under the Transfer of Land Act for owners of General Law land to voluntarily convert their land to the Torrens system of land ownership. Although the expectation was that all land would be brought under the operation of the Transfer of Land Act fairly quickly, this did not prove to be the case. In the mid-1980s, after 120 years of operation of the Torrens system, large areas of land remained under the General Law system. The registration of Memorials continued until the 31 December 1998 when the register was closed. This was an effort to help speed up the Conversion process, as all new land transactions would have to be conducted under the Transfer of Land Act following an application to convert the deed into a certificate of title.

Most marketable parcels of land under the General law ownership have now been converted to the Torrens system.

Sample Description (this text reside in the 'Map Document Properties - 'Description' section)

Satellite imagery for the request links.mr10000027 from 2022-08-06 22:00:00 to 2022-09-05 22:00:00 - uploaded by LINKS

ADMMR map collection: The United Globes Mines Maps - Title Page; 34 x 22 in.

In order to exploit mineral raw materials close to the Earth's surface, experts are working on trans-regional and national planning documents. To do this, they need maps which clearly depict the raw materials close to the surface in Germany.

KOR200 displays Germany's national raw material potential in a comparable way, thus forming a basis for future exploration and investigations as well as making a contribution towards the assurance of the supply of raw materials.

The map follows the sheet line system of the topographical survey map 1:200.000 (TÜK 200) and consists of 55 sheets, each with an explanatory booklet. There is a review of the current situation, a description, a depiction and documentation of the occurrence and deposits of mineral raw materials which are usually extracted in mines either on or close to the Earth's surface. Such deposits include, in particular, industrial minerals, rocks and soils, peat, lignite, oil shale and brines.

Besides the delimited deposits and areas of raw materials coloured according to the raw material in question, the maps also depict "mining areas" (=operations) or "focal points of several mining areas", each marked with a symbol.

The map entries are - just as with the topographical basis - recorded in digitalised form in a databank, from which they can be retrieved via a computer using various search criteria.

The entries in the map are supplemented by between 40 to 80 pages of textual explanations, which are currently available only in the printed edition of the map.

The text is divided into: - introduction - description of the deposits and occurrence of useful rocks - supply and demand assessment of the deposits and occurrence of raw materials close to the Earth's surface in the area covered by the sheet - possible ways of using the useful rocks present in the sheet area - list of publications - appendix (with, amongst other things, a general legend and survey of sheets)

Vacant property owned and managed by the City of Chicago Department of Housing and Economic Development. Information provided in the database, or on the City’s website generally, should not be used as a substitute for title research, title evidence, title insurance, real estate tax exemption or payment status, environmental or geotechnical due diligence, or as a substitute for legal, accounting, real estate, business, tax or other professional advice. The City assumes no liability for any damages or loss of any kind that might arise from the reliance upon, use of, misuse of, or the inability to use the LIS database or the City’s web site and the materials contained on the website. The City also assumes no liability for improper or incorrect use of materials or information contained on its website. All materials that appear in the LIS database or on the City’s web site are distributed and transmitted "as is," without warranties of any kind, either express or implied as to the accuracy, reliability or completeness of any information, and subject to the terms and conditions stated in this disclaimer.

MapViewer is a graphical tool for viewing and comparing Gossypium spp. genetic maps. It includes dynamically scrollable maps, correspondence matrices, dot plots, links to details about map features, and exporting functionality. It was developed by the MainLab at Washington State University and is available for download for use in other Tripal databases. The query interface allows the user to select Species, Map, and Linkage Group options. Help information includes a video tutorial, user manual, and sample map, correspondence matrix, dot plot, and exported figures. Resources in this dataset:Resource Title: Website Pointer for CottonGen Map Viewer. File Name: Web Page, url: https://www.cottongen.org/MapViewer MapViewer is a graphical tool for viewing and comparing Gossypium spp. genetic maps. It includes dynamically scrollable maps, correspondence matrices, dot plots, links to details about map features, and exporting functionality. It was developed by the MainLab at Washington State University and is available for download for use in other Tripal databases. The query interface allows the user to select Species, Map, and Linkage Group options. Help information includes a video tutorial, user manual, and sample map, correspondence matrix, dot plot, and exported figures.

Map Tools is a configurable app template that enables you to display an ArcGIS web map using a variety of tools.Use CasesDisplays a set of commonly used tools in a more traditional toolbar-driven user experience. The app includes the ability to toggle layer visibility, print a map, and view a table of attributes.Configurable OptionsThe template can be configured using the following options:Map:Choose the web map used in your application.Color Scheme: Choose between five color schemes for the application.Show Title: Choose whether to include an application title.Title Text: The application title. The default title is the web map name.Logo: Choose a custom logo for your application.Legend: Display a legend for map layers.Details: Display the web map item description.Print: Enables printing the map at the current extent. It can be configured to include a legend and supports different layout options.Layer List: Enables toggling the visibility of operational layers within the web mapBasemaps: Enables the display of the basemap gallery.Bookmarks: Enables the use of web map bookmarks for navigation.Share: Allows users to share the application with others.Search: Displays the Search box to enable navigation to addresses and places.Search for locations within current extent: Enable toggling of search within the current map extent only.Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to create a web appOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.

The map title is British Columbia. Tactile map scale. 1.8 centimetres = 100 kilometres North arrow pointing to the top of the page. Borders of the province of British Columbia, shown as dashed and solid lines. The Pacific Ocean, shown with a wavy symbol to indicate water. A circle and the city name to show the location of Prince George and Vancouver. A filled star and the city name to show the location the capital of the province, Victoria. Text labels for the Pacific Ocean and Fraser River. The word lake is abbreviated as L. The abbreviation "AB" to indicate the province of Alberta. The abbreviation "YT" to indicate the Yukon Territory. The abbreviation "NT" to indicate the Northwest Territories. The abbreviation "USA" to indicate the neighbouring country, The United States of America. The abbreviation "AK" to indicate the State of Alaska. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

The Digital City Map (DCM) data represents street lines and other features shown on the City Map, which is the official street map of the City of New York. The City Map consists of 5 different sets of maps, one for each borough, totaling over 8000 individual paper maps. The DCM datasets were created in an ongoing effort to digitize official street records and bring them together with other street information to make them easily accessible to the public. The Digital City Map (DCM) is comprised of seven datasets; Digital City Map, Street Center Line, City Map Alterations, Arterial Highways and Major Streets, Street Name Changes (areas), Street Name Changes (lines), and Street Name Changes (points).

All of the Digital City Map (DCM) datasets are featured on the Streets App

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

Updates for this dataset, along with other multilayered maps on NYC Open Data, are temporarily paused while they are moved to a new mapping format. Please visit https://www.nyc.gov/site/planning/data-maps/open-data/dwn-digital-city-map.page to utilize this data in the meantime.