(2) binary snow maps derived from the land cover maps

This layer can be used to view parcel property boundaries in the County of Burlington, NJ. Note that the property boundaries displayed here are not survey grade and are intended for planning level purposes. Most are based on tax maps which were digitized and then aligned to aerial photography (geo-referenced).

Land Cover Map 2021 (LCM2021) is a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2021. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2021. Land cover maps describe the physical material on the surface of the country. For example grassland, woodland, rivers & lakes or man-made structures such as roads and buildingsThis is a 10 m Classified Pixel dataset, classified to create a single mosaic of national cover. Provenance and quality:UKCEH’s automated land cover classification algorithms generated the 10m classified pixels. Training data were automatically selected from stable land covers over the interval of 2017 to 2019. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.Land cover was validated by organising the pixel classification into a land parcel framework (the LCM2021 Classified Land Parcels product). The classified land parcels were compared to known land cover producing confusion matrix to determine overall and per class accuracy.View full metadata information and download the data at catalogue.ceh.ac.uk

Approximate boundaries for all land parcels in New Brunswick. The boundaries are structured as Polygons. The Property Identifier number or PID is included for each parcel.

To access parcel information:Enter an address or zoom in by using the +/- tools or your mouse scroll wheel. Parcels will draw when zoomed in.Click on a parcel to display a popup with information about that parcel.Click the "Basemap" button to display background aerial imagery.From the "Layers" button you can turn map features on and off.Complete Help (PDF)Parcel Legend:Full Map LegendAbout this ViewerThis viewer displays land property boundaries from assessor parcel maps across Massachusetts. Each parcel is linked to selected descriptive information from assessor databases. Data for all 351 cities and towns are the standardized "Level 3" tax parcels served by MassGIS. More details ...Read about and download parcel dataUpdatesV 1.1: Added 'Layers' tab. (2018)V 1.2: Reformatted popup to use HTML table for columns and made address larger. (Jan 2019)V 1.3: Added 'Download Parcel Data by City/Town' option to list of layers. This box is checked off by default but when activated a user can identify anywhere and download data for that entire city/town, except Boston. (March 14, 2019)V 1.4: Data for Boston is included in the "Level 3" standardized parcels layer. (August 10, 2020)V 1.4 MassGIS, EOTSS 2021

NZ Parcel Boundaries Wireframe provides a map of land, road and other parcel boundaries, and is especially useful for displaying property boundaries.
This map service is for visualisation purposes only and is not intended for download. You can download the full parcels data from the NZ Parcels dataset.
This map service provides a dark outline and transparent fill, making it perfect for overlaying on our basemaps or any map service you choose.
Data for this map service is sourced from the NZ Parcels dataset which is updated weekly with authoritative data direct from LINZ’s Survey and Title system. Refer to the NZ Parcel layer for detailed metadata.
To simplify the visualisation of this data, the map service filters the data from the NZ Parcels layer to display parcels with a status of 'current' only.
This map service has been designed to be integrated into GIS, web and mobile applications via LINZ’s WMTS and XYZ tile services. View the Services tab to access these services.
See the LINZ website for service specifications and help using WMTS and XYZ tile services and more information about this service.

This collection of geo-referenced photos vary with regards to spatial accuracy and resolution. Use the hotlinks below to learn the details of each collection or review MassGIS's new story map explaining all the vintages of aerial photos. Tip: Reviewing that story map might be an easier way to digest the information rather than reviewing the more formal/standard metadata accessible via the hotlinks below.Within the web map certain layers will only be visible at particular zoom extents. If a layer is unavailable to turn on/off, then zoom in or out as needed until the layer becomes active.All photos, except year 1938, are captured during leaf-off (typically late winter/early spring). With the exception of the 1938 & 1990s collection, all photos are in true color. The 1938 & 1990s are in black and white. With regards to Dukes County (which includes the Islands of Martha's Vineyard and the Elizabeth Islands) these are the applicable years of acquisition for those State-wide collections that span multiple years: "1990s collection" -- Only year 1999 for Dukes County"2001-2003 collection" -- Only year 2003 for Dukes County"2008-2009 collection" - Only year 2009 for Dukes County"2011-2012 collection" - Only year 2011 for Dukes County"2013-2014 collection" - Only year 2014 for Dukes CountyPhoto Details (Metadata)1938 Black & White Aerials (georeferenced & hosted by Harvard Forest)1990s Black & White Aerials2001-2003 Color Aerials2005 Color Aerials2008-2009 Color Aerials2011-2012 Color Aerials2013-2014 Color Aerials2015 Satellite Images - Extra Details2019 Color Aerials2021 Color Aerials2023 Color AerialsParcel Lines -- These data are NOT survey grade and are intended for general reference only. The parcel data comply with the MassGIS Level 3 parcel data standard. Each town in Dukes County hires a GIS Consultant to prepare their digital parcel lines and to link the properties to the respective records from the town's assessing database. The linkage is static and not updated in real-time - it is only 'as current' as the day the data was exported from the assessing database. The Martha's Vineyard Commission does not edit nor maintain any assessing data or parcel lines/property bounds. Each town within Dukes County updates their digital parcel data when they see fit (most, typically, update annually). Click on a specific town in this map to see when their parcel data was updated and by whom. Similarly, clicking on a parcel in this "MA Aerial Photos Since 1990s web map" will show you the applicable Fiscal Year the assessing info was exported.

The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) collaborated on the creation of the global land datasets using Landsat data from 1972 through 2008. NASA and the USGS have again partnered to develop the Global Land Survey 2010 (GLS2010), a new global land data set with core acquisition dates of 2008-2011. This dataset consists of both Landsat TM and ETM+ images that meet quality and cloud cover standards established by the earlier GLS collections. Data acquired in 2011 were used to fill areas of low image quality or excessive cloud cover.

This dataset consists of the vector version of the Land Cover Map 2015 (LCM2015) for Great Britain. The vector data set is the core LCM data set from which the full range of other LCM2015 products is derived. It provides a number of attributes including land cover at the target class level (given as an integer value and also as text), the number of pixels within the polygon classified as each land cover type and a probability value provided by the classification algorithm (for full details see the LCM2015 Dataset Documentation). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019.

This data layer is an Esri file geodatabase polygon feature class that contains parcel boundaries maintained by county agencies in Indiana. It was released by the Indiana Geographic Information Office (IGIO) on November 13, 2024. The IGIO compiled the data as part of the Indiana Data Harvest program between the Indiana Geographic Information Council (IGIC) and Indiana local governments to provide the most accurate framework data for the citizens of Indiana. These layers include address points, street centerlines, land parcels, and governmental boundaries.

The satellite image of Canada is a composite of several individual satellite images form the Advanced Very High Resolution Radiometre (AVHRR) sensor on board various NOAA Satellites. The colours reflect differences in the density of vegetation cover: bright green for dense vegetation in humid southern regions; yellow for semi-arid and for mountainous regions; brown for the north where vegetation cover is very sparse; and white for snow and ice. An inset map shows a satellite image mosaic of North America with 35 land cover classes, based on data from the SPOT satellite VGT (vegetation) sensor.

Declassified satellite images provide an important worldwide record of land-surface change. With the success of the first release of classified satellite photography in 1995, images from U.S. military intelligence satellites KH-7 and KH-9 were declassified in accordance with Executive Order 12951 in 2002. The data were originally used for cartographic information and reconnaissance for U.S. intelligence agencies. Since the images could be of historical value for global change research and were no longer critical to national security, the collection was made available to the public.

Keyhole (KH) satellite systems KH-7 and KH-9 acquired photographs of the Earth’s surface with a telescopic camera system and transported the exposed film through the use of recovery capsules. The capsules or buckets were de-orbited and retrieved by aircraft while the capsules parachuted to earth. The exposed film was developed and the images were analyzed for a range of military applications.

The KH-7 surveillance system was a high resolution imaging system that was operational from July 1963 to June 1967. Approximately 18,000 black-and-white images and 230 color images are available from the 38 missions flown during this program. Key features for this program were larger area of coverage and improved ground resolution. The cameras acquired imagery in continuous lengthwise sweeps of the terrain. KH-7 images are 9 inches wide, vary in length from 4 inches to 500 feet long, and have a resolution of 2 to 4 feet.

The KH-9 mapping program was operational from March 1973 to October 1980 and was designed to support mapping requirements and exact positioning of geographical points for the military. This was accomplished by using image overlap for stereo coverage and by using a camera system with a reseau grid to correct image distortion. The KH-9 framing cameras produced 9 x 18 inch imagery at a resolution of 20-30 feet. Approximately 29,000 mapping images were acquired from 12 missions.

The original film sources are maintained by the National Archives and Records Administration (NARA). Duplicate film sources held in the USGS EROS Center archive are used to produce digital copies of the imagery.

This map displays the location of all open spaces owned and managed by the Watershed Protection Department. The following information about each open space is included: location, owner, property type, maintenance programs.

The flight and images produced under this task order have been supplied to Nez Perce County for use in the development of the geographic information system (GIS) for the county of Nez Perce, Idaho and Lewis Clark Valley area. Digital orthophotos are aerial images corrected for displacement caused by relief in the Earth's surface, camera/sensor lens distortion and tilting of the sensor at the time of image acquisition. Additionally, orthophotos are assigned a uniform scale, which allows an end-user the ability to derive accurate measurements from the imagery. Orthophotos can be used as an accurate record of landscape conditions at the time of the corresponding aerial imagery. As such, the digital orthophotos are used in a variety of applications, such as environmental monitoring, facility engineering/maintenance, city/county planning, property line review, etc. The digital orthophoto can be used alone or as a raster base map for corresponding vector line mapping. These data are horizontally referenced to the North American Datum of 1983 (NAD83) 2011, Idaho: State Plane Idaho West Zone (Idaho portions) and vertically referenced to the North American Vertical Datum of NAVD 1988. Survey Feet have been adjusted to ground for the Idaho portions. Units are in U.S. Foot.

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2018(LCM2018) representing Great Britain. It describes Great Britain's land cover in 2018 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2018 20m classified pixels dataset. All further LCM2018 datasets for Great Britain are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value, and a range of per-parcel pixel statistics to help to assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2018 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2018. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2018. LCM2018 was simultaneously released with LCM2017 and LCM2019. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

Two satellite images maps of Mt Ruker and Mt Rymill in the Australian Antarctic Territory were produced by the Australian Antarctic Division in 1998. Both maps are at a scale of 1:100 000 using Landsat TM imagery.

Data source: Mount Ruker - Landsat TM imagery, scenes 128/112, acquired 29 November 1989. Mount Rymill - Landsat TM imagery, scenes 128/111 and 128/112, acquired 18 March 1989 and 29 November 1989 respectively.

Nomenclature: Names have been approved by the Antarctic Names Committee of Australia. Please see the URL link for details on the images and processes used to produce these maps.

This is the 25m rasterised land parcels dataset for the UKCEH Land Cover Map of 2019 (LCM2019) representing Great Britain. It describes Great Britain's land cover in 2019 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived by rasterising the corresponding LCM2019 land parcels dataset into 25m pixels. It is provided as a 3-band, 8-bit integer raster. The first band is the UKCEH Land Cover Class identifier. Bands 2 and 3 are indicators of classification confidence. For a fuller description please refer to the product documentation. LCM2019 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2019. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2019. LCM2019 was simultaneously released with LCM2017 and LCM2018. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/f15289da-6424-4a5e-bd92-48c4d9c830cc

This dataset contains Barrow Area Remote Sensing - Brw Be Land Cover data. Cloud free Quickbird satellite imagery was used to develop the land cover maps in this study. The dataset is composed of four multispectral (2.4m) and one panchromatic (0.6m) band. The multispectral bands were fused with the panchromatic scene using a Principal Components sharpening method, which characteristically maintains spatial and spectral quality (Vijayaraj et al., 2006). Ten land cover types were chosen for the land cover classification. These included seven vegetated land cover types identified from cluster analysis of plot level species cover data from the International Tundra Experiment (ITEX) and resampled International Biological Program (IBP) plots, bare ground, ice/snow/urban areas, and water.

This dataset consists of the 1km raster, percentage target class version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 1km percentage product provides the percentage cover for each of 21 land cover classes for 1km x 1km pixels. This product contains one band per target habitat class (producing a 21 band image). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019. Full details about this dataset can be found at https://doi.org/10.5285/505d1e0c-ab60-4a60-b448-68c5bbae403e

This dataset represents a high resolution urban land cover classification map across the southern California Air Basin (SoCAB) with a spatial resolution of 60 cm in urban regions and 10 m in non-urban regions. This map was developed to support NASA JPL-based urban biospheric CO2 modeling in Los Angeles, CA. Land cover classification was derived from a novel fusion of Sentinel-2 (10-60 m x 10-60 m) and 2016 NAIP (60 cm x 60 cm) imagery and provides identification of impervious surface, non-photosynthetic vegetation, shrub, tree, grass, pools and lakes.

Land Cover Classes in .tif file: 0: Impervious surface 1: Tree (mixed evergreen/deciduous) 2: Grass (assumed irrigated) 3: Shrub 4: Non-photosynthetic vegetation 5: Water (masked using MNDWI/NDWI)

Google Earth Engine interactive app displaying this map: https://wcoleman.users.earthengine.app/view/socab-irrigated-classification

A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Support from the Earth Science Division OCO-2 program is acknowledged. Copyright 2020. All rights reserved.