Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

ABSTRACT: The U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) has produced the Vegetation Spatial Database Coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). The vegetation map is of Acadia National Park (NP) and extended environs, providing 99,693 hectares (246,347 acres) of map data. Of this coverage, 52,872 hectares (130,650 acres) is non-vegetated ocean, bay, and estuary (53% of coverage). Acadia NP comprises 19,276 hectares (47,633 acres) of the total data coverage area (19%, 40% not counting ocean and estuary data). Over 7,120 polygons make up the coverage, each with map class description and, for vegetation classes, physiognomic feature information. The spatial database provides crosswalk information to all National Vegetation Classification System (NVCS) floristic and physiognomic levels, and to other established classification systems (NatureServe's U.S. Terrestrial Ecological System Classification, Maine Natural Community Classification, and the USGS Land Use and Land Cover Classification). This mapping project has identified 53 NVCS associations (vegetation communities) at Acadia National Park through analyses of vegetation sample data. These associations are represented in the map coverage with 33 map classes. With all vegetation types, land use classes, and park specific categories combined, 57 map classes define the ground features within the project area (58 classes including the class for no map data). Each polygon within the spatial database map is identified with one of these map classes. In addition, physiognomic modifiers are added to map classes representing vegetation to describe the vegetation structure within a polygon (density, pattern, and height). The spatial database was produced from the interpretation of spring 1997 1:15,840-scale color infrared aerial photographs. The standard minimum mapping unit (MMU) applied is 0.5 hectares (1.25 acres). The interpreted data were transferred and automated using base maps produced from USGS digital orthophoto quadrangles. The finished spatial database is a single seamless coverage, projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. The estimated overall thematic accuracy for vegetation map classes is 80%.

Map Direct focus for viewing Spatial Air Quality System (SAQS) data. Please refer to https://floridadep.gov/air/air-monitoring/content/floridas-air-quality for more information. Originally created on 03/12/2007, and moved to Map Direct Lite on 11/29/2016. Please contact GIS.Librarian@floridadep.gov for more information.

The list of study sites, meteorological stations and locations of interest that are shown on the Bonanza Creek Long Term Ecological Research site (BNZ LTER) internet map server (IMS, available at http://www.lter.uaf.edu/ims_intro.cfm) is generated from the LTER study sites database. The information is converted into a shapefile and posted to the IMS. Some study sites shown on the main LTER website will not appear on the IMS because they do not have location coordinates. In all cases the most up-to-date information will be found on the (study sites website ).

The spatial information represented on the IMS is available to the public according to the restrictions outlined in the LTER data policy. The dataset represented here consists of the map layers shown on the IMS. The information consists of shapefiles in Environmental Systems Research Institute (ESRI) format. Users of this dataset should be aware that the contents are dynamic. Portions of the information shown on the IMS are derived from the Bonanza Creek LTER databank and are constantly being updated.

Spatial data describing the catchment boundaries, roads, streams, wireless sensor network, and other items of interest within the study site of Providence, as well as the broader context of Sierra National Forest.

Click on Parent Folder to access all data and metadata that are currently available.

You may also click on individual file links to immediately download a file of the data.

NOTE: We are working to update individual data listings on this site. Current individual data files listed below may not represent all available data and metadata. Click on the Parent Folder link to access all files.

This report publishes a geologic digital spatial database (ORGEO) for the geologic map of Oregon by Walker and MacLeod (1991) which was originally printed on a single sheet of paper at a scale of 1:500,000 and accompanied by a second sheet for map unit descriptions and ancillary data. The spatial digital database (GIS) provided in this report supersedes an earlier digital edition by Raines and others (1996).

Spatial map of Taichung City in December 2019 to query administrative district statistical files

Maps and map applications of all kinds—interactive map viewers, downloadable maps, map collections and more—from all around King County government.

MAPDAT is a program for plotting spatial data held in the ORACLE relational database onto any map within the Australian region at any scale. MAPDAT also includes a system for defining geological structures, thus any geological structure can be stored in the database and plotted. The program enables the plotting of sample locations along with infomration specific to each location. The information can be displayed beside each point or in a list to the side of the map. The symbols can be sized proportionally to the value of a column in a table or a SQL expression. Town locations, survey paths, gridlines, survey areas, coastlines and other geographical lines can be plotted. The program does not compete with geographical information systems but fills a niche at a much lower level of complexity. As a result of its simplicity a minimum in setting up of data is required and using the program is very straight forward with the user always aware of the database operations being performed.

See full Data Guide here. This layer includes polygon features that depict protected open space for towns of the Protected Open Space Mapping (POSM) project, which is administered by the Connecticut Department of Energy and Environmental Protection, Land Acquisition and Management. Only parcels that meet the criteria of protected open space as defined in the POSM project are in this layer. Protected open space is defined as: (1) Land or interest in land acquired for the permanent protection of natural features of the state's landscape or essential habitat for endangered or threatened species; or (2) Land or an interest in land acquired to permanently support and sustain non-facility-based outdoor recreation, forestry and fishery activities, or other wildlife or natural resource conservation or preservation activities. Includes protected open space data for the towns of Andover, Ansonia, Ashford, Avon, Beacon Falls, Canaan, Clinton, Berlin, Bethany, Bethel, Bethlehem, Bloomfield, Bridgewater, Bolton, Brookfield, Brooklyn, Canterbury, Canton, Chaplin, Cheshire, Colchester, Colebrook, Columbia, Cornwall, Coventry, Cromwell, Danbury, Derby, East Granby, East Haddam, East Hampton, East Hartford, East Windsor, Eastford, Ellington, Enfield, Essex, Farmington, Franklin, Glastonbury, Goshen, Granby, Griswold, Groton, Guilford, Haddam, Hampton, Hartford, Hebron, Kent, Killingworth, Lebanon, Ledyard, Lisbon, Litchfield, Madison, Manchester, Mansfield, Marlborough, Meriden, Middlebury, Middlefield, Middletown, Monroe, Montville, Morris, New Britain, New Canaan, New Fairfield, New Milford, New Hartford, Newington, Newtown, Norfolk, North, Norwich, Preston, Ridgefield, Shelton, Stonington, Oxford, Plainfield, Plainville, Pomfret, Portland, Prospect, Putnam, Redding, Rocky Hill, Roxbury, Salem, Salisbury, Scotland, Seymour, Sharon, Sherman, Simsbury, Somers, South Windsor, Southbury, Southington, Sprague, Sterling, Suffield, Thomaston, Thompson, Tolland, Torrington, Union, Vernon, Wallingford, Windham, Warren, Washington, Waterbury, Watertown, West Hartford, Westbrook, Weston, Wethersfield, Willington, Wilton, Windsor, Windsor Locks, Wolcott, Woodbridge, Woodbury, and Woodstock. Additional towns are added to this list as they are completed. The layer is based on information from various sources collected and compiled during the period from March 2005 through the present. These sources include but are not limited to municipal Assessor's records (the Assessor's database, hard copy maps and deeds) and existing digital parcel data. The layer represents conditions as of the date of research at each city or town hall. The Protected Open Space layer includes the parcel shape (geometry), a project-specific parcel ID based on the Town and Town Assessor's lot numbering system, and system-defined (automatically generated) fields. The Protected Open Space layer has an accompanying table containing more detailed information about each feature (parcel). This table is called Protected Open Space Dat, and can be joined to Protected Open Space in ArcMap using the parcel ID (PAR_ID) field. Detailed information in the Protected Open Space Data attribute table includes the Assessor's Map, Block and Lot numbers (the Assessor's parcel identification numbering system), the official name of the parcel (such as the park or forest name if it has one), address and owner information, the deed volume and page numbers, survey information, open space type, the unique parcel ID number (Par_ID), comments collected by researchers during city/town hall visits, and acreage. This layer does not include parcels that do not meet the definition of open space as defined above. Features are stored as polygons that represent the best available locational information, and are "best fit" to the land base available for each.

The Connecticut Department of Environmental Protection's (CTDEP) Permanently Protected Open Space Phase Mapping Project Phase 1 (Protected Open Space Phase1) layer includes permanently protected open space parcels in towns in Phase 1 that meet the CTDEP's definition for this project, the Permanently Protected Open Space Mapping (CT POSM) Project. The CTDEP defines permanently protected open space as (1) Land or interest in land acquired for the permanent protection of natural features of the state's landscape or essential habitat for endangered or threatened species; or (2) Land or an interest in land acquired to permanently support and sustain non facility-based outdoor recreations, forestry and fishery activities, or other wildlife or natural resource conservation or preservation activities.

Towns in Phase 1 of the CT POSM project are situated along the CT coast and portions of the Thames River and are the following: Branford, Bridgeport, Chester, Clinton, Darien, Deep River, East Haven, East Lyme, Essex, Fairfield, Greenwich, Groton, Guilford, Hamden, Ledyard, Lyme, Madison, Milford, Montville, New Haven, New London, North Branford, North Haven, Norwalk, Norwich, Old Lyme, Old Saybrook, Orange, Preston, Shelton, Stamford, Stonington, Stratford, Waterford, West Haven, Westbrook, Westport.

For the purposes of the project a number of categories or classifications of open space have also been created. These include: Land Trust, Land Trust with buidlings, Private, Private with buildings, Utility Company, Utility Company with buildings, Federal, State, Municipal, Municipal with buildings, Conservation easement, and non-DEP State land. The layer is based on information from various sources collected and compiled during the period from August 2002 trhough October 2003. These sources include municipal Assessor's records (the Assessor's database, hard copy maps and deeds) and existing digital parcel data. The layer represents conditions on the date of research at each city or town hall.

The Protected Open Space Phase1 layer includes the parcel shape (geometry), a project-specific parcel ID based on the Town and Town's Assessor lot numbering system, and system-defined (automatically generated) fields. In addition, the Protected_Open_Space_Phase1 layer has an accompanying table containing more detailed information about each parcel's collection, standardization and storage. This table is called Protected Open Space Phase1 Data and can be joined to Protected Open Space Phase1 in ArcMap using the parcel ID (PAR_ID) field. Detailed information includes the Assessor's Map, Block and Lot numbers (the Assessor's parcel identification numbering system), the official name of the parcel (such as the park or forest name if it has one), address and owner information, the deed volume and page numbers, survey information, open space type, the project-specific parcel ID number (Par_ID), comments collected by researchers during city/town hall visits, acreage collected during site reconaissance and the data source. This layer does not include parcels that do not meet the definition of open space as defined above. Features are stored as polygon feature type that represent the best available locational information, i.e. "best fit" to the land base available for each.

Phase 1 of the Protected Open Space Mapping (POSM) Project was accomplished by a contractor using only a querying process to identify open space. The contractor obtained assessor's data from the various towns and created programs to cull open space parcels strictly by query processes. We have found many errors and omissions in the data, but at this point in the project we cannot revisit all the coastal towns. Therefore, this data is being sent with a disclaimer for accuracy. You are welcome to use it but not to publish it. Please note that we do not include any water company parcels despite them being listed as part of our criteria because we must first obtain written clarification and clearance from the U.S. Department of Homeland Security.

We have since changed our data collection method for Phase 2 of this project. DEP staff now visit each town hall and thoroughly research the land records. The project is expected to be complete by 2010.

These spatial-index maps act as an important finding aid for map collections in libraries. They serve as a spatial 'table of contents' for the maps contained in a series of maps and are important for users to determine which sheet covers a particular location–-information that cannot be adequately described in a traditional catalog record.

The dataset contains daily grass-reference evapotranspiration (ETo) maps stored as ASCII files. ETo at a 2 km spatial resolution are calculated statewide using the American Society of Civil Engineers version of the Penman-Monteith equation (ASCE-PM). Required input parameters for the ASCE-PM ETo equation are solar radiation, air temperature, relative humidity, and wind speed at two meters height. These parameters are estimated for each 2 km pixel using various methods.

Daily solar radiation is generated from the visible band of the National Oceanic and Atmospheric Administration's (NOAA) Geostationary Operational Environmental Satellite (GOES) using the Heliosat-II model. This model is designed to convert images acquired by the Meteosat satellite into maps of global (direct plus diffused) irradiation received at ground level.

This dataset comprises land use maps of Maputo city, with exception of the KaTembe urban district, for the years 1964, 1973, 1982, 1991 and 2001. It is the digital version of the land use maps published by Henriques [1] and revised under the LUCO research project.

The land use of Maputo city was identified from: i) aerial photographs (1964, 1982, 1991), orthophoto maps (1973) and IKONOS images (2001); ii) documentary sources, such as the Urbanization Master Plan (1969) and the Maputo City Addressing (1997); iii) the recognition made during several field survey campaigns. The methodology is described in Henriques [1].

Land use was classified into three levels, resulting from a hierarchical classification system, including descriptive and parametric classes. Levels I and II are available in this repository.

Level I, composed by 10 classes, contains the main forms of occupation: built-up areas (residential, economic activity, equipment, and infrastructure) and non-built-up areas (vacant or "natural"). It is geared towards analyses that serve policymaking and resource management at the regional or national scale [1].

Level II, composed by 31 classes, discriminates the higher hierarchical level according to its functional land use to become useful for municipal planning and management in municipal master plans, for example [1].

Maps are available in shapefile format and include predefined symbology-legend files, for QGIS and ArcGIS (v.10.7 or higher). The urban land use classes are described in Portuguese and English, and their meaning is provided as an accompanying document (ULU_Maputo_Nomenclatura_PT.pdf / ULU_Maputo_Nomenclature_EN.pdf).

Data format: vector (shapefile, polygon)

Reference system: WGS84, UTM 36S (EPSG:32736)

Original minimum mapping unit: 25 m2

Urban Land Use dataset attributes:

[N_I_C] – code of level I

[N_I_D_PT] – name of level I, in Portuguese

[N_I_D_EN] - name of level I, in English

[N_II_C] – code of level II

[N_II_D_PT] - name of level II, in Portuguese

[N_II_D_EN] - name of level II, in English

Funding: this research was supported by national funds through FCT – Fundação para a Ciência e Tecnologia, I.P. Project number: FCT AGA-KHAN/ 541731809 / 2019

[1] Henriques, C.D. (2008). Maputo. Cinco décadas de mudança territorial. O uso do solo observado por tecnologias de informação geográfica [Maputo. Five decades of territorial transformation. Land use assessed by geographical information technologies]. Lisboa, Instituto Português de Apoio ao Desenvolvimento (ISBN: 978-972-8975-22-7).

The PacificMap is a platform developed by CSIRO Data61 and the Pacific Data Hub (PDH) in collaboration with the Pacific Community Secretariat (SPC), as part of the Asia - Pacific for Development Initiative (D4D). The PacificMap is a platform for map-based access to spatial data from 22 Pacific Island Countries and Territories. It will lower the barrier and enhance access to timely, relevant and useful data for government and non-government organisations, businesses and communities throughout the Pacific.

The PacificMap... * provides easy access to authoritative and other spatial data to government, business and the public * facilitates the opening of data by federal, state and local government bodies * provides an open framework of geospatial data services that supports commercial and community innovation * allows to create and share interactgive stories directly from your map

To see what data is available on the Pacific Map, refer to the Data Catalogue in the Pacific Map itself. Click the Add data button and expand a category to browse.

description: A spatial database was created for the Drewes (1980) tectonic map of southeast Arizona: this database supercedes Drewes and others (2001, ver. 1.0). The west tectonic map (Drewes, 1980) was converted to digital format by Optronics Specialty Co., Inc. and published in 2001. Staff and a contractor at the U.S. Geological Survey in Tucson, Arizona developed a digital geologic map database for the east map in 2001, made revisions to the previously released digital data for the west map (Drewes and others, 2001, ver. 1.0), merged data files for the east and west sheets, and added additional data not previously captured.; abstract: A spatial database was created for the Drewes (1980) tectonic map of southeast Arizona: this database supercedes Drewes and others (2001, ver. 1.0). The west tectonic map (Drewes, 1980) was converted to digital format by Optronics Specialty Co., Inc. and published in 2001. Staff and a contractor at the U.S. Geological Survey in Tucson, Arizona developed a digital geologic map database for the east map in 2001, made revisions to the previously released digital data for the west map (Drewes and others, 2001, ver. 1.0), merged data files for the east and west sheets, and added additional data not previously captured.

Abstract This research investigates subjective user preference for using Floor Plans and Schematic Maps in an indoor environment, and how users locate and orient themselves when using these representations. We sought to verify the efficiency of these two kinds of digital maps and evaluate which elements found in physical environments and which elements found in the representations influence the user spatial orientation process. Users answered questions and performed orientation tasks which indicated their level of familiarity with the area being studied, their understanding of the symbology used, and their identification of Points of Interest (POI) in the environment. The initial results indicated a preference for the Schematic Map, because users thought that the symbology used on the map adopted was easy to understand.

The geospatial dataset maps organic carbon (OC) storage (kg OC m-2) and OC stocks (tonnes OC) of surficial soils across 438 Great British saltmarshes. The OC density for the surficial soils (top 10 cm) is mapped across 451.65 km2 of saltmarshes, identified from current saltmarsh maps of Great Britain’s three constituent countries; Scotland, England and Wales The spatial maps are built upon surficial (top 10 cm) soil bulk density and carbon data produced by the NERC C-Side project and Marine Scotland data combined with existing saltmarsh vegetation maps. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1.

description: The paper geologic map of the east part of the Pullman 1 x 2 -degree quadrangle, Idaho (Rember and Bennett, 1979) was scanned and initially attributed by Optronics Speciality Corp. Inc. (Northride, CA) and remitted to the U.S. Geological Survey for furter attribution and publication of the geospatial digital files. The resulting digital geologic map GIS can be queried in many ways to produce a variety of geological maps.; abstract: The paper geologic map of the east part of the Pullman 1 x 2 -degree quadrangle, Idaho (Rember and Bennett, 1979) was scanned and initially attributed by Optronics Speciality Corp. Inc. (Northride, CA) and remitted to the U.S. Geological Survey for furter attribution and publication of the geospatial digital files. The resulting digital geologic map GIS can be queried in many ways to produce a variety of geological maps.

This file set includes:Two raster datasets of marine ecosystems in Spencer Gulf produced for a cumulative impact assessment. There is one raster for the benthic ecosystems and one for the pelagic ecosystem. For each of the rasters there is an associated projection file with the same name.Two tiff files of the ecosystem maps (illustrating what they look like when plotted)A metadata text file with details of the spatial data layers and their projection - as well as sources of further information.

Datasets- simple_land_cover1.tif - an example land cover dataset presented in Figures 1 and 2- simple_landform1.tif - an example landform dataset presented in Figures 1 and 2- landcover_europe.tif - a land cover dataset with nine categories for Europe - landcover_europe.qml - a QGIS color style for the landcover_europe.tif dataset- landform_europe.tif - a landform dataset with 17 categories for Europe - landform_europe.qml - a QGIS color style for the landform_europe.tif dataset- map1.gpkg - a map of LTs in Europe constructed using the INCOMA-based method- map1.qml - a QGIS color style for the map1.gpkg dataset- map2.gpkg - a map of LTs in Europe constructed using the COMA method to identify and delineate pattern types in each theme separately- map2.qml - a QGIS color style for the map2.gpkg dataset- map3.gpkg - a map of LTs in Europe constructed using the map overlay method- map3.qml - a QGIS color style for the map3.gpkg dataset